LayerRx Mapping ID
364
Slot System
Featured Buckets
Featured Buckets Admin

Retrospective Cohort Study of the Prevalence of Off-label Gabapentinoid Prescriptions in Hospitalized Medical Patients

Article Type
Changed
Tue, 09/17/2019 - 23:19

In the1990s, gabapentin was licensed in the United States as an anticonvulsant and it became widely successful in the mid-2000s when marketed for the treatment of pain. Since then, prescriptions for gabapentinoids have accelerated dramatically.1,2 Between 2012 and 2016, the total spending on pregabalin in the United States increased from $1.9 to $4.4 billion, with pregabalin ranking eighth overall for specific drug spending.3

Despite a finite number of indications, there has been a steady rise in off-label use, with an increased risk of adverse drug events (ADEs).4,5 Several meta-analyses suggest either low-quality or no evidence of benefit for gabapentinoid use in settings including neuropathic pain in cancer, sciatica, and chronic low back pain.6-8 Lack of efficacy is compounded by adverse effects such as altered mental status, fluid retention, sedation, and increased risk of traumatic falls in older adults.6,9,10 Finally, dependency is a concern; opioids are coprescribed in up to 50% of patients,11 increasing the odds of opioid-related death by up to 60%.12

To better characterize gabapentinoid use in hospitalized patients, we analyzed a retrospective cohort of patients admitted to our tertiary care medical teaching unit, examining preadmission and in-hospital prescribing trends, off-label use, and deprescribing.

METHODS

Patient data were collected from a retrospective cohort, including all consecutive admissions to our 52-bed medical clinical teaching unit in Montréal, Canada, since December 2013.13 We reviewed admissions between December 17, 2013 and June 30, 2017 and identified three populations of gabapentinoid users from medication reconciliation documents: preadmission users continued at discharge, preadmission users deprescribed in hospital, and new in-hospital users continued at discharge. Deprescribing was defined as having the drug stopped at discharge or a prescribed taper that included stopping. The term “gabapentinoid users” refers to preadmission gabapentinoid use.

Gabapentinoid users were compared with nonusers with regard to demographic characteristics; select comorbidities; coprescription of opioids, benzodiazepines, and Z-drugs; length of stay (LOS); and inpatient mortality. Only the first eligible admission per patient was considered. Patients who had multiple admissions over the period of interest were classified as “users” in the patient-level analyses if they were taking a gabapentinoid at home or at discharge on at least one admission.

Doses and indications were collected from medication reconciliation performed by a clinical pharmacist, which included an interview with the patient or a proxy and a review of the indications for all drugs. These data were merged with any additional potential indications found in the admission notes (listing all chronic conditions from a detailed medical history) and review of the electronic medical record. The US Food and Drug Administration (FDA) approved the indications and the recommended doses were taken from product monographs and compared with doses prescribed to patients. When documented, the reason for new prescriptions and justification for deprescribing at discharge were manually abstracted from discharge summaries and medication reconciliation documents.

Continuous variables were expressed as median and interquartile range (IQR) and compared using the Wilcoxon rank-sum test. Categorical variables were compared using the χ2 test. Proportions of gabapentinoid use and deprescribing, including 95% confidence intervals around each proportion, were plotted and linear regression was performed versus fiscal quarter to evaluate for temporal trends. A two-sided α value of 0.05 was considered to be statistically significant. Statistical analyses were performed using Stata version 15 (StataCorp LLC, College Station, Texas). The McGill University Health Centre Research Ethics Board approved this study.

 

 

RESULTS

A total of 4,103 unique patients were admitted from December 2013 to July 2017, of whom 550 (13.4%) were receiving a gabapentinoid before admission. Two preadmission users were coprescribed gabapentin and pregabalin for a total of 552 prescriptions. The prevalence of preadmission gabapentinoid use remained steady during the period of interest (Appendix 1; P = .29 for temporal trend). There were no significant differences between gabapentinoid users and nonusers with regard to age or sex, but users had a higher prevalence of chronic disease (Table 1). In addition, compared with nonusers, gabapentinoid users were more likely to be coprescribed opioids (28.2% vs 12%; P < .01), benzodiazepines (24.5% vs 14.3%; P < .01), and nonbenzodiazepine sedative hypnotics (7.5% vs 3.6%; P < .01). Of note, 10.2% of gabapentinoid users were simultaneously coprescribed both opioids and benzodiazepines versus. 3.6% of nonusers (P < .01; Table 1). Nonetheless, there was no statistically significant difference between users and nonusers with regard to inpatient mortality (10% vs 12%; P = .17).

The indications for gabapentinoid use are presented in Table 2. Only a minority (17% or 94/552) had an approved indication. Among these 94 patients, 38 (40%) received FDA-recommended doses, 47 (50%) received doses below those demonstrated to be effective, and 9 (10%) received higher-than-recommended doses. New prescriptions at discharge were observed in 1.5% of patients, with the majority given for off-label indications (Appendix 2).

Gabapentinoids were deprescribed in 65/495 preadmission users who survived to discharge (13.1%) and 33/495 patients (6.7%) had their dose decreased without a further plan to taper (Table 1). Approximately 50% of patients with a gabapentinoid deprescribed did not have a documented justification for cessation; however, when present, commonly cited reasons included ADEs (eg, impaired cognition, falls, edema) or the absence of an identified reason for ongoing use (Appendix 3). The proportion of patients who had a gabapentinoid deprescribed did not change over the study period (Appendix 4; P = .77 for temporal trend).

DISCUSSION

In this large cohort study of hospitalized medical patients, preadmission gabapentinoid use was present in one in every eight admitted patients. Most patients had off-label indications, including the small number of patients who had the drug started in hospital. Even for approved indications, the doses were often lower than what trials have suggested to be effective. Finally, although we have demonstrated that deprescribing occurred, it was uncommon and either precipitated by an adverse event or the justification was poorly documented.

To our knowledge, our study is one of the first to examine what happens to gabapentinoids in hospitalized patients and we present important new data with respect to dosing and prescribing patterns. The low rates of discontinuation, intent to taper, or dose decreases in our cohort represent a potential area of improvement in deprescribing.

Deprescribing should be considered for patients with serious adverse events, for whom less serious adverse effects preclude achieving clinically effective doses, and for those who do not perceive benefit. Given the magnitude of the problems presented by polypharmacy, we propose that stopping priority be given to off-label use (especially when clinically ineffective) and for patients coprescribed opioids or sedatives. Up to a third of users in our cohort were coprescribed opioids or benzodiazepines, which is particularly concerning given the association with increased opioid-related mortality.12,15 Although we did not observe a difference in inpatient mortality, such a study is underpowered for this outcome especially when considering the competing risks of death in hospital. Importantly, when deprescribing, the drug should be tapered over several weeks to limit symptoms of withdrawal and to prevent seizure.11

Presumed off-label use and subtherapeutic doses were common in our cohort, with only 17% of users having a clearly documented FDA-approved indication, in agreement with a previous study that reported only 5% on-label use.4 High doses of gabapentinoids required for efficacy in clinical trials may be difficult to achieve because of dose-limiting side effects, which may explain the relatively low median doses recorded in our real-world cohort. Another possibility is that frail, older patients with renal dysfunction experience effectiveness at lower median doses than those quoted from study populations. In our study, patients on lower doses of gabapentinoids had a higher prevalence of stage IV or V chronic kidney disease (CKD). Stage IV/V CKD was identified in 16/47 (34.0%) patients on lower doses of gabapentinoids, compared to 4/38 (10.5%) on doses within the FDA-recommended range.

Our study has limitations; findings from a single Canadian tertiary care hospital may not be generalizable to other hospitals or countries, particularly given the differences between the Canadian and US health systems. Indications were extracted from the patient chart and even with the best possible medication history and thorough review, sometimes they had to be inferred. Caution should also be exercised when interpreting the omission of an indication as equating to a lack of justifiable medication use; however, the rate of off-label use in our cohort is in agreement with prior research.4 Moreover, with a retrospective design, the effectiveness of the drug on an individual basis could not be assessed, which would have allowed a more precise estimate of the proportion of patients for whom deprescribing might have been appropriate. The strengths of this study include a large sample of real-world, heterogeneous, general medical patients spanning several years and our use of trained pharmacists and physicians to determine the drug indication as opposed to reliance on administrative data.

 

 

CONCLUSION

Gabapentinoid use was frequent in our cohort of hospitalized medical patients, with a high prevalence of off-label use, subtherapeutic doses, and coadministration with opioids and benzodiazepines. Deprescribing at discharge was uncommon and often triggered by an adverse event. The identification of gabapentinoids during hospitalization is an opportunity to reevaluate the indication for the drug, assess for effectiveness, and consider deprescribing to help reduce polypharmacy and ideally ADEs.

Acknowledgment

For the purposes of authorship, Dr. McDonald and Dr. Lee contributed equally.

Disclosures

Dr. Emily McDonald and Dr. Todd Lee have a patent pending for MedSafer, a deprescribing software, and both receive research salary support from the Fonds de Recherche Santé du Québec. Dr. Gingras, Dr. Lieu, and Dr. Papillon-Ferland have nothing to disclose.

 

Files
References

1. Johansen ME. Gabapentinoid use in the United States 2002 through 2015. JAMA Intern Med. 2018;178(2):292-294. https://doi.org/10.1001/jamainternmed.2017.7856.
2. Kwok H, Khuu W, Fernandes K, et al. Impact of unrestricted access to pregabalin on the use of opioids and other CNS-active medications: a cross-sectional time series analysis. Pain Med. 2017;18(6):1019-1026. https://doi.org/10.1093/pm/pnw351.
3. Medicines use and spending in the U.S. — a review of 2016 and outlook to 2021: IMS Institute for Healthcare Informatics; 2017. https://structurecms-staging-psyclone.netdna-ssl.com/client_assets/dwonk/media/attachments/590c/6aa0/6970/2d2d/4182/0000/590c6aa069702d2d41820000.pdf?1493985952. Accessed March 21, 2019.
4. Hamer AM, Haxby DG, McFarland BH, Ketchum K. Gabapentin use in a managed medicaid population. J Manag Care Pharm. 2002;8(4):266-271. doi: 10.18553/jmcp.2002.8.4.266.
5. Eguale T, Buckeridge DL, Verma A, et al. Association of off-label drug use and adverse drug events in an adult population. JAMA Intern Med. 2016;176(1):55-63. https://doi.org/10.1001/jamainternmed.2015.6058.
6. Shanthanna H, Gilron I, Rajarathinam M, et al. Benefits and safety of gabapentinoids in chronic low back pain: a systematic review and meta-analysis of randomized controlled trials. PLoS Med. 2017;14(8):e1002369. https://doi.org/10.1371/journal.pmed.1002369.
7. Enke O, New HA, New CH, et al. Anticonvulsants in the treatment of low back pain and lumbar radicular pain: a systematic review and meta-analysis. CMAJ. 2018;190(26):E786-E793. https://doi.org/10.1503/cmaj.171333.
8. Kane CM, Mulvey MR, Wright S, Craigs C, Wright JM, Bennett MI. Opioids combined with antidepressants or antiepileptic drugs for cancer pain: systematic review and meta-analysis. Palliat Med. 2018;32(1):276-286. https://doi.org/10.1177/0269216317711826.
9. Zaccara G, Perucca P, Gangemi PF. The adverse event profile of pregabalin across different disorders: a meta-analysis. Eur J Clin Pharmacol. 2012;68(6):903-912. https://doi.org/10.1007/s00228-012-1213-x.
10. Huang AR, Mallet L, Rochefort CM, Eguale T, Buckeridge DL, Tamblyn R. Medication-related falls in the elderly: causative factors and preventive strategies. Drugs Aging. 2012;29(5):359-376. https://doi.org/10.2165/11599460-000000000-00000.
11. Evoy KE, Morrison MD, Saklad SR. Abuse and misuse of pregabalin and gabapentin. Drugs. 2017;77(4):403-426. https://doi.org/10.1007/s40265-017-0700-x.
12. Gomes T, Juurlink DN, Antoniou T, Mamdani MM, Paterson JM, van den Brink W. Gabapentin, opioids, and the risk of opioid-related death: a population-based nested case-control study. PLoS Med. 2017;14(10):e1002396. https://doi.org/10.1371/journal.pmed.1002396.
13. McDonald EG, Saleh RR, Lee TC. Ezetimibe use remains common among medical inpatients. Am J Med. 2015;128(2):193-195. https://doi.org/10.1016/j.amjmed.2014.10.016.
14. U.S. Food and Drug Administration. LYRICA - Highlights of Prescribing Information 2012. https://www.accessdata.fda.gov/drugsatfda_docs/label/2012/021446s028lbl.pdf. Accessed April 30, 2019.
15. U.S. Food and Drug Administration. NEURONTIN - Highlights of Prescribing Information 2017. https://www.accessdata.fda.gov/drugsatfda_docs/label/2017/020235s064_020882s047_021129s046lbl.pdf. Accessed April 30, 2019.
16. Gomes T, Greaves S, van den Brink W, et al. Pregabalin and the risk for opioid-related death: a nested case–control study. Ann Intern Med. 2018;169(10):732-734. https://doi.org/10.7326/M18-1136.

Article PDF
Issue
Journal of Hospital Medicine 14(9)
Topics
Page Number
547-550. Published online first May 10, 2019
Sections
Files
Files
Article PDF
Article PDF
Related Articles

In the1990s, gabapentin was licensed in the United States as an anticonvulsant and it became widely successful in the mid-2000s when marketed for the treatment of pain. Since then, prescriptions for gabapentinoids have accelerated dramatically.1,2 Between 2012 and 2016, the total spending on pregabalin in the United States increased from $1.9 to $4.4 billion, with pregabalin ranking eighth overall for specific drug spending.3

Despite a finite number of indications, there has been a steady rise in off-label use, with an increased risk of adverse drug events (ADEs).4,5 Several meta-analyses suggest either low-quality or no evidence of benefit for gabapentinoid use in settings including neuropathic pain in cancer, sciatica, and chronic low back pain.6-8 Lack of efficacy is compounded by adverse effects such as altered mental status, fluid retention, sedation, and increased risk of traumatic falls in older adults.6,9,10 Finally, dependency is a concern; opioids are coprescribed in up to 50% of patients,11 increasing the odds of opioid-related death by up to 60%.12

To better characterize gabapentinoid use in hospitalized patients, we analyzed a retrospective cohort of patients admitted to our tertiary care medical teaching unit, examining preadmission and in-hospital prescribing trends, off-label use, and deprescribing.

METHODS

Patient data were collected from a retrospective cohort, including all consecutive admissions to our 52-bed medical clinical teaching unit in Montréal, Canada, since December 2013.13 We reviewed admissions between December 17, 2013 and June 30, 2017 and identified three populations of gabapentinoid users from medication reconciliation documents: preadmission users continued at discharge, preadmission users deprescribed in hospital, and new in-hospital users continued at discharge. Deprescribing was defined as having the drug stopped at discharge or a prescribed taper that included stopping. The term “gabapentinoid users” refers to preadmission gabapentinoid use.

Gabapentinoid users were compared with nonusers with regard to demographic characteristics; select comorbidities; coprescription of opioids, benzodiazepines, and Z-drugs; length of stay (LOS); and inpatient mortality. Only the first eligible admission per patient was considered. Patients who had multiple admissions over the period of interest were classified as “users” in the patient-level analyses if they were taking a gabapentinoid at home or at discharge on at least one admission.

Doses and indications were collected from medication reconciliation performed by a clinical pharmacist, which included an interview with the patient or a proxy and a review of the indications for all drugs. These data were merged with any additional potential indications found in the admission notes (listing all chronic conditions from a detailed medical history) and review of the electronic medical record. The US Food and Drug Administration (FDA) approved the indications and the recommended doses were taken from product monographs and compared with doses prescribed to patients. When documented, the reason for new prescriptions and justification for deprescribing at discharge were manually abstracted from discharge summaries and medication reconciliation documents.

Continuous variables were expressed as median and interquartile range (IQR) and compared using the Wilcoxon rank-sum test. Categorical variables were compared using the χ2 test. Proportions of gabapentinoid use and deprescribing, including 95% confidence intervals around each proportion, were plotted and linear regression was performed versus fiscal quarter to evaluate for temporal trends. A two-sided α value of 0.05 was considered to be statistically significant. Statistical analyses were performed using Stata version 15 (StataCorp LLC, College Station, Texas). The McGill University Health Centre Research Ethics Board approved this study.

 

 

RESULTS

A total of 4,103 unique patients were admitted from December 2013 to July 2017, of whom 550 (13.4%) were receiving a gabapentinoid before admission. Two preadmission users were coprescribed gabapentin and pregabalin for a total of 552 prescriptions. The prevalence of preadmission gabapentinoid use remained steady during the period of interest (Appendix 1; P = .29 for temporal trend). There were no significant differences between gabapentinoid users and nonusers with regard to age or sex, but users had a higher prevalence of chronic disease (Table 1). In addition, compared with nonusers, gabapentinoid users were more likely to be coprescribed opioids (28.2% vs 12%; P < .01), benzodiazepines (24.5% vs 14.3%; P < .01), and nonbenzodiazepine sedative hypnotics (7.5% vs 3.6%; P < .01). Of note, 10.2% of gabapentinoid users were simultaneously coprescribed both opioids and benzodiazepines versus. 3.6% of nonusers (P < .01; Table 1). Nonetheless, there was no statistically significant difference between users and nonusers with regard to inpatient mortality (10% vs 12%; P = .17).

The indications for gabapentinoid use are presented in Table 2. Only a minority (17% or 94/552) had an approved indication. Among these 94 patients, 38 (40%) received FDA-recommended doses, 47 (50%) received doses below those demonstrated to be effective, and 9 (10%) received higher-than-recommended doses. New prescriptions at discharge were observed in 1.5% of patients, with the majority given for off-label indications (Appendix 2).

Gabapentinoids were deprescribed in 65/495 preadmission users who survived to discharge (13.1%) and 33/495 patients (6.7%) had their dose decreased without a further plan to taper (Table 1). Approximately 50% of patients with a gabapentinoid deprescribed did not have a documented justification for cessation; however, when present, commonly cited reasons included ADEs (eg, impaired cognition, falls, edema) or the absence of an identified reason for ongoing use (Appendix 3). The proportion of patients who had a gabapentinoid deprescribed did not change over the study period (Appendix 4; P = .77 for temporal trend).

DISCUSSION

In this large cohort study of hospitalized medical patients, preadmission gabapentinoid use was present in one in every eight admitted patients. Most patients had off-label indications, including the small number of patients who had the drug started in hospital. Even for approved indications, the doses were often lower than what trials have suggested to be effective. Finally, although we have demonstrated that deprescribing occurred, it was uncommon and either precipitated by an adverse event or the justification was poorly documented.

To our knowledge, our study is one of the first to examine what happens to gabapentinoids in hospitalized patients and we present important new data with respect to dosing and prescribing patterns. The low rates of discontinuation, intent to taper, or dose decreases in our cohort represent a potential area of improvement in deprescribing.

Deprescribing should be considered for patients with serious adverse events, for whom less serious adverse effects preclude achieving clinically effective doses, and for those who do not perceive benefit. Given the magnitude of the problems presented by polypharmacy, we propose that stopping priority be given to off-label use (especially when clinically ineffective) and for patients coprescribed opioids or sedatives. Up to a third of users in our cohort were coprescribed opioids or benzodiazepines, which is particularly concerning given the association with increased opioid-related mortality.12,15 Although we did not observe a difference in inpatient mortality, such a study is underpowered for this outcome especially when considering the competing risks of death in hospital. Importantly, when deprescribing, the drug should be tapered over several weeks to limit symptoms of withdrawal and to prevent seizure.11

Presumed off-label use and subtherapeutic doses were common in our cohort, with only 17% of users having a clearly documented FDA-approved indication, in agreement with a previous study that reported only 5% on-label use.4 High doses of gabapentinoids required for efficacy in clinical trials may be difficult to achieve because of dose-limiting side effects, which may explain the relatively low median doses recorded in our real-world cohort. Another possibility is that frail, older patients with renal dysfunction experience effectiveness at lower median doses than those quoted from study populations. In our study, patients on lower doses of gabapentinoids had a higher prevalence of stage IV or V chronic kidney disease (CKD). Stage IV/V CKD was identified in 16/47 (34.0%) patients on lower doses of gabapentinoids, compared to 4/38 (10.5%) on doses within the FDA-recommended range.

Our study has limitations; findings from a single Canadian tertiary care hospital may not be generalizable to other hospitals or countries, particularly given the differences between the Canadian and US health systems. Indications were extracted from the patient chart and even with the best possible medication history and thorough review, sometimes they had to be inferred. Caution should also be exercised when interpreting the omission of an indication as equating to a lack of justifiable medication use; however, the rate of off-label use in our cohort is in agreement with prior research.4 Moreover, with a retrospective design, the effectiveness of the drug on an individual basis could not be assessed, which would have allowed a more precise estimate of the proportion of patients for whom deprescribing might have been appropriate. The strengths of this study include a large sample of real-world, heterogeneous, general medical patients spanning several years and our use of trained pharmacists and physicians to determine the drug indication as opposed to reliance on administrative data.

 

 

CONCLUSION

Gabapentinoid use was frequent in our cohort of hospitalized medical patients, with a high prevalence of off-label use, subtherapeutic doses, and coadministration with opioids and benzodiazepines. Deprescribing at discharge was uncommon and often triggered by an adverse event. The identification of gabapentinoids during hospitalization is an opportunity to reevaluate the indication for the drug, assess for effectiveness, and consider deprescribing to help reduce polypharmacy and ideally ADEs.

Acknowledgment

For the purposes of authorship, Dr. McDonald and Dr. Lee contributed equally.

Disclosures

Dr. Emily McDonald and Dr. Todd Lee have a patent pending for MedSafer, a deprescribing software, and both receive research salary support from the Fonds de Recherche Santé du Québec. Dr. Gingras, Dr. Lieu, and Dr. Papillon-Ferland have nothing to disclose.

 

In the1990s, gabapentin was licensed in the United States as an anticonvulsant and it became widely successful in the mid-2000s when marketed for the treatment of pain. Since then, prescriptions for gabapentinoids have accelerated dramatically.1,2 Between 2012 and 2016, the total spending on pregabalin in the United States increased from $1.9 to $4.4 billion, with pregabalin ranking eighth overall for specific drug spending.3

Despite a finite number of indications, there has been a steady rise in off-label use, with an increased risk of adverse drug events (ADEs).4,5 Several meta-analyses suggest either low-quality or no evidence of benefit for gabapentinoid use in settings including neuropathic pain in cancer, sciatica, and chronic low back pain.6-8 Lack of efficacy is compounded by adverse effects such as altered mental status, fluid retention, sedation, and increased risk of traumatic falls in older adults.6,9,10 Finally, dependency is a concern; opioids are coprescribed in up to 50% of patients,11 increasing the odds of opioid-related death by up to 60%.12

To better characterize gabapentinoid use in hospitalized patients, we analyzed a retrospective cohort of patients admitted to our tertiary care medical teaching unit, examining preadmission and in-hospital prescribing trends, off-label use, and deprescribing.

METHODS

Patient data were collected from a retrospective cohort, including all consecutive admissions to our 52-bed medical clinical teaching unit in Montréal, Canada, since December 2013.13 We reviewed admissions between December 17, 2013 and June 30, 2017 and identified three populations of gabapentinoid users from medication reconciliation documents: preadmission users continued at discharge, preadmission users deprescribed in hospital, and new in-hospital users continued at discharge. Deprescribing was defined as having the drug stopped at discharge or a prescribed taper that included stopping. The term “gabapentinoid users” refers to preadmission gabapentinoid use.

Gabapentinoid users were compared with nonusers with regard to demographic characteristics; select comorbidities; coprescription of opioids, benzodiazepines, and Z-drugs; length of stay (LOS); and inpatient mortality. Only the first eligible admission per patient was considered. Patients who had multiple admissions over the period of interest were classified as “users” in the patient-level analyses if they were taking a gabapentinoid at home or at discharge on at least one admission.

Doses and indications were collected from medication reconciliation performed by a clinical pharmacist, which included an interview with the patient or a proxy and a review of the indications for all drugs. These data were merged with any additional potential indications found in the admission notes (listing all chronic conditions from a detailed medical history) and review of the electronic medical record. The US Food and Drug Administration (FDA) approved the indications and the recommended doses were taken from product monographs and compared with doses prescribed to patients. When documented, the reason for new prescriptions and justification for deprescribing at discharge were manually abstracted from discharge summaries and medication reconciliation documents.

Continuous variables were expressed as median and interquartile range (IQR) and compared using the Wilcoxon rank-sum test. Categorical variables were compared using the χ2 test. Proportions of gabapentinoid use and deprescribing, including 95% confidence intervals around each proportion, were plotted and linear regression was performed versus fiscal quarter to evaluate for temporal trends. A two-sided α value of 0.05 was considered to be statistically significant. Statistical analyses were performed using Stata version 15 (StataCorp LLC, College Station, Texas). The McGill University Health Centre Research Ethics Board approved this study.

 

 

RESULTS

A total of 4,103 unique patients were admitted from December 2013 to July 2017, of whom 550 (13.4%) were receiving a gabapentinoid before admission. Two preadmission users were coprescribed gabapentin and pregabalin for a total of 552 prescriptions. The prevalence of preadmission gabapentinoid use remained steady during the period of interest (Appendix 1; P = .29 for temporal trend). There were no significant differences between gabapentinoid users and nonusers with regard to age or sex, but users had a higher prevalence of chronic disease (Table 1). In addition, compared with nonusers, gabapentinoid users were more likely to be coprescribed opioids (28.2% vs 12%; P < .01), benzodiazepines (24.5% vs 14.3%; P < .01), and nonbenzodiazepine sedative hypnotics (7.5% vs 3.6%; P < .01). Of note, 10.2% of gabapentinoid users were simultaneously coprescribed both opioids and benzodiazepines versus. 3.6% of nonusers (P < .01; Table 1). Nonetheless, there was no statistically significant difference between users and nonusers with regard to inpatient mortality (10% vs 12%; P = .17).

The indications for gabapentinoid use are presented in Table 2. Only a minority (17% or 94/552) had an approved indication. Among these 94 patients, 38 (40%) received FDA-recommended doses, 47 (50%) received doses below those demonstrated to be effective, and 9 (10%) received higher-than-recommended doses. New prescriptions at discharge were observed in 1.5% of patients, with the majority given for off-label indications (Appendix 2).

Gabapentinoids were deprescribed in 65/495 preadmission users who survived to discharge (13.1%) and 33/495 patients (6.7%) had their dose decreased without a further plan to taper (Table 1). Approximately 50% of patients with a gabapentinoid deprescribed did not have a documented justification for cessation; however, when present, commonly cited reasons included ADEs (eg, impaired cognition, falls, edema) or the absence of an identified reason for ongoing use (Appendix 3). The proportion of patients who had a gabapentinoid deprescribed did not change over the study period (Appendix 4; P = .77 for temporal trend).

DISCUSSION

In this large cohort study of hospitalized medical patients, preadmission gabapentinoid use was present in one in every eight admitted patients. Most patients had off-label indications, including the small number of patients who had the drug started in hospital. Even for approved indications, the doses were often lower than what trials have suggested to be effective. Finally, although we have demonstrated that deprescribing occurred, it was uncommon and either precipitated by an adverse event or the justification was poorly documented.

To our knowledge, our study is one of the first to examine what happens to gabapentinoids in hospitalized patients and we present important new data with respect to dosing and prescribing patterns. The low rates of discontinuation, intent to taper, or dose decreases in our cohort represent a potential area of improvement in deprescribing.

Deprescribing should be considered for patients with serious adverse events, for whom less serious adverse effects preclude achieving clinically effective doses, and for those who do not perceive benefit. Given the magnitude of the problems presented by polypharmacy, we propose that stopping priority be given to off-label use (especially when clinically ineffective) and for patients coprescribed opioids or sedatives. Up to a third of users in our cohort were coprescribed opioids or benzodiazepines, which is particularly concerning given the association with increased opioid-related mortality.12,15 Although we did not observe a difference in inpatient mortality, such a study is underpowered for this outcome especially when considering the competing risks of death in hospital. Importantly, when deprescribing, the drug should be tapered over several weeks to limit symptoms of withdrawal and to prevent seizure.11

Presumed off-label use and subtherapeutic doses were common in our cohort, with only 17% of users having a clearly documented FDA-approved indication, in agreement with a previous study that reported only 5% on-label use.4 High doses of gabapentinoids required for efficacy in clinical trials may be difficult to achieve because of dose-limiting side effects, which may explain the relatively low median doses recorded in our real-world cohort. Another possibility is that frail, older patients with renal dysfunction experience effectiveness at lower median doses than those quoted from study populations. In our study, patients on lower doses of gabapentinoids had a higher prevalence of stage IV or V chronic kidney disease (CKD). Stage IV/V CKD was identified in 16/47 (34.0%) patients on lower doses of gabapentinoids, compared to 4/38 (10.5%) on doses within the FDA-recommended range.

Our study has limitations; findings from a single Canadian tertiary care hospital may not be generalizable to other hospitals or countries, particularly given the differences between the Canadian and US health systems. Indications were extracted from the patient chart and even with the best possible medication history and thorough review, sometimes they had to be inferred. Caution should also be exercised when interpreting the omission of an indication as equating to a lack of justifiable medication use; however, the rate of off-label use in our cohort is in agreement with prior research.4 Moreover, with a retrospective design, the effectiveness of the drug on an individual basis could not be assessed, which would have allowed a more precise estimate of the proportion of patients for whom deprescribing might have been appropriate. The strengths of this study include a large sample of real-world, heterogeneous, general medical patients spanning several years and our use of trained pharmacists and physicians to determine the drug indication as opposed to reliance on administrative data.

 

 

CONCLUSION

Gabapentinoid use was frequent in our cohort of hospitalized medical patients, with a high prevalence of off-label use, subtherapeutic doses, and coadministration with opioids and benzodiazepines. Deprescribing at discharge was uncommon and often triggered by an adverse event. The identification of gabapentinoids during hospitalization is an opportunity to reevaluate the indication for the drug, assess for effectiveness, and consider deprescribing to help reduce polypharmacy and ideally ADEs.

Acknowledgment

For the purposes of authorship, Dr. McDonald and Dr. Lee contributed equally.

Disclosures

Dr. Emily McDonald and Dr. Todd Lee have a patent pending for MedSafer, a deprescribing software, and both receive research salary support from the Fonds de Recherche Santé du Québec. Dr. Gingras, Dr. Lieu, and Dr. Papillon-Ferland have nothing to disclose.

 

References

1. Johansen ME. Gabapentinoid use in the United States 2002 through 2015. JAMA Intern Med. 2018;178(2):292-294. https://doi.org/10.1001/jamainternmed.2017.7856.
2. Kwok H, Khuu W, Fernandes K, et al. Impact of unrestricted access to pregabalin on the use of opioids and other CNS-active medications: a cross-sectional time series analysis. Pain Med. 2017;18(6):1019-1026. https://doi.org/10.1093/pm/pnw351.
3. Medicines use and spending in the U.S. — a review of 2016 and outlook to 2021: IMS Institute for Healthcare Informatics; 2017. https://structurecms-staging-psyclone.netdna-ssl.com/client_assets/dwonk/media/attachments/590c/6aa0/6970/2d2d/4182/0000/590c6aa069702d2d41820000.pdf?1493985952. Accessed March 21, 2019.
4. Hamer AM, Haxby DG, McFarland BH, Ketchum K. Gabapentin use in a managed medicaid population. J Manag Care Pharm. 2002;8(4):266-271. doi: 10.18553/jmcp.2002.8.4.266.
5. Eguale T, Buckeridge DL, Verma A, et al. Association of off-label drug use and adverse drug events in an adult population. JAMA Intern Med. 2016;176(1):55-63. https://doi.org/10.1001/jamainternmed.2015.6058.
6. Shanthanna H, Gilron I, Rajarathinam M, et al. Benefits and safety of gabapentinoids in chronic low back pain: a systematic review and meta-analysis of randomized controlled trials. PLoS Med. 2017;14(8):e1002369. https://doi.org/10.1371/journal.pmed.1002369.
7. Enke O, New HA, New CH, et al. Anticonvulsants in the treatment of low back pain and lumbar radicular pain: a systematic review and meta-analysis. CMAJ. 2018;190(26):E786-E793. https://doi.org/10.1503/cmaj.171333.
8. Kane CM, Mulvey MR, Wright S, Craigs C, Wright JM, Bennett MI. Opioids combined with antidepressants or antiepileptic drugs for cancer pain: systematic review and meta-analysis. Palliat Med. 2018;32(1):276-286. https://doi.org/10.1177/0269216317711826.
9. Zaccara G, Perucca P, Gangemi PF. The adverse event profile of pregabalin across different disorders: a meta-analysis. Eur J Clin Pharmacol. 2012;68(6):903-912. https://doi.org/10.1007/s00228-012-1213-x.
10. Huang AR, Mallet L, Rochefort CM, Eguale T, Buckeridge DL, Tamblyn R. Medication-related falls in the elderly: causative factors and preventive strategies. Drugs Aging. 2012;29(5):359-376. https://doi.org/10.2165/11599460-000000000-00000.
11. Evoy KE, Morrison MD, Saklad SR. Abuse and misuse of pregabalin and gabapentin. Drugs. 2017;77(4):403-426. https://doi.org/10.1007/s40265-017-0700-x.
12. Gomes T, Juurlink DN, Antoniou T, Mamdani MM, Paterson JM, van den Brink W. Gabapentin, opioids, and the risk of opioid-related death: a population-based nested case-control study. PLoS Med. 2017;14(10):e1002396. https://doi.org/10.1371/journal.pmed.1002396.
13. McDonald EG, Saleh RR, Lee TC. Ezetimibe use remains common among medical inpatients. Am J Med. 2015;128(2):193-195. https://doi.org/10.1016/j.amjmed.2014.10.016.
14. U.S. Food and Drug Administration. LYRICA - Highlights of Prescribing Information 2012. https://www.accessdata.fda.gov/drugsatfda_docs/label/2012/021446s028lbl.pdf. Accessed April 30, 2019.
15. U.S. Food and Drug Administration. NEURONTIN - Highlights of Prescribing Information 2017. https://www.accessdata.fda.gov/drugsatfda_docs/label/2017/020235s064_020882s047_021129s046lbl.pdf. Accessed April 30, 2019.
16. Gomes T, Greaves S, van den Brink W, et al. Pregabalin and the risk for opioid-related death: a nested case–control study. Ann Intern Med. 2018;169(10):732-734. https://doi.org/10.7326/M18-1136.

References

1. Johansen ME. Gabapentinoid use in the United States 2002 through 2015. JAMA Intern Med. 2018;178(2):292-294. https://doi.org/10.1001/jamainternmed.2017.7856.
2. Kwok H, Khuu W, Fernandes K, et al. Impact of unrestricted access to pregabalin on the use of opioids and other CNS-active medications: a cross-sectional time series analysis. Pain Med. 2017;18(6):1019-1026. https://doi.org/10.1093/pm/pnw351.
3. Medicines use and spending in the U.S. — a review of 2016 and outlook to 2021: IMS Institute for Healthcare Informatics; 2017. https://structurecms-staging-psyclone.netdna-ssl.com/client_assets/dwonk/media/attachments/590c/6aa0/6970/2d2d/4182/0000/590c6aa069702d2d41820000.pdf?1493985952. Accessed March 21, 2019.
4. Hamer AM, Haxby DG, McFarland BH, Ketchum K. Gabapentin use in a managed medicaid population. J Manag Care Pharm. 2002;8(4):266-271. doi: 10.18553/jmcp.2002.8.4.266.
5. Eguale T, Buckeridge DL, Verma A, et al. Association of off-label drug use and adverse drug events in an adult population. JAMA Intern Med. 2016;176(1):55-63. https://doi.org/10.1001/jamainternmed.2015.6058.
6. Shanthanna H, Gilron I, Rajarathinam M, et al. Benefits and safety of gabapentinoids in chronic low back pain: a systematic review and meta-analysis of randomized controlled trials. PLoS Med. 2017;14(8):e1002369. https://doi.org/10.1371/journal.pmed.1002369.
7. Enke O, New HA, New CH, et al. Anticonvulsants in the treatment of low back pain and lumbar radicular pain: a systematic review and meta-analysis. CMAJ. 2018;190(26):E786-E793. https://doi.org/10.1503/cmaj.171333.
8. Kane CM, Mulvey MR, Wright S, Craigs C, Wright JM, Bennett MI. Opioids combined with antidepressants or antiepileptic drugs for cancer pain: systematic review and meta-analysis. Palliat Med. 2018;32(1):276-286. https://doi.org/10.1177/0269216317711826.
9. Zaccara G, Perucca P, Gangemi PF. The adverse event profile of pregabalin across different disorders: a meta-analysis. Eur J Clin Pharmacol. 2012;68(6):903-912. https://doi.org/10.1007/s00228-012-1213-x.
10. Huang AR, Mallet L, Rochefort CM, Eguale T, Buckeridge DL, Tamblyn R. Medication-related falls in the elderly: causative factors and preventive strategies. Drugs Aging. 2012;29(5):359-376. https://doi.org/10.2165/11599460-000000000-00000.
11. Evoy KE, Morrison MD, Saklad SR. Abuse and misuse of pregabalin and gabapentin. Drugs. 2017;77(4):403-426. https://doi.org/10.1007/s40265-017-0700-x.
12. Gomes T, Juurlink DN, Antoniou T, Mamdani MM, Paterson JM, van den Brink W. Gabapentin, opioids, and the risk of opioid-related death: a population-based nested case-control study. PLoS Med. 2017;14(10):e1002396. https://doi.org/10.1371/journal.pmed.1002396.
13. McDonald EG, Saleh RR, Lee TC. Ezetimibe use remains common among medical inpatients. Am J Med. 2015;128(2):193-195. https://doi.org/10.1016/j.amjmed.2014.10.016.
14. U.S. Food and Drug Administration. LYRICA - Highlights of Prescribing Information 2012. https://www.accessdata.fda.gov/drugsatfda_docs/label/2012/021446s028lbl.pdf. Accessed April 30, 2019.
15. U.S. Food and Drug Administration. NEURONTIN - Highlights of Prescribing Information 2017. https://www.accessdata.fda.gov/drugsatfda_docs/label/2017/020235s064_020882s047_021129s046lbl.pdf. Accessed April 30, 2019.
16. Gomes T, Greaves S, van den Brink W, et al. Pregabalin and the risk for opioid-related death: a nested case–control study. Ann Intern Med. 2018;169(10):732-734. https://doi.org/10.7326/M18-1136.

Issue
Journal of Hospital Medicine 14(9)
Issue
Journal of Hospital Medicine 14(9)
Page Number
547-550. Published online first May 10, 2019
Page Number
547-550. Published online first May 10, 2019
Topics
Article Type
Sections
Article Source

© 2019 Society of Hospital Medicine

Disallow All Ads
Correspondence Location
Emily G McDonald, MD, MSc, FRCPC; E-mail: [email protected]; Telephone: 514-934-1934 ext. 36134; Twitter: @DrEmilyMcD
Content Gating
Gated (full article locked unless allowed per User)
Alternative CME
Disqus Comments
Default
Gate On Date
Mon, 06/10/2019 - 05:00
Use ProPublica
Hide sidebar & use full width
render the right sidebar.
Gating Strategy
First Peek Free
Article PDF Media
Media Files

Association of Herpes Simplex Virus Testing with Hospital Length of Stay for Infants ≤60 Days of Age Undergoing Evaluation for Meningitis

Article Type
Changed
Sun, 08/04/2019 - 22:59

Neonatal herpes simplex virus (HSV) is associated with significant morbidity and mortality,1 particularly when the diagnosis or treatment is delayed.2 Therefore, many infants aged ≤60 days being evaluated for meningitis undergo cerebrospinal fluid (CSF) HSV polymerase chain reaction (PCR) testing even though the risk of HSV infection is low [estimated at 0.4% of those undergoing evaluation for central nervous system (CNS) infection].3 A single-center study demonstrated that CSF HSV PCR testing increases the hospital length of stay (LOS) for infants aged ≤56 days,4 although these single-center findings may not be generalizable. To this end, we measured the association between CSF HSV PCR testing and LOS in a multicenter cohort of hospitalized young infants.

METHODS

Study Design

We conducted a planned secondary analysis of a retrospective cohort of infants aged ≤60 days who presented to the emergency department (ED) between January 1, 2005 and December 31, 2013, enrolled in the Pediatric Emergency Medicine Collaborative Research Committee (PEM CRC) HSV study.3 Our study was limited to the 20 hospitals that contributed hospital LOS data. The study protocol was approved by each site’s institutional review board with permission for data sharing.

Study Population

Eligible infants were identified at each site using a site-specific electronic search strategy. Infants were eligible for inclusion if a CSF culture was obtained in the ED or within 24 hours of ED arrival. We excluded infants who were discharged from the ED and those with missing hospital LOS data.

 

 

Data Collection

Site investigators extracted the following data elements either electronically or from medical records: patient demographics; ED arrival date and time; hospital discharge date and time; urinalysis results; peripheral and CSF cell counts; blood, urine, and CSF bacterial culture results; as well as the results of HSV PCR and viral cultures. Infants with growth of a pathogen in blood or CSF, or a catheterized urine culture with ≥50,000 colony-forming units (CFUs)/mL of a single pathogenic bacteria, or 10,000-50,000 CFUs/mL of a single pathogenic bacteria with an abnormal urinalysis (ie, positive nitrite or leukocyte esterase on urine dipstick or >5 white blood cells [WBCs] per high power field on urine microscopy) were classified as having a serious bacterial infection (SBI).5,6 Infants with a positive HSV PCR or viral culture from any site were classified as having HSV infection.3 Hospitalized infants who did not have an HSV PCR test performed were assumed not to have HSV disease if not diagnosed during the hospital stay or repeat ED encounter.3

Outcome Measures

The primary outcome was hospital LOS, defined at all hospitals as the time from ED arrival to provider signature of the hospital discharge order, calculated in minutes and then converted into days.

Statistical Analysis

We described LOS using medians with interquartile ranges (IQR) and compared between infants with and without a CSF HSV PCR test performed using the Mann–Whitney U test. To evaluate the association between performance of CSF HSV PCR testing and hospital LOS, we used negative binomial regression given the count variable outcome (LOS) with an overdispersed distribution. For this analysis, we clustered by hospital after adjusting for the following factors determined a priori: age, gender, study year, and presence of serious bacterial or HSV infection. Using the relative marginal modeled estimates of LOS (tested vs not tested), we determined the percentage increase in LOS. We then repeated the analyses after stratifying by the location of testing (ie, in-house vs send-out), age (≤28 days vs 29-60 days), and presence or absence of CSF pleocytosis (defined as a CSF WBC of ≥16 cells/mm3for infants aged ≤28 days and ≥10 cells/mm3for infants aged 29-60 days),7 because infants aged 29-60 days and those without CSF pleocytosis are reported to be at very low risk for CNS HSV infection.3,8 We utilized Stata Data Analysis and Statistical Software, version 15.0 (StataCorp, Inc.; College Station, Texas) for statistical analyses.

RESULTS

Of 24,103 infants with CSF cultures obtained at the 20 participating sites, we excluded 2,673 (11.1%) discharged from the ED or with missing disposition and 934 (3.9%) with missing LOS, leaving a study cohort of 20,496 infants (Figure). Overall, 1,780 infants (8.7%) had an SBI and 99 (0.5%) had an HSV infection, of which 46 (46.5%) had a CNS HSV infection.

Among the 20,496 study infants, 7,399 (36.1%) had a CSF HSV PCR test performed; 5,935 infants (80.2% of those tested) had in-house and 1,464 (19.8%) had send-out testing. Among infants with available CSF cell counts, a CSF HSV PCR test was more commonly performed in infants with CSF pleocytosis than in those without (1,865/4,439 [42.0%] with CSF pleocytosis vs 3,705/12,002 [30.9%] without CSF pleocytosis; odds ratio [OR] 1.6, 95% CI 1.5-1.7). Of the 7,399 infants who had a CSF HSV PCR test performed, 46 (0.6%) had a positive test. Of the tested infants, 5,570 (75.3%) had an available CSF WBC count; a positive CSF HSV PCR test was more common in infants with CSF pleocytosis than in those without (25 positive tests/1,865 infants with CSF pleocytosis [1.3%] vs 9/3,705 [0.2%] without CSF pleocytosis; OR 5.6, 95% CI 2.6-12.0). Among the 5,308 infants aged 29-60 days without CSF pleocytosis, 1,110 (20.9%) had a CSF HSV PCR test performed and only one infant (0.09% of those tested) had a positive test.

Without adjustment, infants with a CSF HSV PCR test had a longer median LOS than infants who were not tested (2.5 vs 2.3 days; P < .001). After adjustment, infants with a CSF HSV PCR test performed had a 23% longer duration of hospitalization. The association between testing and LOS was similar for older vs younger infants, infants with and without CSF pleocytosis, and in-house vs send-out testing (Table).

 

 

DISCUSSION

In a large, multicenter cohort of more than 20,000 hospitalized infants aged ≤60 days undergoing evaluation for meningitis, we examined the association of CSF HSV PCR testing with hospital LOS. Approximately one-third of study infants had a CSF HSV PCR test obtained. After adjustment for patient- and hospital-level factors, the treating clinician’s decision to obtain a CSF HSV PCR test was associated with a 23% longer hospital LOS (nearly one-half day).

Our findings are consistent with those of previous studies. First, our observed association of the decision to obtain a CSF HSV PCR test and LOS was similar in magnitude to that of a previous single-center investigation.4 Second, we also found that older infants and those without CSF pleocytosis were at very low risk of HSV infection.3,8 For the otherwise low-risk infants, the longer LOS may be due to delays in obtaining CSF HSV PCR test results, which should be explored in future research. Our study has greater generalizability than previous single-center studies by substantially increasing the population size as well as the variety of clinical settings. Ensuring clinicians’ access to rapid HSV PCR testing platforms will further mitigate the impact of HSV testing on LOS.

When deciding to perform a CSF HSV PCR test for infants aged ≤60 days, clinicians must balance the low incidence of neonatal HSV3 with the risk of delayed diagnosis and treatment of HSV infection, which include neurologic sequelae or even death.1,2 As infants with CNS HSV infection commonly present nonspecifically and only a minority of infected infants have skin vesicles,1 controversy exists as to which infants should be evaluated for HSV infection, resulting in considerable variability in HSV testing.3 Some clinicians advocate for more conservative testing strategies that include the performance of CSF HSV PCR testing in all febrile infants aged ≤21 days.9 Others suggest limiting testing to infants who meet high-risk criteria (eg, seizures, ill-appearance, or CSF pleocytosis).10,11 Further investigation will need to elucidate the clinical and laboratory predictors of HSV infection to identify those infants who would benefit most from HSV testing as well as the outcomes of infants not tested.

Our study has several limitations. First, we could not determine the reason why clinicians elected to obtain a CSF HSV PCR test, and we do not know the test turnaround time or the time when results became available to the clinical team. Second, we did not abstract clinical data such as ill-appearance or seizures. Although we adjusted for the presence of serious bacterial or HSV infection as proxy measures for illness severity, it is possible that other clinical factors were associated with HSV testing and LOS. Third, although we adjusted for patient- and hospital-level factors in our regression model, the potential for residual confounding persists. Fourth, we did not explore acyclovir administration as a factor associated with LOS as some sites did not provide data on acyclovir. Fifth, we did not evaluate the impact of HSV testing of other sample types (eg, blood or skin) on LOS. Sixth, our study was conducted primarily at children’s hospitals, and our findings may not be generalizable to general hospitals with hospitalized neonates.

 

 

CONCLUSIONS

For infants aged ≤60 days undergoing evaluation for meningitis, CSF HSV PCR testing was associated with a slightly longer hospital LOS. Improved methods to identify and target testing to higher risk infants may mitigate the impact on LOS for low-risk infants.

Acknowledgments

The authors acknowledge the following collaborators in the Pediatric Emergency Medicine Clinical Research Network (PEM CRC) Herpes Simplex Virus (HSV) Study Group who collected data for this study and/or the parent study: Joseph L Arms, MD (Minneapolis, Minnesota), Stuart A Bradin, DO (Ann Arbor, Michigan), Sarah J Curtis, MD, MSc (Edmonton, Alberta, Canada), Paul T Ishimine, MD (San Diego, California), Dina Kulik, MD (Toronto, Ontario, Canada), Prashant Mahajan, MD, MPH, MBA (Ann Arbor, Michigan), Aaron S Miller, MD, MSPH (St. Louis, Missouri), Pamela J Okada, MD (Dallas, Texas), Christopher M Pruitt, MD (Birmingham, Alabama), Suzanne M Schmidt, MD (Chicago, Illinois), David Schnadower, Amy D Thompson, MD (Wilmington, Delaware), Joanna E Thomson, MD, MPH (Cincinnati, Ohio), MD, MPH (St. Louis, Missouri), and Neil G. Uspal, MD (Seattle, Washington).

Disclosures

Dr. Aronson reports grants from the Agency for Healthcare Research and Quality during the conduct of the study. Dr. Shah reports grants from Patient-Centered Outcomes Research Institute, grants from the National Institute of Allergy and Infectious Diseases, and grants from the National Heart Lung Blood Institute, outside the submitted work. Dr. Shah is the Editor-in-Chief of the Journal of Hospital Medicine. All other authors have no conflicts of interest or financial relationships relevant to this article to disclose.

Funding

This project was supported by the Section of Emergency Medicine of the American Academy of Pediatrics (AAP) and Baylor College of Medicine and by the grant number K08HS026006 (Aronson) from the Agency for Healthcare Research and Quality. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Agency for Healthcare Research and Quality. Stephen Freedman is supported by the Alberta Children’s Hospital Foundation Professorship in Child Health and Wellness.

 

References

1. Kimberlin DW, Lin CY, Jacobs RF, et al. Natural history of neonatal herpes simplex virus infections in the acyclovir era. Pediatrics. 2001;108(2):223-229. PubMed
2. Shah SS, Aronson PL, Mohamad Z, Lorch SA. Delayed acyclovir therapy and death among neonates with herpes simplex virus infection. Pediatrics. 2011;128(6):1153-1160. https://doi.org/10.1136/eb-2012-100674.
3. Cruz AT, Freedman SB, Kulik DM, et al. Herpes simplex virus infection in infants undergoing meningitis evaluation. Pediatrics. 2018;141(2):e20171688. https://doi.org/10.1542/peds.2017-1688.
4. Shah SS, Volk J, Mohamad Z, Hodinka RL, Zorc JJ. Herpes simplex virus testing and hospital length of stay in neonates and young infants. J Pediatr. 2010;156(5):738-743. https://doi.org/10.1016/j.jpeds.2009.11.079.
5. Mahajan P, Kuppermann N, Mejias A, et al. Association of RNA biosignatures with bacterial infections in febrile infants aged 60 days or younger. JAMA. 2016;316(8):846-857. https://doi.org/10.1001/jama.2016.9207.
6. Schnadower D, Kuppermann N, Macias CG, et al. Febrile infants with urinary tract infections at very low risk for adverse events and bacteremia. Pediatrics. 2010;126(6):1074-1083. https://doi.org/10.1542/peds.2010-0479.
7. Thomson J, Sucharew H, Cruz AT, et al. Cerebrospinal fluid reference values for young infants undergoing lumbar puncture. Pediatrics. 2018;141(3):e20173405. https://doi.org/10.1542/peds.2017-3405.
8. Caviness AC, Demmler GJ, Almendarez Y, Selwyn BJ. The prevalence of neonatal herpes simplex virus infection compared with serious bacterial illness in hospitalized neonates. J Pediatr. 2008;153(2):164-169. https://doi.org/10.1016/j.jpeds.2008.02.031.
9. Long SS. In defense of empiric acyclovir therapy in certain neonates. J Pediatr. 2008;153(2):157-158. https://doi.org/10.1016/j.jpeds.2008.04.071.
10. Brower L, Schondelmeyer A, Wilson P, Shah SS. Testing and empiric treatment for neonatal herpes simplex virus: challenges and opportunities for improving the value of care. Hosp Pediatr. 2016;6(2):108-111. https://doi.org/10.1542/hpeds.2015-0166.
11. Kimberlin DW. When should you initiate acyclovir therapy in a neonate? J Pediatr. 2008;153(2):155-156. https://doi.org/10.1016/j.jpeds.2008.04.027.

Article PDF
Issue
Journal of Hospital Medicine 14(8)
Topics
Page Number
492-495
Sections
Article PDF
Article PDF

Neonatal herpes simplex virus (HSV) is associated with significant morbidity and mortality,1 particularly when the diagnosis or treatment is delayed.2 Therefore, many infants aged ≤60 days being evaluated for meningitis undergo cerebrospinal fluid (CSF) HSV polymerase chain reaction (PCR) testing even though the risk of HSV infection is low [estimated at 0.4% of those undergoing evaluation for central nervous system (CNS) infection].3 A single-center study demonstrated that CSF HSV PCR testing increases the hospital length of stay (LOS) for infants aged ≤56 days,4 although these single-center findings may not be generalizable. To this end, we measured the association between CSF HSV PCR testing and LOS in a multicenter cohort of hospitalized young infants.

METHODS

Study Design

We conducted a planned secondary analysis of a retrospective cohort of infants aged ≤60 days who presented to the emergency department (ED) between January 1, 2005 and December 31, 2013, enrolled in the Pediatric Emergency Medicine Collaborative Research Committee (PEM CRC) HSV study.3 Our study was limited to the 20 hospitals that contributed hospital LOS data. The study protocol was approved by each site’s institutional review board with permission for data sharing.

Study Population

Eligible infants were identified at each site using a site-specific electronic search strategy. Infants were eligible for inclusion if a CSF culture was obtained in the ED or within 24 hours of ED arrival. We excluded infants who were discharged from the ED and those with missing hospital LOS data.

 

 

Data Collection

Site investigators extracted the following data elements either electronically or from medical records: patient demographics; ED arrival date and time; hospital discharge date and time; urinalysis results; peripheral and CSF cell counts; blood, urine, and CSF bacterial culture results; as well as the results of HSV PCR and viral cultures. Infants with growth of a pathogen in blood or CSF, or a catheterized urine culture with ≥50,000 colony-forming units (CFUs)/mL of a single pathogenic bacteria, or 10,000-50,000 CFUs/mL of a single pathogenic bacteria with an abnormal urinalysis (ie, positive nitrite or leukocyte esterase on urine dipstick or >5 white blood cells [WBCs] per high power field on urine microscopy) were classified as having a serious bacterial infection (SBI).5,6 Infants with a positive HSV PCR or viral culture from any site were classified as having HSV infection.3 Hospitalized infants who did not have an HSV PCR test performed were assumed not to have HSV disease if not diagnosed during the hospital stay or repeat ED encounter.3

Outcome Measures

The primary outcome was hospital LOS, defined at all hospitals as the time from ED arrival to provider signature of the hospital discharge order, calculated in minutes and then converted into days.

Statistical Analysis

We described LOS using medians with interquartile ranges (IQR) and compared between infants with and without a CSF HSV PCR test performed using the Mann–Whitney U test. To evaluate the association between performance of CSF HSV PCR testing and hospital LOS, we used negative binomial regression given the count variable outcome (LOS) with an overdispersed distribution. For this analysis, we clustered by hospital after adjusting for the following factors determined a priori: age, gender, study year, and presence of serious bacterial or HSV infection. Using the relative marginal modeled estimates of LOS (tested vs not tested), we determined the percentage increase in LOS. We then repeated the analyses after stratifying by the location of testing (ie, in-house vs send-out), age (≤28 days vs 29-60 days), and presence or absence of CSF pleocytosis (defined as a CSF WBC of ≥16 cells/mm3for infants aged ≤28 days and ≥10 cells/mm3for infants aged 29-60 days),7 because infants aged 29-60 days and those without CSF pleocytosis are reported to be at very low risk for CNS HSV infection.3,8 We utilized Stata Data Analysis and Statistical Software, version 15.0 (StataCorp, Inc.; College Station, Texas) for statistical analyses.

RESULTS

Of 24,103 infants with CSF cultures obtained at the 20 participating sites, we excluded 2,673 (11.1%) discharged from the ED or with missing disposition and 934 (3.9%) with missing LOS, leaving a study cohort of 20,496 infants (Figure). Overall, 1,780 infants (8.7%) had an SBI and 99 (0.5%) had an HSV infection, of which 46 (46.5%) had a CNS HSV infection.

Among the 20,496 study infants, 7,399 (36.1%) had a CSF HSV PCR test performed; 5,935 infants (80.2% of those tested) had in-house and 1,464 (19.8%) had send-out testing. Among infants with available CSF cell counts, a CSF HSV PCR test was more commonly performed in infants with CSF pleocytosis than in those without (1,865/4,439 [42.0%] with CSF pleocytosis vs 3,705/12,002 [30.9%] without CSF pleocytosis; odds ratio [OR] 1.6, 95% CI 1.5-1.7). Of the 7,399 infants who had a CSF HSV PCR test performed, 46 (0.6%) had a positive test. Of the tested infants, 5,570 (75.3%) had an available CSF WBC count; a positive CSF HSV PCR test was more common in infants with CSF pleocytosis than in those without (25 positive tests/1,865 infants with CSF pleocytosis [1.3%] vs 9/3,705 [0.2%] without CSF pleocytosis; OR 5.6, 95% CI 2.6-12.0). Among the 5,308 infants aged 29-60 days without CSF pleocytosis, 1,110 (20.9%) had a CSF HSV PCR test performed and only one infant (0.09% of those tested) had a positive test.

Without adjustment, infants with a CSF HSV PCR test had a longer median LOS than infants who were not tested (2.5 vs 2.3 days; P < .001). After adjustment, infants with a CSF HSV PCR test performed had a 23% longer duration of hospitalization. The association between testing and LOS was similar for older vs younger infants, infants with and without CSF pleocytosis, and in-house vs send-out testing (Table).

 

 

DISCUSSION

In a large, multicenter cohort of more than 20,000 hospitalized infants aged ≤60 days undergoing evaluation for meningitis, we examined the association of CSF HSV PCR testing with hospital LOS. Approximately one-third of study infants had a CSF HSV PCR test obtained. After adjustment for patient- and hospital-level factors, the treating clinician’s decision to obtain a CSF HSV PCR test was associated with a 23% longer hospital LOS (nearly one-half day).

Our findings are consistent with those of previous studies. First, our observed association of the decision to obtain a CSF HSV PCR test and LOS was similar in magnitude to that of a previous single-center investigation.4 Second, we also found that older infants and those without CSF pleocytosis were at very low risk of HSV infection.3,8 For the otherwise low-risk infants, the longer LOS may be due to delays in obtaining CSF HSV PCR test results, which should be explored in future research. Our study has greater generalizability than previous single-center studies by substantially increasing the population size as well as the variety of clinical settings. Ensuring clinicians’ access to rapid HSV PCR testing platforms will further mitigate the impact of HSV testing on LOS.

When deciding to perform a CSF HSV PCR test for infants aged ≤60 days, clinicians must balance the low incidence of neonatal HSV3 with the risk of delayed diagnosis and treatment of HSV infection, which include neurologic sequelae or even death.1,2 As infants with CNS HSV infection commonly present nonspecifically and only a minority of infected infants have skin vesicles,1 controversy exists as to which infants should be evaluated for HSV infection, resulting in considerable variability in HSV testing.3 Some clinicians advocate for more conservative testing strategies that include the performance of CSF HSV PCR testing in all febrile infants aged ≤21 days.9 Others suggest limiting testing to infants who meet high-risk criteria (eg, seizures, ill-appearance, or CSF pleocytosis).10,11 Further investigation will need to elucidate the clinical and laboratory predictors of HSV infection to identify those infants who would benefit most from HSV testing as well as the outcomes of infants not tested.

Our study has several limitations. First, we could not determine the reason why clinicians elected to obtain a CSF HSV PCR test, and we do not know the test turnaround time or the time when results became available to the clinical team. Second, we did not abstract clinical data such as ill-appearance or seizures. Although we adjusted for the presence of serious bacterial or HSV infection as proxy measures for illness severity, it is possible that other clinical factors were associated with HSV testing and LOS. Third, although we adjusted for patient- and hospital-level factors in our regression model, the potential for residual confounding persists. Fourth, we did not explore acyclovir administration as a factor associated with LOS as some sites did not provide data on acyclovir. Fifth, we did not evaluate the impact of HSV testing of other sample types (eg, blood or skin) on LOS. Sixth, our study was conducted primarily at children’s hospitals, and our findings may not be generalizable to general hospitals with hospitalized neonates.

 

 

CONCLUSIONS

For infants aged ≤60 days undergoing evaluation for meningitis, CSF HSV PCR testing was associated with a slightly longer hospital LOS. Improved methods to identify and target testing to higher risk infants may mitigate the impact on LOS for low-risk infants.

Acknowledgments

The authors acknowledge the following collaborators in the Pediatric Emergency Medicine Clinical Research Network (PEM CRC) Herpes Simplex Virus (HSV) Study Group who collected data for this study and/or the parent study: Joseph L Arms, MD (Minneapolis, Minnesota), Stuart A Bradin, DO (Ann Arbor, Michigan), Sarah J Curtis, MD, MSc (Edmonton, Alberta, Canada), Paul T Ishimine, MD (San Diego, California), Dina Kulik, MD (Toronto, Ontario, Canada), Prashant Mahajan, MD, MPH, MBA (Ann Arbor, Michigan), Aaron S Miller, MD, MSPH (St. Louis, Missouri), Pamela J Okada, MD (Dallas, Texas), Christopher M Pruitt, MD (Birmingham, Alabama), Suzanne M Schmidt, MD (Chicago, Illinois), David Schnadower, Amy D Thompson, MD (Wilmington, Delaware), Joanna E Thomson, MD, MPH (Cincinnati, Ohio), MD, MPH (St. Louis, Missouri), and Neil G. Uspal, MD (Seattle, Washington).

Disclosures

Dr. Aronson reports grants from the Agency for Healthcare Research and Quality during the conduct of the study. Dr. Shah reports grants from Patient-Centered Outcomes Research Institute, grants from the National Institute of Allergy and Infectious Diseases, and grants from the National Heart Lung Blood Institute, outside the submitted work. Dr. Shah is the Editor-in-Chief of the Journal of Hospital Medicine. All other authors have no conflicts of interest or financial relationships relevant to this article to disclose.

Funding

This project was supported by the Section of Emergency Medicine of the American Academy of Pediatrics (AAP) and Baylor College of Medicine and by the grant number K08HS026006 (Aronson) from the Agency for Healthcare Research and Quality. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Agency for Healthcare Research and Quality. Stephen Freedman is supported by the Alberta Children’s Hospital Foundation Professorship in Child Health and Wellness.

 

Neonatal herpes simplex virus (HSV) is associated with significant morbidity and mortality,1 particularly when the diagnosis or treatment is delayed.2 Therefore, many infants aged ≤60 days being evaluated for meningitis undergo cerebrospinal fluid (CSF) HSV polymerase chain reaction (PCR) testing even though the risk of HSV infection is low [estimated at 0.4% of those undergoing evaluation for central nervous system (CNS) infection].3 A single-center study demonstrated that CSF HSV PCR testing increases the hospital length of stay (LOS) for infants aged ≤56 days,4 although these single-center findings may not be generalizable. To this end, we measured the association between CSF HSV PCR testing and LOS in a multicenter cohort of hospitalized young infants.

METHODS

Study Design

We conducted a planned secondary analysis of a retrospective cohort of infants aged ≤60 days who presented to the emergency department (ED) between January 1, 2005 and December 31, 2013, enrolled in the Pediatric Emergency Medicine Collaborative Research Committee (PEM CRC) HSV study.3 Our study was limited to the 20 hospitals that contributed hospital LOS data. The study protocol was approved by each site’s institutional review board with permission for data sharing.

Study Population

Eligible infants were identified at each site using a site-specific electronic search strategy. Infants were eligible for inclusion if a CSF culture was obtained in the ED or within 24 hours of ED arrival. We excluded infants who were discharged from the ED and those with missing hospital LOS data.

 

 

Data Collection

Site investigators extracted the following data elements either electronically or from medical records: patient demographics; ED arrival date and time; hospital discharge date and time; urinalysis results; peripheral and CSF cell counts; blood, urine, and CSF bacterial culture results; as well as the results of HSV PCR and viral cultures. Infants with growth of a pathogen in blood or CSF, or a catheterized urine culture with ≥50,000 colony-forming units (CFUs)/mL of a single pathogenic bacteria, or 10,000-50,000 CFUs/mL of a single pathogenic bacteria with an abnormal urinalysis (ie, positive nitrite or leukocyte esterase on urine dipstick or >5 white blood cells [WBCs] per high power field on urine microscopy) were classified as having a serious bacterial infection (SBI).5,6 Infants with a positive HSV PCR or viral culture from any site were classified as having HSV infection.3 Hospitalized infants who did not have an HSV PCR test performed were assumed not to have HSV disease if not diagnosed during the hospital stay or repeat ED encounter.3

Outcome Measures

The primary outcome was hospital LOS, defined at all hospitals as the time from ED arrival to provider signature of the hospital discharge order, calculated in minutes and then converted into days.

Statistical Analysis

We described LOS using medians with interquartile ranges (IQR) and compared between infants with and without a CSF HSV PCR test performed using the Mann–Whitney U test. To evaluate the association between performance of CSF HSV PCR testing and hospital LOS, we used negative binomial regression given the count variable outcome (LOS) with an overdispersed distribution. For this analysis, we clustered by hospital after adjusting for the following factors determined a priori: age, gender, study year, and presence of serious bacterial or HSV infection. Using the relative marginal modeled estimates of LOS (tested vs not tested), we determined the percentage increase in LOS. We then repeated the analyses after stratifying by the location of testing (ie, in-house vs send-out), age (≤28 days vs 29-60 days), and presence or absence of CSF pleocytosis (defined as a CSF WBC of ≥16 cells/mm3for infants aged ≤28 days and ≥10 cells/mm3for infants aged 29-60 days),7 because infants aged 29-60 days and those without CSF pleocytosis are reported to be at very low risk for CNS HSV infection.3,8 We utilized Stata Data Analysis and Statistical Software, version 15.0 (StataCorp, Inc.; College Station, Texas) for statistical analyses.

RESULTS

Of 24,103 infants with CSF cultures obtained at the 20 participating sites, we excluded 2,673 (11.1%) discharged from the ED or with missing disposition and 934 (3.9%) with missing LOS, leaving a study cohort of 20,496 infants (Figure). Overall, 1,780 infants (8.7%) had an SBI and 99 (0.5%) had an HSV infection, of which 46 (46.5%) had a CNS HSV infection.

Among the 20,496 study infants, 7,399 (36.1%) had a CSF HSV PCR test performed; 5,935 infants (80.2% of those tested) had in-house and 1,464 (19.8%) had send-out testing. Among infants with available CSF cell counts, a CSF HSV PCR test was more commonly performed in infants with CSF pleocytosis than in those without (1,865/4,439 [42.0%] with CSF pleocytosis vs 3,705/12,002 [30.9%] without CSF pleocytosis; odds ratio [OR] 1.6, 95% CI 1.5-1.7). Of the 7,399 infants who had a CSF HSV PCR test performed, 46 (0.6%) had a positive test. Of the tested infants, 5,570 (75.3%) had an available CSF WBC count; a positive CSF HSV PCR test was more common in infants with CSF pleocytosis than in those without (25 positive tests/1,865 infants with CSF pleocytosis [1.3%] vs 9/3,705 [0.2%] without CSF pleocytosis; OR 5.6, 95% CI 2.6-12.0). Among the 5,308 infants aged 29-60 days without CSF pleocytosis, 1,110 (20.9%) had a CSF HSV PCR test performed and only one infant (0.09% of those tested) had a positive test.

Without adjustment, infants with a CSF HSV PCR test had a longer median LOS than infants who were not tested (2.5 vs 2.3 days; P < .001). After adjustment, infants with a CSF HSV PCR test performed had a 23% longer duration of hospitalization. The association between testing and LOS was similar for older vs younger infants, infants with and without CSF pleocytosis, and in-house vs send-out testing (Table).

 

 

DISCUSSION

In a large, multicenter cohort of more than 20,000 hospitalized infants aged ≤60 days undergoing evaluation for meningitis, we examined the association of CSF HSV PCR testing with hospital LOS. Approximately one-third of study infants had a CSF HSV PCR test obtained. After adjustment for patient- and hospital-level factors, the treating clinician’s decision to obtain a CSF HSV PCR test was associated with a 23% longer hospital LOS (nearly one-half day).

Our findings are consistent with those of previous studies. First, our observed association of the decision to obtain a CSF HSV PCR test and LOS was similar in magnitude to that of a previous single-center investigation.4 Second, we also found that older infants and those without CSF pleocytosis were at very low risk of HSV infection.3,8 For the otherwise low-risk infants, the longer LOS may be due to delays in obtaining CSF HSV PCR test results, which should be explored in future research. Our study has greater generalizability than previous single-center studies by substantially increasing the population size as well as the variety of clinical settings. Ensuring clinicians’ access to rapid HSV PCR testing platforms will further mitigate the impact of HSV testing on LOS.

When deciding to perform a CSF HSV PCR test for infants aged ≤60 days, clinicians must balance the low incidence of neonatal HSV3 with the risk of delayed diagnosis and treatment of HSV infection, which include neurologic sequelae or even death.1,2 As infants with CNS HSV infection commonly present nonspecifically and only a minority of infected infants have skin vesicles,1 controversy exists as to which infants should be evaluated for HSV infection, resulting in considerable variability in HSV testing.3 Some clinicians advocate for more conservative testing strategies that include the performance of CSF HSV PCR testing in all febrile infants aged ≤21 days.9 Others suggest limiting testing to infants who meet high-risk criteria (eg, seizures, ill-appearance, or CSF pleocytosis).10,11 Further investigation will need to elucidate the clinical and laboratory predictors of HSV infection to identify those infants who would benefit most from HSV testing as well as the outcomes of infants not tested.

Our study has several limitations. First, we could not determine the reason why clinicians elected to obtain a CSF HSV PCR test, and we do not know the test turnaround time or the time when results became available to the clinical team. Second, we did not abstract clinical data such as ill-appearance or seizures. Although we adjusted for the presence of serious bacterial or HSV infection as proxy measures for illness severity, it is possible that other clinical factors were associated with HSV testing and LOS. Third, although we adjusted for patient- and hospital-level factors in our regression model, the potential for residual confounding persists. Fourth, we did not explore acyclovir administration as a factor associated with LOS as some sites did not provide data on acyclovir. Fifth, we did not evaluate the impact of HSV testing of other sample types (eg, blood or skin) on LOS. Sixth, our study was conducted primarily at children’s hospitals, and our findings may not be generalizable to general hospitals with hospitalized neonates.

 

 

CONCLUSIONS

For infants aged ≤60 days undergoing evaluation for meningitis, CSF HSV PCR testing was associated with a slightly longer hospital LOS. Improved methods to identify and target testing to higher risk infants may mitigate the impact on LOS for low-risk infants.

Acknowledgments

The authors acknowledge the following collaborators in the Pediatric Emergency Medicine Clinical Research Network (PEM CRC) Herpes Simplex Virus (HSV) Study Group who collected data for this study and/or the parent study: Joseph L Arms, MD (Minneapolis, Minnesota), Stuart A Bradin, DO (Ann Arbor, Michigan), Sarah J Curtis, MD, MSc (Edmonton, Alberta, Canada), Paul T Ishimine, MD (San Diego, California), Dina Kulik, MD (Toronto, Ontario, Canada), Prashant Mahajan, MD, MPH, MBA (Ann Arbor, Michigan), Aaron S Miller, MD, MSPH (St. Louis, Missouri), Pamela J Okada, MD (Dallas, Texas), Christopher M Pruitt, MD (Birmingham, Alabama), Suzanne M Schmidt, MD (Chicago, Illinois), David Schnadower, Amy D Thompson, MD (Wilmington, Delaware), Joanna E Thomson, MD, MPH (Cincinnati, Ohio), MD, MPH (St. Louis, Missouri), and Neil G. Uspal, MD (Seattle, Washington).

Disclosures

Dr. Aronson reports grants from the Agency for Healthcare Research and Quality during the conduct of the study. Dr. Shah reports grants from Patient-Centered Outcomes Research Institute, grants from the National Institute of Allergy and Infectious Diseases, and grants from the National Heart Lung Blood Institute, outside the submitted work. Dr. Shah is the Editor-in-Chief of the Journal of Hospital Medicine. All other authors have no conflicts of interest or financial relationships relevant to this article to disclose.

Funding

This project was supported by the Section of Emergency Medicine of the American Academy of Pediatrics (AAP) and Baylor College of Medicine and by the grant number K08HS026006 (Aronson) from the Agency for Healthcare Research and Quality. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Agency for Healthcare Research and Quality. Stephen Freedman is supported by the Alberta Children’s Hospital Foundation Professorship in Child Health and Wellness.

 

References

1. Kimberlin DW, Lin CY, Jacobs RF, et al. Natural history of neonatal herpes simplex virus infections in the acyclovir era. Pediatrics. 2001;108(2):223-229. PubMed
2. Shah SS, Aronson PL, Mohamad Z, Lorch SA. Delayed acyclovir therapy and death among neonates with herpes simplex virus infection. Pediatrics. 2011;128(6):1153-1160. https://doi.org/10.1136/eb-2012-100674.
3. Cruz AT, Freedman SB, Kulik DM, et al. Herpes simplex virus infection in infants undergoing meningitis evaluation. Pediatrics. 2018;141(2):e20171688. https://doi.org/10.1542/peds.2017-1688.
4. Shah SS, Volk J, Mohamad Z, Hodinka RL, Zorc JJ. Herpes simplex virus testing and hospital length of stay in neonates and young infants. J Pediatr. 2010;156(5):738-743. https://doi.org/10.1016/j.jpeds.2009.11.079.
5. Mahajan P, Kuppermann N, Mejias A, et al. Association of RNA biosignatures with bacterial infections in febrile infants aged 60 days or younger. JAMA. 2016;316(8):846-857. https://doi.org/10.1001/jama.2016.9207.
6. Schnadower D, Kuppermann N, Macias CG, et al. Febrile infants with urinary tract infections at very low risk for adverse events and bacteremia. Pediatrics. 2010;126(6):1074-1083. https://doi.org/10.1542/peds.2010-0479.
7. Thomson J, Sucharew H, Cruz AT, et al. Cerebrospinal fluid reference values for young infants undergoing lumbar puncture. Pediatrics. 2018;141(3):e20173405. https://doi.org/10.1542/peds.2017-3405.
8. Caviness AC, Demmler GJ, Almendarez Y, Selwyn BJ. The prevalence of neonatal herpes simplex virus infection compared with serious bacterial illness in hospitalized neonates. J Pediatr. 2008;153(2):164-169. https://doi.org/10.1016/j.jpeds.2008.02.031.
9. Long SS. In defense of empiric acyclovir therapy in certain neonates. J Pediatr. 2008;153(2):157-158. https://doi.org/10.1016/j.jpeds.2008.04.071.
10. Brower L, Schondelmeyer A, Wilson P, Shah SS. Testing and empiric treatment for neonatal herpes simplex virus: challenges and opportunities for improving the value of care. Hosp Pediatr. 2016;6(2):108-111. https://doi.org/10.1542/hpeds.2015-0166.
11. Kimberlin DW. When should you initiate acyclovir therapy in a neonate? J Pediatr. 2008;153(2):155-156. https://doi.org/10.1016/j.jpeds.2008.04.027.

References

1. Kimberlin DW, Lin CY, Jacobs RF, et al. Natural history of neonatal herpes simplex virus infections in the acyclovir era. Pediatrics. 2001;108(2):223-229. PubMed
2. Shah SS, Aronson PL, Mohamad Z, Lorch SA. Delayed acyclovir therapy and death among neonates with herpes simplex virus infection. Pediatrics. 2011;128(6):1153-1160. https://doi.org/10.1136/eb-2012-100674.
3. Cruz AT, Freedman SB, Kulik DM, et al. Herpes simplex virus infection in infants undergoing meningitis evaluation. Pediatrics. 2018;141(2):e20171688. https://doi.org/10.1542/peds.2017-1688.
4. Shah SS, Volk J, Mohamad Z, Hodinka RL, Zorc JJ. Herpes simplex virus testing and hospital length of stay in neonates and young infants. J Pediatr. 2010;156(5):738-743. https://doi.org/10.1016/j.jpeds.2009.11.079.
5. Mahajan P, Kuppermann N, Mejias A, et al. Association of RNA biosignatures with bacterial infections in febrile infants aged 60 days or younger. JAMA. 2016;316(8):846-857. https://doi.org/10.1001/jama.2016.9207.
6. Schnadower D, Kuppermann N, Macias CG, et al. Febrile infants with urinary tract infections at very low risk for adverse events and bacteremia. Pediatrics. 2010;126(6):1074-1083. https://doi.org/10.1542/peds.2010-0479.
7. Thomson J, Sucharew H, Cruz AT, et al. Cerebrospinal fluid reference values for young infants undergoing lumbar puncture. Pediatrics. 2018;141(3):e20173405. https://doi.org/10.1542/peds.2017-3405.
8. Caviness AC, Demmler GJ, Almendarez Y, Selwyn BJ. The prevalence of neonatal herpes simplex virus infection compared with serious bacterial illness in hospitalized neonates. J Pediatr. 2008;153(2):164-169. https://doi.org/10.1016/j.jpeds.2008.02.031.
9. Long SS. In defense of empiric acyclovir therapy in certain neonates. J Pediatr. 2008;153(2):157-158. https://doi.org/10.1016/j.jpeds.2008.04.071.
10. Brower L, Schondelmeyer A, Wilson P, Shah SS. Testing and empiric treatment for neonatal herpes simplex virus: challenges and opportunities for improving the value of care. Hosp Pediatr. 2016;6(2):108-111. https://doi.org/10.1542/hpeds.2015-0166.
11. Kimberlin DW. When should you initiate acyclovir therapy in a neonate? J Pediatr. 2008;153(2):155-156. https://doi.org/10.1016/j.jpeds.2008.04.027.

Issue
Journal of Hospital Medicine 14(8)
Issue
Journal of Hospital Medicine 14(8)
Page Number
492-495
Page Number
492-495
Topics
Article Type
Sections
Article Source

© 2019 Society of Hospital Medicine

Disallow All Ads
Correspondence Location
Paul L Aronson, MD, MHS; E-mail: [email protected]; Telephone: 203-785-3849.
Content Gating
Gated (full article locked unless allowed per User)
Alternative CME
Disqus Comments
Default
Un-Gate On Date
Sun, 05/10/2020 - 00:00
Use ProPublica
Hide sidebar & use full width
render the right sidebar.
Gating Strategy
First Peek Free
Article PDF Media

Can Medicine Bring Good Out of War?

Article Type
Changed
Mon, 05/20/2019 - 10:05

The title of this essay is more often posed as “Is War Good for Medicine?”2 The career VA physician in me, and the daughter and granddaughter of combat veterans, finds this question historically accurate, but ethically problematic. So I have rewritten the question to one that enables us to examine the historic relationship of medical advances and war from a more ethically justifiable posture. I am by no means ascribing to authors of other publications with this title anything but the highest motives of education and edification.

Yet the more I read and thought about the question(s), I realized that the moral assumptions underlying and supporting each concept are significantly different. What led me to that realization was a story my father told me when I was young which in my youthful ignorance I either dismissed or ignored. I now see that the narrative captured a profound truth about how war is not good especially for those who must wage it, but good may come from it for those who now live in peace.

My father was one of the founders of military pediatrics. Surprisingly, pediatricians were valuable members of the military medical forces because of their knowledge of infectious diseases.3 My father had gone in to the then new specialty of pediatrics because in the 1930s, infectious diseases were the primary cause of death in children. Before antibiotics, children would often die of common infections. Service as a combat medical officer in World War II stationed in the European Theater, my father had experience with and access to penicillin. After returning from the war to work in an Army hospital, he and his staff went into the acute pediatric ward and gave the drug to several very sick children, many of whom were likely to die. The next morning on rounds, they noted that many of the children were feeling much better, some even bouncing on their beds.

Perhaps either his telling or my remembering of these events is partly apocryphal, but the reality is that those lethal microbes had no idea what had hit them. Before human physicians overused the new drugs and nature struck back with antibiotic resistance, penicillin seemed miraculous.

Most likely, in 1945 those children would never have been prescribed penicillin, much less survived, if not for the unprecedented and war-driven consortium of industry and government that mass-produced penicillin to treat the troops with infections. Without a doubt then, from the sacrifice and devastation of World War II came the benefits and boons of the antibiotic era—one of the greatest discoveries in medical science.4

Penicillin is but one of legions of scientific discoveries that emerged during wartime. Many of these dramatic improvements, especially those in surgical techniques and emergency medicine, quickly entered the civilian sector. The French surgeon Amboise Paré, for example, revived an old Roman Army practice of using ligatures or tourniquets to stop excessive blood loss, now a staple of emergency responders in disasters. The ambulance services that transported wounded troops to the hospital began on the battlefields of the Civil War.5

These impressive contributions are the direct result of military medicine intended to preserve fighting strength. There are also indirect, although just as revolutionary, efforts of DoD and VA scientists and health care professionals to minimize disability and prevent progression especially of service-connected injuries and illnesses. Among the most groundbreaking is the VA’s 3D-printed artificial lung. I have to admit at first I thought that it was futuristic, but quickly I learned that it was a realistic possibility for the coming decades.6 VA researchers hope the lung will offer a treatment option for patients with chronic obstructive pulmonary disease (COPD), a lung condition more prevalent in veterans than in the civilian population.7 One contributing factor to the increased risk of COPD among former military is the higher rate of smoking among both active duty and veterans than that in the civilian population.8 And the last chain in the link of causation is that smoking is more common in those service members who have posttraumatic stress disorder.9

However, there also is a very dark side to the link between wartime research and medicine—most infamously the Nazi hypothermia experiments conducted at concentration camps. The proposed publication aroused a decades long ethical controversy regarding whether the data should be published, much less used, in research and practice even if it could save the lives of present or future warriors. In 1990, Marcia Angel, MD, then editor-in-chief of the prestigious New England Journal of Medicine, published the information with an accompanying ethical justification. “Finally, refusal to publish the unethical work serves notice to society at large that even scientists do not consider science the primary measure of a civilization. Knowledge, although important, may be less important to a decent society than the way it is obtained.”10 Ethicist Stephen Post writing on behalf of Holocaust victims strenuously disagreed with the decision to publish the research, “Because the Nazi experiments on human beings were so appallingly unethical, it follows, prima facie, that the use of the records is unethical.”11

This debate is key to the distinction between the 2 questions posed at the beginning of this column. Few who have been on a battlefield or who have cared for those who were can suggest or defend that wars should be fought as a catalyst for scientific research or an impetus to medical advancement. Such an instrumentalist view justifies the end of healing with the means of death, which is an intrinsic contradiction that would eventually corrode the integrity of the medical and scientific professions. Conversely, the second question challenges all of us in federal practice to assume a mantle of obligation to take the interventions that enabled combat medicine to save soldiers and apply them to improve the health and save the lives of veterans and civilians alike. It summons scientists laboring in the hundreds of DoD and VA laboratories to use the unparalleled funding and infrastructure of the institutions to develop promising therapeutics to treat the psychological toll and physical cost of war. And finally it charges the citizens whose family and friends have and will serve in uniform to enlist in a political process that enables military medicine and science to achieve the greatest good-health in peace.

References

1. Remarque EM. All Quiet on the Western Front. New York, NY: Fawcett Books; 1929:228.

2. Connell C. Is war good for medicine: war’s medical legacy? http://sm.stanford.edu/archive/stanmed/2007summer/main.html. Published 2007. Accessed April 18, 2019.

3. Burnett MW, Callahan CW. American pediatricians at war; a legacy of service. Pediatrics. 2012;129(suppl 1):S33-S49.

4. Ligon BL. Penicillin: its discovery and early development. Semin Pediatr Infect Dis. 2004;15(1):52-57.

5. Samuel L. 6 medical innovations that moved from the battlefield to mainstream medicine. https://www.scientificamercan.com/article/6-medical-innovations-that-moved-from-the-battlefield-to-mainstream-medicine. Published November 11, 2017. Accessed April 18, 2019.

6. Richman M. Breathing easier. https://www.research.va.gov/currents/0818-Researchers-strive-to-make-3D-printed-artificial-lung-to-help-Vets-with-respiratory-disease.cfm. Published August 1, 2018. Accessed April 18, 2019.

7. Murphy DE, Chaudry Z, Almoosa KF, Panos RJ. High prevalence of chronic obstructive pulmonary disease among veterans in the urban Midwest. Mill Med. 2011;176(5):552-560.

8. Thompson WH, St-Hilaire C. Prevalence of chronic obstructive pulmonary disease and tobacco use in veterans at Boise Veterans Affairs Medical Center. Respir Care. 2010;55(5):555-560.

9. Cook J, Jakupcak M, Rosenheck R, Fontana A, McFall M. Influence of PTSD symptom clusters on smoking status among help-seeking Iraq and Afghanistan veterans. Nicotine Tob Res. 2009;11(10):1189-1195.

10. Angell M. The Nazi hypothermia experiments and unethical research today. N Eng J Med 1990;322(20):1462-1464.

11. Post SG. The echo of Nuremberg: Nazi data and ethics. J Med Ethics. 1991;17(1):42-44.

Article PDF
Author and Disclosure Information

Cynthia M.A. Geppert, MD, Editor-in-Chief
Correspondence: Cynthia Geppert ([email protected])

Author disclosures
The author reports no actual or potential conflicts of interest with regard to this article.

Disclaimer
The opinions expressed herein are those of the author and do not necessarily reflect those of Federal Practitioner, Frontline Medical Communications Inc., the US Government, or any of its agencies. This article may discuss unlabeled or investigational use of certain drugs. Please review the complete prescribing information for specific drugs or drug combinations—including indications, contraindications, warnings, and adverse effects—before administering pharmacologic therapy to patients.

Issue
Federal Practitioner - 36(5)a
Publications
Topics
Page Number
204-205
Sections
Author and Disclosure Information

Cynthia M.A. Geppert, MD, Editor-in-Chief
Correspondence: Cynthia Geppert ([email protected])

Author disclosures
The author reports no actual or potential conflicts of interest with regard to this article.

Disclaimer
The opinions expressed herein are those of the author and do not necessarily reflect those of Federal Practitioner, Frontline Medical Communications Inc., the US Government, or any of its agencies. This article may discuss unlabeled or investigational use of certain drugs. Please review the complete prescribing information for specific drugs or drug combinations—including indications, contraindications, warnings, and adverse effects—before administering pharmacologic therapy to patients.

Author and Disclosure Information

Cynthia M.A. Geppert, MD, Editor-in-Chief
Correspondence: Cynthia Geppert ([email protected])

Author disclosures
The author reports no actual or potential conflicts of interest with regard to this article.

Disclaimer
The opinions expressed herein are those of the author and do not necessarily reflect those of Federal Practitioner, Frontline Medical Communications Inc., the US Government, or any of its agencies. This article may discuss unlabeled or investigational use of certain drugs. Please review the complete prescribing information for specific drugs or drug combinations—including indications, contraindications, warnings, and adverse effects—before administering pharmacologic therapy to patients.

Article PDF
Article PDF
Related Articles

The title of this essay is more often posed as “Is War Good for Medicine?”2 The career VA physician in me, and the daughter and granddaughter of combat veterans, finds this question historically accurate, but ethically problematic. So I have rewritten the question to one that enables us to examine the historic relationship of medical advances and war from a more ethically justifiable posture. I am by no means ascribing to authors of other publications with this title anything but the highest motives of education and edification.

Yet the more I read and thought about the question(s), I realized that the moral assumptions underlying and supporting each concept are significantly different. What led me to that realization was a story my father told me when I was young which in my youthful ignorance I either dismissed or ignored. I now see that the narrative captured a profound truth about how war is not good especially for those who must wage it, but good may come from it for those who now live in peace.

My father was one of the founders of military pediatrics. Surprisingly, pediatricians were valuable members of the military medical forces because of their knowledge of infectious diseases.3 My father had gone in to the then new specialty of pediatrics because in the 1930s, infectious diseases were the primary cause of death in children. Before antibiotics, children would often die of common infections. Service as a combat medical officer in World War II stationed in the European Theater, my father had experience with and access to penicillin. After returning from the war to work in an Army hospital, he and his staff went into the acute pediatric ward and gave the drug to several very sick children, many of whom were likely to die. The next morning on rounds, they noted that many of the children were feeling much better, some even bouncing on their beds.

Perhaps either his telling or my remembering of these events is partly apocryphal, but the reality is that those lethal microbes had no idea what had hit them. Before human physicians overused the new drugs and nature struck back with antibiotic resistance, penicillin seemed miraculous.

Most likely, in 1945 those children would never have been prescribed penicillin, much less survived, if not for the unprecedented and war-driven consortium of industry and government that mass-produced penicillin to treat the troops with infections. Without a doubt then, from the sacrifice and devastation of World War II came the benefits and boons of the antibiotic era—one of the greatest discoveries in medical science.4

Penicillin is but one of legions of scientific discoveries that emerged during wartime. Many of these dramatic improvements, especially those in surgical techniques and emergency medicine, quickly entered the civilian sector. The French surgeon Amboise Paré, for example, revived an old Roman Army practice of using ligatures or tourniquets to stop excessive blood loss, now a staple of emergency responders in disasters. The ambulance services that transported wounded troops to the hospital began on the battlefields of the Civil War.5

These impressive contributions are the direct result of military medicine intended to preserve fighting strength. There are also indirect, although just as revolutionary, efforts of DoD and VA scientists and health care professionals to minimize disability and prevent progression especially of service-connected injuries and illnesses. Among the most groundbreaking is the VA’s 3D-printed artificial lung. I have to admit at first I thought that it was futuristic, but quickly I learned that it was a realistic possibility for the coming decades.6 VA researchers hope the lung will offer a treatment option for patients with chronic obstructive pulmonary disease (COPD), a lung condition more prevalent in veterans than in the civilian population.7 One contributing factor to the increased risk of COPD among former military is the higher rate of smoking among both active duty and veterans than that in the civilian population.8 And the last chain in the link of causation is that smoking is more common in those service members who have posttraumatic stress disorder.9

However, there also is a very dark side to the link between wartime research and medicine—most infamously the Nazi hypothermia experiments conducted at concentration camps. The proposed publication aroused a decades long ethical controversy regarding whether the data should be published, much less used, in research and practice even if it could save the lives of present or future warriors. In 1990, Marcia Angel, MD, then editor-in-chief of the prestigious New England Journal of Medicine, published the information with an accompanying ethical justification. “Finally, refusal to publish the unethical work serves notice to society at large that even scientists do not consider science the primary measure of a civilization. Knowledge, although important, may be less important to a decent society than the way it is obtained.”10 Ethicist Stephen Post writing on behalf of Holocaust victims strenuously disagreed with the decision to publish the research, “Because the Nazi experiments on human beings were so appallingly unethical, it follows, prima facie, that the use of the records is unethical.”11

This debate is key to the distinction between the 2 questions posed at the beginning of this column. Few who have been on a battlefield or who have cared for those who were can suggest or defend that wars should be fought as a catalyst for scientific research or an impetus to medical advancement. Such an instrumentalist view justifies the end of healing with the means of death, which is an intrinsic contradiction that would eventually corrode the integrity of the medical and scientific professions. Conversely, the second question challenges all of us in federal practice to assume a mantle of obligation to take the interventions that enabled combat medicine to save soldiers and apply them to improve the health and save the lives of veterans and civilians alike. It summons scientists laboring in the hundreds of DoD and VA laboratories to use the unparalleled funding and infrastructure of the institutions to develop promising therapeutics to treat the psychological toll and physical cost of war. And finally it charges the citizens whose family and friends have and will serve in uniform to enlist in a political process that enables military medicine and science to achieve the greatest good-health in peace.

The title of this essay is more often posed as “Is War Good for Medicine?”2 The career VA physician in me, and the daughter and granddaughter of combat veterans, finds this question historically accurate, but ethically problematic. So I have rewritten the question to one that enables us to examine the historic relationship of medical advances and war from a more ethically justifiable posture. I am by no means ascribing to authors of other publications with this title anything but the highest motives of education and edification.

Yet the more I read and thought about the question(s), I realized that the moral assumptions underlying and supporting each concept are significantly different. What led me to that realization was a story my father told me when I was young which in my youthful ignorance I either dismissed or ignored. I now see that the narrative captured a profound truth about how war is not good especially for those who must wage it, but good may come from it for those who now live in peace.

My father was one of the founders of military pediatrics. Surprisingly, pediatricians were valuable members of the military medical forces because of their knowledge of infectious diseases.3 My father had gone in to the then new specialty of pediatrics because in the 1930s, infectious diseases were the primary cause of death in children. Before antibiotics, children would often die of common infections. Service as a combat medical officer in World War II stationed in the European Theater, my father had experience with and access to penicillin. After returning from the war to work in an Army hospital, he and his staff went into the acute pediatric ward and gave the drug to several very sick children, many of whom were likely to die. The next morning on rounds, they noted that many of the children were feeling much better, some even bouncing on their beds.

Perhaps either his telling or my remembering of these events is partly apocryphal, but the reality is that those lethal microbes had no idea what had hit them. Before human physicians overused the new drugs and nature struck back with antibiotic resistance, penicillin seemed miraculous.

Most likely, in 1945 those children would never have been prescribed penicillin, much less survived, if not for the unprecedented and war-driven consortium of industry and government that mass-produced penicillin to treat the troops with infections. Without a doubt then, from the sacrifice and devastation of World War II came the benefits and boons of the antibiotic era—one of the greatest discoveries in medical science.4

Penicillin is but one of legions of scientific discoveries that emerged during wartime. Many of these dramatic improvements, especially those in surgical techniques and emergency medicine, quickly entered the civilian sector. The French surgeon Amboise Paré, for example, revived an old Roman Army practice of using ligatures or tourniquets to stop excessive blood loss, now a staple of emergency responders in disasters. The ambulance services that transported wounded troops to the hospital began on the battlefields of the Civil War.5

These impressive contributions are the direct result of military medicine intended to preserve fighting strength. There are also indirect, although just as revolutionary, efforts of DoD and VA scientists and health care professionals to minimize disability and prevent progression especially of service-connected injuries and illnesses. Among the most groundbreaking is the VA’s 3D-printed artificial lung. I have to admit at first I thought that it was futuristic, but quickly I learned that it was a realistic possibility for the coming decades.6 VA researchers hope the lung will offer a treatment option for patients with chronic obstructive pulmonary disease (COPD), a lung condition more prevalent in veterans than in the civilian population.7 One contributing factor to the increased risk of COPD among former military is the higher rate of smoking among both active duty and veterans than that in the civilian population.8 And the last chain in the link of causation is that smoking is more common in those service members who have posttraumatic stress disorder.9

However, there also is a very dark side to the link between wartime research and medicine—most infamously the Nazi hypothermia experiments conducted at concentration camps. The proposed publication aroused a decades long ethical controversy regarding whether the data should be published, much less used, in research and practice even if it could save the lives of present or future warriors. In 1990, Marcia Angel, MD, then editor-in-chief of the prestigious New England Journal of Medicine, published the information with an accompanying ethical justification. “Finally, refusal to publish the unethical work serves notice to society at large that even scientists do not consider science the primary measure of a civilization. Knowledge, although important, may be less important to a decent society than the way it is obtained.”10 Ethicist Stephen Post writing on behalf of Holocaust victims strenuously disagreed with the decision to publish the research, “Because the Nazi experiments on human beings were so appallingly unethical, it follows, prima facie, that the use of the records is unethical.”11

This debate is key to the distinction between the 2 questions posed at the beginning of this column. Few who have been on a battlefield or who have cared for those who were can suggest or defend that wars should be fought as a catalyst for scientific research or an impetus to medical advancement. Such an instrumentalist view justifies the end of healing with the means of death, which is an intrinsic contradiction that would eventually corrode the integrity of the medical and scientific professions. Conversely, the second question challenges all of us in federal practice to assume a mantle of obligation to take the interventions that enabled combat medicine to save soldiers and apply them to improve the health and save the lives of veterans and civilians alike. It summons scientists laboring in the hundreds of DoD and VA laboratories to use the unparalleled funding and infrastructure of the institutions to develop promising therapeutics to treat the psychological toll and physical cost of war. And finally it charges the citizens whose family and friends have and will serve in uniform to enlist in a political process that enables military medicine and science to achieve the greatest good-health in peace.

References

1. Remarque EM. All Quiet on the Western Front. New York, NY: Fawcett Books; 1929:228.

2. Connell C. Is war good for medicine: war’s medical legacy? http://sm.stanford.edu/archive/stanmed/2007summer/main.html. Published 2007. Accessed April 18, 2019.

3. Burnett MW, Callahan CW. American pediatricians at war; a legacy of service. Pediatrics. 2012;129(suppl 1):S33-S49.

4. Ligon BL. Penicillin: its discovery and early development. Semin Pediatr Infect Dis. 2004;15(1):52-57.

5. Samuel L. 6 medical innovations that moved from the battlefield to mainstream medicine. https://www.scientificamercan.com/article/6-medical-innovations-that-moved-from-the-battlefield-to-mainstream-medicine. Published November 11, 2017. Accessed April 18, 2019.

6. Richman M. Breathing easier. https://www.research.va.gov/currents/0818-Researchers-strive-to-make-3D-printed-artificial-lung-to-help-Vets-with-respiratory-disease.cfm. Published August 1, 2018. Accessed April 18, 2019.

7. Murphy DE, Chaudry Z, Almoosa KF, Panos RJ. High prevalence of chronic obstructive pulmonary disease among veterans in the urban Midwest. Mill Med. 2011;176(5):552-560.

8. Thompson WH, St-Hilaire C. Prevalence of chronic obstructive pulmonary disease and tobacco use in veterans at Boise Veterans Affairs Medical Center. Respir Care. 2010;55(5):555-560.

9. Cook J, Jakupcak M, Rosenheck R, Fontana A, McFall M. Influence of PTSD symptom clusters on smoking status among help-seeking Iraq and Afghanistan veterans. Nicotine Tob Res. 2009;11(10):1189-1195.

10. Angell M. The Nazi hypothermia experiments and unethical research today. N Eng J Med 1990;322(20):1462-1464.

11. Post SG. The echo of Nuremberg: Nazi data and ethics. J Med Ethics. 1991;17(1):42-44.

References

1. Remarque EM. All Quiet on the Western Front. New York, NY: Fawcett Books; 1929:228.

2. Connell C. Is war good for medicine: war’s medical legacy? http://sm.stanford.edu/archive/stanmed/2007summer/main.html. Published 2007. Accessed April 18, 2019.

3. Burnett MW, Callahan CW. American pediatricians at war; a legacy of service. Pediatrics. 2012;129(suppl 1):S33-S49.

4. Ligon BL. Penicillin: its discovery and early development. Semin Pediatr Infect Dis. 2004;15(1):52-57.

5. Samuel L. 6 medical innovations that moved from the battlefield to mainstream medicine. https://www.scientificamercan.com/article/6-medical-innovations-that-moved-from-the-battlefield-to-mainstream-medicine. Published November 11, 2017. Accessed April 18, 2019.

6. Richman M. Breathing easier. https://www.research.va.gov/currents/0818-Researchers-strive-to-make-3D-printed-artificial-lung-to-help-Vets-with-respiratory-disease.cfm. Published August 1, 2018. Accessed April 18, 2019.

7. Murphy DE, Chaudry Z, Almoosa KF, Panos RJ. High prevalence of chronic obstructive pulmonary disease among veterans in the urban Midwest. Mill Med. 2011;176(5):552-560.

8. Thompson WH, St-Hilaire C. Prevalence of chronic obstructive pulmonary disease and tobacco use in veterans at Boise Veterans Affairs Medical Center. Respir Care. 2010;55(5):555-560.

9. Cook J, Jakupcak M, Rosenheck R, Fontana A, McFall M. Influence of PTSD symptom clusters on smoking status among help-seeking Iraq and Afghanistan veterans. Nicotine Tob Res. 2009;11(10):1189-1195.

10. Angell M. The Nazi hypothermia experiments and unethical research today. N Eng J Med 1990;322(20):1462-1464.

11. Post SG. The echo of Nuremberg: Nazi data and ethics. J Med Ethics. 1991;17(1):42-44.

Issue
Federal Practitioner - 36(5)a
Issue
Federal Practitioner - 36(5)a
Page Number
204-205
Page Number
204-205
Publications
Publications
Topics
Article Type
Sections
Disallow All Ads
Content Gating
No Gating (article Unlocked/Free)
Alternative CME
Disqus Comments
Default
Use ProPublica
Hide sidebar & use full width
render the right sidebar.
Article PDF Media

Development of a Program to Support VA Community Living Centers’ Quality Improvement

Article Type
Changed
Mon, 05/20/2019 - 09:56

US Department of Veterans Affairs (VA) Community Living Centers (CLCs) provide a dynamic array of long- and short-term health and rehabilitative services in a person-centered environment designed to meet the individual needs of veteran residents. The VA Office of Geriatrics and Extended Care (GEC) manages CLCs as part of its commitment to “optimizing the health and well-being of veterans with multiple chronic conditions, life-limiting illness, frailty or disability associated with chronic disease, aging or injury.”1

CLCs are home to veterans who require short stays before going home, as well as those who require longer or permanent domicile. CLCs also are home to several special populations of veterans, including those with spinal cord injury and those who choose palliative or hospice care. CLCs have embraced cultural transformation, creating therapeutic environments that function as real homes, with the kitchen at the center, and daily activities scheduled around the veterans’ preferences. Data about CLC quality are now available to the public, highlighting the important role of support for and continual refinement to quality improvement (QI) processes in the CLC system. 2,3

CONCERT Program

High-functioning teams are critical to achieving improvement in such processes.4 In fiscal year (FY) 2017, GEC launched a national center to engage and support CLC staff in creating high-functioning, relationship-based teams through specific QI practices, thereby aiming to improve veteran experience and quality of care. The center, known as the CLCs’ Ongoing National Center for Enhancing Resources and Training (CONCERT), is based on extensive VA-funded research in CLCs5-7 and builds on existing, evidence-based literature emphasizing the importance of strengths-based learning, collaborative problem solving, and structured observation.8-13 The CONCERT mission is to support CLCs in ongoing QI efforts, providing guidance, training, and resources. This article summarizes the previous research on which CONCERT is based and describes its current activities, which focus on implementing a national team-based quality improvement initiative.

Earlier VA-funded CLC research included a VA Office of Patient Centered Care and Cultural Transformation local innovation project and 2 VA Office of Research and Development-funded research studies. The local innovation project focused on strengthening staff leadership and relational skills in 1 CLC by engaging leaders and staff in collaborative work to reduce stress. The goal was to build high-functioning team skills through shared projects that created positive work experiences and reduced job-related stress while also improving veteran experience and quality of care.14,15 Over the course of a year, 2 national consultants in nursing home quality improvement worked with CLC leadership and staff, including conducting nine 4-day site visits. Using an approach designed to foster development of high-functioning teams, individual CLC neighborhoods (ie, units) developed and implemented neighborhood-initiated, neighborhood-based pilot projects, such as an individualized finger foods dining option for residents with dementia who became distressed when sitting at a table during a meal. Outcomes of these projects included improved staff communication and staff satisfaction, particularly psychological safety.

In the concurrently conducted pilot research study, a research team comprehensively assessed the person-centered care efforts of 3 CLCs prior to their construction of Green House-type (small house) homes. This mixed-methods study included more than 50 qualitative interviews conducted with VA medical center leadership and CLC staff and residents. Researchers also administered online employee surveys and conducted site visits, including more than 60 hours of direct observation of CLC life and team functioning. The local institutional review boards approved all study procedures, and researchers notified local unions.

Analyses highlighted 2 important aspects of person-centered care not captured by then-existing measurement instruments: the type, quality, and number of staff/resident interactions and the type, quality, and level of resident engagement. The team therefore developed a structured, systematic, observation-based instrument to measure these concepts.5 But while researchers found this instrument useful, it was too complex to be used by CLC staff for QI.

 

 

LOCK Quality Improvement

A later and larger research study addressed this issue. In the study, researchers worked with CLC staff to convert the complex observation-based research instrument into several structured tools that were easier for CLC staff to use.6 The researchers then incorporated their experience with the prior local innovation project and designed and implemented a QI program, which operationalized an evidence-based bundle of practices to implement the new tools in 6 CLCs. Researchers called the bundle of practices “LOCK”: (1) Learn from the bright spots; (2) Observe; (3) Collaborate in huddles; and (4) Keep it bite-sized.

Learn from the bright spots. Studies on strengths-based learning indicate that recognizing and sharing positive instances of ideal practice helps provide clear direction regarding what needs to be done differently to achieve success. Identifying and learning from outlying instances of successful practice encourages staff to continue those behaviors and gives staff tangible examples of how they may improve.16-19 That is, concentrating on instances where a negative outcome was at risk of occurring but did not occur (ie, a positive outlier or “bright spot”) enables staff to analyze what facilitated the success and design and pilot strategies to replicate it.

Observe. Human factors engineering is built on the principle that integrated approaches for studying work systems can identify areas for improvement.8 Observation is a key tool in this approach. A recent review of 69 studies that used observation to assess clinical performance found it useful in identifying factors affecting quality and safety.9

Collaborate in huddles. A necessary component to overcoming barriers to successful QI is having high-functioning teams effectively coordinate work. In the theory of relational coordination, this is operationalized as high-quality interactions (frequent, timely, and accurate communication) and high-quality relationships (share knowledge, shared goals, and mutual respect).10,11 Improved relational coordination can lead to higher quality of care outcomes and job satisfaction by enabling individuals to manage their tasks with less delay, more rapid and effective responses, fewer errors, and less wasted effort.12

Keep it bite-sized. Regular practice of a new behavior is one of the keys to making that new behavior part of an automatic routine (ie, a habit). To be successfully integrated into staff work routines, QI initiatives must be perceived as congruent with and easily integrated into care goals and workplace practices. Quick, focused, team-building and solution-oriented QI initiatives, therefore, have the greatest chance of success, particularly if staff feel they have little time for participating in new initiatives.13

Researchers designed the 4 LOCK practices to be interrelated and build on one another, creating a bundle to be used together to help facilitate positive change in resident/staff interactions and resident engagement.7 For 6 months, researchers studied the 6 CLCs’ use of the new structured observation tools as part of the LOCK-based QI program. The participating CLCs had such success in improving staff interactions with residents and residents’ engagement in CLC life that GEC, under the CONCERT umbrella, rolled out the LOCK bundle of practices to CLCs nationwide.20

CONCERT’s current activities focus on helping CLCs implement the LOCK bundle nationwide as a relational coordination-based national QI initiative designed to improve quality of care and staff satisfaction. The CONCERT team began this implementation in FY 2017 using a train-the-trainer approach through a staggered veterans integrated service network (VISN) rollout. Each CLC sent 2 leaders to a VISN-wide training program at a host CLC site (the host site was able to have more participants attend). Afterward, the CONCERT team provided individualized phone support to help CLCs implement the program. A VA Pulse (intranet-based social media portal) site hosts all training materials, program videos, an active blog, community discussions, etc.

In FY 2018, the program shifted to a VISN-based support system, with a CONCERT team member assigned to each VISN and VISN-based webinars to facilitate information exchange, collaboration, and group learning. In FY 2018, the CONCERT team also conducted site visits to selected CLCs with strong implementation success records to learn about program facilitators and to disseminate the lessons learned. Spanning FYs 2018 and 2019, the CONCERT team also supports historically low-performing CLCs through a series of rapid-cycle learning intensives based on the Institute for Healthcare Improvement breakthrough collaborative series model for accelerated and sustained QI.21 These incorporate in-person or virtual learning sessions, in which participants learn about and share effective practices, and between-session learning assignments, to facilitate the piloting, implementation, and sustainment of system changes. As part of the CONCERT continuous QI process, the CONCERT team closely monitors the impact of the program and continues to pilot, adapt, and change practices as it learns more about how best to help CLCs improve.

 

 

Conclusion

A key CONCERT principle is that health care systems create health care outcomes. The CONCERT team uses the theory of relational coordination to support implementation of the LOCK bundle of practices to help CLCs change their systems to achieve high performance. Through implementation of the LOCK bundle of practices, CLC staff develop, pilot, and spread new systems for communication, teamwork, and collaborative problem solving, as well as developing skills to participate effectively in these systems. CONCERT represents just 1 way VA supports CLCs in their continual journeys toward ever-improved quality of veteran care.

Acknowledgments
The authors thank Barbara Frank and Cathie Brady for their contributions to the development of the CONCERT program.

References

1. US Department of Veterans Affairs, Geriatrics and Extended Care Services (GEC). https://www.va.gov/GERIATRICS/index.asp. Updated February 25, 2019. Accessed April 9, 2019.

2. US Department of Veterans Affairs. https://www.accesstocare.va.gov/CNH/Statemap. Accessed April 10, 2019.

3. US Department of Veterans Affairs. https://www.va.gov/QUALITYOFCARE/apps/aspire/clcsurvey.aspx/. Updated September 21, 2015. Accessed April 10, 2019.

4. Gittell JH, Weinberg D, Pfefferle S, Bishop C. Impact of relational coordination on job satisfaction and quality outcomes: a study of nursing homes. Hum Resour Manag. 2008;18(2):154-170

5. Snow AL, Dodson, ML, Palmer JA, et al. Development of a new systematic observation tool of nursing home resident and staff engagement and relationship. Gerontologist. 2018;58(2):e15-e24.

6. Hartmann CW, Palmer JA, Mills WL, et al. Adaptation of a nursing home culture change research instrument for frontline staff quality improvement use. Psychol Serv. 2017;14(3):337-346.

7. Mills WL, Pimentel CB, Palmer JA, et al. Applying a theory-driven framework to guide quality improvement efforts in nursing homes: the LOCK model. Gerontologist. 2018;58(3):598-605.

8. Caravon P, Hundt AS, Karsh B, et al. Work system design for patient safety: the SEIPS model. Quality & Safety in Health Care. 2006;15(suppl 1), i50-i58.

9. Yanes AF, McElroy LM, Abecassis ZA, Holl J, Woods D, Ladner DP. Observation for assessment of clinician performance: a narrative review. BMJ Qual Saf. 2016;25(1):46-55.

10. Gittell JH. Supervisory span, relational coordination and flight departure performance: a reassessment of postbureaucracy theory. Organ Sci. 2011;12(4):468-483.

11. Gittell JH. New Directions for Relational Coordination Theory. In Spreitzer GM, Cameron KS, eds. The Oxford Handbook of Positive Organizational Scholarship. Oxford University Press: New York; 2012:400-411.

12. Weinberg DB, Lusenhop RW, Gittell JH, Kautz CM. Coordination between formal providers and informal caregivers. Health Care Manage Rev. 2007;32(2):140-149.

13. Phillips J, Hebish LJ, Mann S, Ching JM, Blackmore CC. Engaging frontline leaders and staff in real-time improvement. Jt Comm J Qual Patient Saf. 2016;42(4):170-183.

14. Farrell D, Brady C, Frank B. Meeting the Leadership Challenge in Long-Term Care: What You Do Matters. Health Professions Press: Baltimore, MD; 2011.

15. Brady C, Farrell D, Frank B. A Long-Term Leaders’ Guide to High Performance: Doing Better Together. Health Professions Press: Baltimore, MD; 2018.

16. Bradley EH, Curry LA, Ramanadhan S, Rowe L, Nembhard IM, Krumholz HM. Research in action: using positive deviance to improve quality of health care. Implement Sci. 2009;4:25.

17. Marsh DR, Schroeder DG, Dearden KA, Sternin J, Sternin M. The power of positive deviance. BMJ. 2004; 329(7475):1177-1179.

18. Vogt K, Johnson F, Fraser V, et al. An innovative, strengths-based, peer mentoring approach to professional development for registered dietitians. Can J Diet Pract Res. 2015;76(4):185-189.

19. Beckett P, Field J, Molloy L, Yu N, Holmes D, Pile E. Practice what you preach: developing person-centered culture in inpatient mental health settings through strengths-based, transformational leadership. Issues Ment Health Nurs. 2013;34(8):595-601.

20. Hartmann CW, Mills WL, Pimentel CB, et al. Impact of intervention to improve nursing home resident-staff interactions and engagement. Gerontologist. 2018;58(4):e291-e301.

21. Institute for Healthcare Improvement. The breakthrough series: IHI’s collaborative model for achieving breakthrough improvement. http://www.ihi.org/resources/Pages/IHIWhitePapers/TheBreakthroughSeriesIHIsCollaborativeModelforAchievingBreakthroughImprovement.aspx. Published 2003. Accessed April 9, 2019.

Article PDF
Author and Disclosure Information

Christine Hartmann is a Supervisory Research Health Scientist, Center for Healthcare Organization and Implementation Research at the Edith Nourse Rogers Memorial Veterans Hospital in Bedford; and a Research Associate Professor, Department of Health Law, Policy and Management at the School of Public Health, Boston University, in Massachusetts. Lisa Minor is Director, Community Living Centers, Department of Veterans Affairs (VA) Office of Geriatrics and Extended Care in Washington, DC. Lynn Snow is a Research Health Scientist at Tuscaloosa VA Medical Center and a Professor in the Alabama Research Institute on Aging and the Department of Psychology at the University of Alabama in Tuscaloosa.
Correspondence: Christine Hartmann ([email protected])

Author disclosures
The authors report no actual or potential conflicts of interest with regard to this article.

Disclaimer
The opinions expressed herein are those of the authors and do not necessarily reflect those of Federal Practitioner, Frontline Medical Communications Inc., the US Government, or any of its agencies.

Issue
Federal Practitioner - 36(5)a
Publications
Topics
Page Number
228-231
Sections
Author and Disclosure Information

Christine Hartmann is a Supervisory Research Health Scientist, Center for Healthcare Organization and Implementation Research at the Edith Nourse Rogers Memorial Veterans Hospital in Bedford; and a Research Associate Professor, Department of Health Law, Policy and Management at the School of Public Health, Boston University, in Massachusetts. Lisa Minor is Director, Community Living Centers, Department of Veterans Affairs (VA) Office of Geriatrics and Extended Care in Washington, DC. Lynn Snow is a Research Health Scientist at Tuscaloosa VA Medical Center and a Professor in the Alabama Research Institute on Aging and the Department of Psychology at the University of Alabama in Tuscaloosa.
Correspondence: Christine Hartmann ([email protected])

Author disclosures
The authors report no actual or potential conflicts of interest with regard to this article.

Disclaimer
The opinions expressed herein are those of the authors and do not necessarily reflect those of Federal Practitioner, Frontline Medical Communications Inc., the US Government, or any of its agencies.

Author and Disclosure Information

Christine Hartmann is a Supervisory Research Health Scientist, Center for Healthcare Organization and Implementation Research at the Edith Nourse Rogers Memorial Veterans Hospital in Bedford; and a Research Associate Professor, Department of Health Law, Policy and Management at the School of Public Health, Boston University, in Massachusetts. Lisa Minor is Director, Community Living Centers, Department of Veterans Affairs (VA) Office of Geriatrics and Extended Care in Washington, DC. Lynn Snow is a Research Health Scientist at Tuscaloosa VA Medical Center and a Professor in the Alabama Research Institute on Aging and the Department of Psychology at the University of Alabama in Tuscaloosa.
Correspondence: Christine Hartmann ([email protected])

Author disclosures
The authors report no actual or potential conflicts of interest with regard to this article.

Disclaimer
The opinions expressed herein are those of the authors and do not necessarily reflect those of Federal Practitioner, Frontline Medical Communications Inc., the US Government, or any of its agencies.

Article PDF
Article PDF
Related Articles

US Department of Veterans Affairs (VA) Community Living Centers (CLCs) provide a dynamic array of long- and short-term health and rehabilitative services in a person-centered environment designed to meet the individual needs of veteran residents. The VA Office of Geriatrics and Extended Care (GEC) manages CLCs as part of its commitment to “optimizing the health and well-being of veterans with multiple chronic conditions, life-limiting illness, frailty or disability associated with chronic disease, aging or injury.”1

CLCs are home to veterans who require short stays before going home, as well as those who require longer or permanent domicile. CLCs also are home to several special populations of veterans, including those with spinal cord injury and those who choose palliative or hospice care. CLCs have embraced cultural transformation, creating therapeutic environments that function as real homes, with the kitchen at the center, and daily activities scheduled around the veterans’ preferences. Data about CLC quality are now available to the public, highlighting the important role of support for and continual refinement to quality improvement (QI) processes in the CLC system. 2,3

CONCERT Program

High-functioning teams are critical to achieving improvement in such processes.4 In fiscal year (FY) 2017, GEC launched a national center to engage and support CLC staff in creating high-functioning, relationship-based teams through specific QI practices, thereby aiming to improve veteran experience and quality of care. The center, known as the CLCs’ Ongoing National Center for Enhancing Resources and Training (CONCERT), is based on extensive VA-funded research in CLCs5-7 and builds on existing, evidence-based literature emphasizing the importance of strengths-based learning, collaborative problem solving, and structured observation.8-13 The CONCERT mission is to support CLCs in ongoing QI efforts, providing guidance, training, and resources. This article summarizes the previous research on which CONCERT is based and describes its current activities, which focus on implementing a national team-based quality improvement initiative.

Earlier VA-funded CLC research included a VA Office of Patient Centered Care and Cultural Transformation local innovation project and 2 VA Office of Research and Development-funded research studies. The local innovation project focused on strengthening staff leadership and relational skills in 1 CLC by engaging leaders and staff in collaborative work to reduce stress. The goal was to build high-functioning team skills through shared projects that created positive work experiences and reduced job-related stress while also improving veteran experience and quality of care.14,15 Over the course of a year, 2 national consultants in nursing home quality improvement worked with CLC leadership and staff, including conducting nine 4-day site visits. Using an approach designed to foster development of high-functioning teams, individual CLC neighborhoods (ie, units) developed and implemented neighborhood-initiated, neighborhood-based pilot projects, such as an individualized finger foods dining option for residents with dementia who became distressed when sitting at a table during a meal. Outcomes of these projects included improved staff communication and staff satisfaction, particularly psychological safety.

In the concurrently conducted pilot research study, a research team comprehensively assessed the person-centered care efforts of 3 CLCs prior to their construction of Green House-type (small house) homes. This mixed-methods study included more than 50 qualitative interviews conducted with VA medical center leadership and CLC staff and residents. Researchers also administered online employee surveys and conducted site visits, including more than 60 hours of direct observation of CLC life and team functioning. The local institutional review boards approved all study procedures, and researchers notified local unions.

Analyses highlighted 2 important aspects of person-centered care not captured by then-existing measurement instruments: the type, quality, and number of staff/resident interactions and the type, quality, and level of resident engagement. The team therefore developed a structured, systematic, observation-based instrument to measure these concepts.5 But while researchers found this instrument useful, it was too complex to be used by CLC staff for QI.

 

 

LOCK Quality Improvement

A later and larger research study addressed this issue. In the study, researchers worked with CLC staff to convert the complex observation-based research instrument into several structured tools that were easier for CLC staff to use.6 The researchers then incorporated their experience with the prior local innovation project and designed and implemented a QI program, which operationalized an evidence-based bundle of practices to implement the new tools in 6 CLCs. Researchers called the bundle of practices “LOCK”: (1) Learn from the bright spots; (2) Observe; (3) Collaborate in huddles; and (4) Keep it bite-sized.

Learn from the bright spots. Studies on strengths-based learning indicate that recognizing and sharing positive instances of ideal practice helps provide clear direction regarding what needs to be done differently to achieve success. Identifying and learning from outlying instances of successful practice encourages staff to continue those behaviors and gives staff tangible examples of how they may improve.16-19 That is, concentrating on instances where a negative outcome was at risk of occurring but did not occur (ie, a positive outlier or “bright spot”) enables staff to analyze what facilitated the success and design and pilot strategies to replicate it.

Observe. Human factors engineering is built on the principle that integrated approaches for studying work systems can identify areas for improvement.8 Observation is a key tool in this approach. A recent review of 69 studies that used observation to assess clinical performance found it useful in identifying factors affecting quality and safety.9

Collaborate in huddles. A necessary component to overcoming barriers to successful QI is having high-functioning teams effectively coordinate work. In the theory of relational coordination, this is operationalized as high-quality interactions (frequent, timely, and accurate communication) and high-quality relationships (share knowledge, shared goals, and mutual respect).10,11 Improved relational coordination can lead to higher quality of care outcomes and job satisfaction by enabling individuals to manage their tasks with less delay, more rapid and effective responses, fewer errors, and less wasted effort.12

Keep it bite-sized. Regular practice of a new behavior is one of the keys to making that new behavior part of an automatic routine (ie, a habit). To be successfully integrated into staff work routines, QI initiatives must be perceived as congruent with and easily integrated into care goals and workplace practices. Quick, focused, team-building and solution-oriented QI initiatives, therefore, have the greatest chance of success, particularly if staff feel they have little time for participating in new initiatives.13

Researchers designed the 4 LOCK practices to be interrelated and build on one another, creating a bundle to be used together to help facilitate positive change in resident/staff interactions and resident engagement.7 For 6 months, researchers studied the 6 CLCs’ use of the new structured observation tools as part of the LOCK-based QI program. The participating CLCs had such success in improving staff interactions with residents and residents’ engagement in CLC life that GEC, under the CONCERT umbrella, rolled out the LOCK bundle of practices to CLCs nationwide.20

CONCERT’s current activities focus on helping CLCs implement the LOCK bundle nationwide as a relational coordination-based national QI initiative designed to improve quality of care and staff satisfaction. The CONCERT team began this implementation in FY 2017 using a train-the-trainer approach through a staggered veterans integrated service network (VISN) rollout. Each CLC sent 2 leaders to a VISN-wide training program at a host CLC site (the host site was able to have more participants attend). Afterward, the CONCERT team provided individualized phone support to help CLCs implement the program. A VA Pulse (intranet-based social media portal) site hosts all training materials, program videos, an active blog, community discussions, etc.

In FY 2018, the program shifted to a VISN-based support system, with a CONCERT team member assigned to each VISN and VISN-based webinars to facilitate information exchange, collaboration, and group learning. In FY 2018, the CONCERT team also conducted site visits to selected CLCs with strong implementation success records to learn about program facilitators and to disseminate the lessons learned. Spanning FYs 2018 and 2019, the CONCERT team also supports historically low-performing CLCs through a series of rapid-cycle learning intensives based on the Institute for Healthcare Improvement breakthrough collaborative series model for accelerated and sustained QI.21 These incorporate in-person or virtual learning sessions, in which participants learn about and share effective practices, and between-session learning assignments, to facilitate the piloting, implementation, and sustainment of system changes. As part of the CONCERT continuous QI process, the CONCERT team closely monitors the impact of the program and continues to pilot, adapt, and change practices as it learns more about how best to help CLCs improve.

 

 

Conclusion

A key CONCERT principle is that health care systems create health care outcomes. The CONCERT team uses the theory of relational coordination to support implementation of the LOCK bundle of practices to help CLCs change their systems to achieve high performance. Through implementation of the LOCK bundle of practices, CLC staff develop, pilot, and spread new systems for communication, teamwork, and collaborative problem solving, as well as developing skills to participate effectively in these systems. CONCERT represents just 1 way VA supports CLCs in their continual journeys toward ever-improved quality of veteran care.

Acknowledgments
The authors thank Barbara Frank and Cathie Brady for their contributions to the development of the CONCERT program.

US Department of Veterans Affairs (VA) Community Living Centers (CLCs) provide a dynamic array of long- and short-term health and rehabilitative services in a person-centered environment designed to meet the individual needs of veteran residents. The VA Office of Geriatrics and Extended Care (GEC) manages CLCs as part of its commitment to “optimizing the health and well-being of veterans with multiple chronic conditions, life-limiting illness, frailty or disability associated with chronic disease, aging or injury.”1

CLCs are home to veterans who require short stays before going home, as well as those who require longer or permanent domicile. CLCs also are home to several special populations of veterans, including those with spinal cord injury and those who choose palliative or hospice care. CLCs have embraced cultural transformation, creating therapeutic environments that function as real homes, with the kitchen at the center, and daily activities scheduled around the veterans’ preferences. Data about CLC quality are now available to the public, highlighting the important role of support for and continual refinement to quality improvement (QI) processes in the CLC system. 2,3

CONCERT Program

High-functioning teams are critical to achieving improvement in such processes.4 In fiscal year (FY) 2017, GEC launched a national center to engage and support CLC staff in creating high-functioning, relationship-based teams through specific QI practices, thereby aiming to improve veteran experience and quality of care. The center, known as the CLCs’ Ongoing National Center for Enhancing Resources and Training (CONCERT), is based on extensive VA-funded research in CLCs5-7 and builds on existing, evidence-based literature emphasizing the importance of strengths-based learning, collaborative problem solving, and structured observation.8-13 The CONCERT mission is to support CLCs in ongoing QI efforts, providing guidance, training, and resources. This article summarizes the previous research on which CONCERT is based and describes its current activities, which focus on implementing a national team-based quality improvement initiative.

Earlier VA-funded CLC research included a VA Office of Patient Centered Care and Cultural Transformation local innovation project and 2 VA Office of Research and Development-funded research studies. The local innovation project focused on strengthening staff leadership and relational skills in 1 CLC by engaging leaders and staff in collaborative work to reduce stress. The goal was to build high-functioning team skills through shared projects that created positive work experiences and reduced job-related stress while also improving veteran experience and quality of care.14,15 Over the course of a year, 2 national consultants in nursing home quality improvement worked with CLC leadership and staff, including conducting nine 4-day site visits. Using an approach designed to foster development of high-functioning teams, individual CLC neighborhoods (ie, units) developed and implemented neighborhood-initiated, neighborhood-based pilot projects, such as an individualized finger foods dining option for residents with dementia who became distressed when sitting at a table during a meal. Outcomes of these projects included improved staff communication and staff satisfaction, particularly psychological safety.

In the concurrently conducted pilot research study, a research team comprehensively assessed the person-centered care efforts of 3 CLCs prior to their construction of Green House-type (small house) homes. This mixed-methods study included more than 50 qualitative interviews conducted with VA medical center leadership and CLC staff and residents. Researchers also administered online employee surveys and conducted site visits, including more than 60 hours of direct observation of CLC life and team functioning. The local institutional review boards approved all study procedures, and researchers notified local unions.

Analyses highlighted 2 important aspects of person-centered care not captured by then-existing measurement instruments: the type, quality, and number of staff/resident interactions and the type, quality, and level of resident engagement. The team therefore developed a structured, systematic, observation-based instrument to measure these concepts.5 But while researchers found this instrument useful, it was too complex to be used by CLC staff for QI.

 

 

LOCK Quality Improvement

A later and larger research study addressed this issue. In the study, researchers worked with CLC staff to convert the complex observation-based research instrument into several structured tools that were easier for CLC staff to use.6 The researchers then incorporated their experience with the prior local innovation project and designed and implemented a QI program, which operationalized an evidence-based bundle of practices to implement the new tools in 6 CLCs. Researchers called the bundle of practices “LOCK”: (1) Learn from the bright spots; (2) Observe; (3) Collaborate in huddles; and (4) Keep it bite-sized.

Learn from the bright spots. Studies on strengths-based learning indicate that recognizing and sharing positive instances of ideal practice helps provide clear direction regarding what needs to be done differently to achieve success. Identifying and learning from outlying instances of successful practice encourages staff to continue those behaviors and gives staff tangible examples of how they may improve.16-19 That is, concentrating on instances where a negative outcome was at risk of occurring but did not occur (ie, a positive outlier or “bright spot”) enables staff to analyze what facilitated the success and design and pilot strategies to replicate it.

Observe. Human factors engineering is built on the principle that integrated approaches for studying work systems can identify areas for improvement.8 Observation is a key tool in this approach. A recent review of 69 studies that used observation to assess clinical performance found it useful in identifying factors affecting quality and safety.9

Collaborate in huddles. A necessary component to overcoming barriers to successful QI is having high-functioning teams effectively coordinate work. In the theory of relational coordination, this is operationalized as high-quality interactions (frequent, timely, and accurate communication) and high-quality relationships (share knowledge, shared goals, and mutual respect).10,11 Improved relational coordination can lead to higher quality of care outcomes and job satisfaction by enabling individuals to manage their tasks with less delay, more rapid and effective responses, fewer errors, and less wasted effort.12

Keep it bite-sized. Regular practice of a new behavior is one of the keys to making that new behavior part of an automatic routine (ie, a habit). To be successfully integrated into staff work routines, QI initiatives must be perceived as congruent with and easily integrated into care goals and workplace practices. Quick, focused, team-building and solution-oriented QI initiatives, therefore, have the greatest chance of success, particularly if staff feel they have little time for participating in new initiatives.13

Researchers designed the 4 LOCK practices to be interrelated and build on one another, creating a bundle to be used together to help facilitate positive change in resident/staff interactions and resident engagement.7 For 6 months, researchers studied the 6 CLCs’ use of the new structured observation tools as part of the LOCK-based QI program. The participating CLCs had such success in improving staff interactions with residents and residents’ engagement in CLC life that GEC, under the CONCERT umbrella, rolled out the LOCK bundle of practices to CLCs nationwide.20

CONCERT’s current activities focus on helping CLCs implement the LOCK bundle nationwide as a relational coordination-based national QI initiative designed to improve quality of care and staff satisfaction. The CONCERT team began this implementation in FY 2017 using a train-the-trainer approach through a staggered veterans integrated service network (VISN) rollout. Each CLC sent 2 leaders to a VISN-wide training program at a host CLC site (the host site was able to have more participants attend). Afterward, the CONCERT team provided individualized phone support to help CLCs implement the program. A VA Pulse (intranet-based social media portal) site hosts all training materials, program videos, an active blog, community discussions, etc.

In FY 2018, the program shifted to a VISN-based support system, with a CONCERT team member assigned to each VISN and VISN-based webinars to facilitate information exchange, collaboration, and group learning. In FY 2018, the CONCERT team also conducted site visits to selected CLCs with strong implementation success records to learn about program facilitators and to disseminate the lessons learned. Spanning FYs 2018 and 2019, the CONCERT team also supports historically low-performing CLCs through a series of rapid-cycle learning intensives based on the Institute for Healthcare Improvement breakthrough collaborative series model for accelerated and sustained QI.21 These incorporate in-person or virtual learning sessions, in which participants learn about and share effective practices, and between-session learning assignments, to facilitate the piloting, implementation, and sustainment of system changes. As part of the CONCERT continuous QI process, the CONCERT team closely monitors the impact of the program and continues to pilot, adapt, and change practices as it learns more about how best to help CLCs improve.

 

 

Conclusion

A key CONCERT principle is that health care systems create health care outcomes. The CONCERT team uses the theory of relational coordination to support implementation of the LOCK bundle of practices to help CLCs change their systems to achieve high performance. Through implementation of the LOCK bundle of practices, CLC staff develop, pilot, and spread new systems for communication, teamwork, and collaborative problem solving, as well as developing skills to participate effectively in these systems. CONCERT represents just 1 way VA supports CLCs in their continual journeys toward ever-improved quality of veteran care.

Acknowledgments
The authors thank Barbara Frank and Cathie Brady for their contributions to the development of the CONCERT program.

References

1. US Department of Veterans Affairs, Geriatrics and Extended Care Services (GEC). https://www.va.gov/GERIATRICS/index.asp. Updated February 25, 2019. Accessed April 9, 2019.

2. US Department of Veterans Affairs. https://www.accesstocare.va.gov/CNH/Statemap. Accessed April 10, 2019.

3. US Department of Veterans Affairs. https://www.va.gov/QUALITYOFCARE/apps/aspire/clcsurvey.aspx/. Updated September 21, 2015. Accessed April 10, 2019.

4. Gittell JH, Weinberg D, Pfefferle S, Bishop C. Impact of relational coordination on job satisfaction and quality outcomes: a study of nursing homes. Hum Resour Manag. 2008;18(2):154-170

5. Snow AL, Dodson, ML, Palmer JA, et al. Development of a new systematic observation tool of nursing home resident and staff engagement and relationship. Gerontologist. 2018;58(2):e15-e24.

6. Hartmann CW, Palmer JA, Mills WL, et al. Adaptation of a nursing home culture change research instrument for frontline staff quality improvement use. Psychol Serv. 2017;14(3):337-346.

7. Mills WL, Pimentel CB, Palmer JA, et al. Applying a theory-driven framework to guide quality improvement efforts in nursing homes: the LOCK model. Gerontologist. 2018;58(3):598-605.

8. Caravon P, Hundt AS, Karsh B, et al. Work system design for patient safety: the SEIPS model. Quality & Safety in Health Care. 2006;15(suppl 1), i50-i58.

9. Yanes AF, McElroy LM, Abecassis ZA, Holl J, Woods D, Ladner DP. Observation for assessment of clinician performance: a narrative review. BMJ Qual Saf. 2016;25(1):46-55.

10. Gittell JH. Supervisory span, relational coordination and flight departure performance: a reassessment of postbureaucracy theory. Organ Sci. 2011;12(4):468-483.

11. Gittell JH. New Directions for Relational Coordination Theory. In Spreitzer GM, Cameron KS, eds. The Oxford Handbook of Positive Organizational Scholarship. Oxford University Press: New York; 2012:400-411.

12. Weinberg DB, Lusenhop RW, Gittell JH, Kautz CM. Coordination between formal providers and informal caregivers. Health Care Manage Rev. 2007;32(2):140-149.

13. Phillips J, Hebish LJ, Mann S, Ching JM, Blackmore CC. Engaging frontline leaders and staff in real-time improvement. Jt Comm J Qual Patient Saf. 2016;42(4):170-183.

14. Farrell D, Brady C, Frank B. Meeting the Leadership Challenge in Long-Term Care: What You Do Matters. Health Professions Press: Baltimore, MD; 2011.

15. Brady C, Farrell D, Frank B. A Long-Term Leaders’ Guide to High Performance: Doing Better Together. Health Professions Press: Baltimore, MD; 2018.

16. Bradley EH, Curry LA, Ramanadhan S, Rowe L, Nembhard IM, Krumholz HM. Research in action: using positive deviance to improve quality of health care. Implement Sci. 2009;4:25.

17. Marsh DR, Schroeder DG, Dearden KA, Sternin J, Sternin M. The power of positive deviance. BMJ. 2004; 329(7475):1177-1179.

18. Vogt K, Johnson F, Fraser V, et al. An innovative, strengths-based, peer mentoring approach to professional development for registered dietitians. Can J Diet Pract Res. 2015;76(4):185-189.

19. Beckett P, Field J, Molloy L, Yu N, Holmes D, Pile E. Practice what you preach: developing person-centered culture in inpatient mental health settings through strengths-based, transformational leadership. Issues Ment Health Nurs. 2013;34(8):595-601.

20. Hartmann CW, Mills WL, Pimentel CB, et al. Impact of intervention to improve nursing home resident-staff interactions and engagement. Gerontologist. 2018;58(4):e291-e301.

21. Institute for Healthcare Improvement. The breakthrough series: IHI’s collaborative model for achieving breakthrough improvement. http://www.ihi.org/resources/Pages/IHIWhitePapers/TheBreakthroughSeriesIHIsCollaborativeModelforAchievingBreakthroughImprovement.aspx. Published 2003. Accessed April 9, 2019.

References

1. US Department of Veterans Affairs, Geriatrics and Extended Care Services (GEC). https://www.va.gov/GERIATRICS/index.asp. Updated February 25, 2019. Accessed April 9, 2019.

2. US Department of Veterans Affairs. https://www.accesstocare.va.gov/CNH/Statemap. Accessed April 10, 2019.

3. US Department of Veterans Affairs. https://www.va.gov/QUALITYOFCARE/apps/aspire/clcsurvey.aspx/. Updated September 21, 2015. Accessed April 10, 2019.

4. Gittell JH, Weinberg D, Pfefferle S, Bishop C. Impact of relational coordination on job satisfaction and quality outcomes: a study of nursing homes. Hum Resour Manag. 2008;18(2):154-170

5. Snow AL, Dodson, ML, Palmer JA, et al. Development of a new systematic observation tool of nursing home resident and staff engagement and relationship. Gerontologist. 2018;58(2):e15-e24.

6. Hartmann CW, Palmer JA, Mills WL, et al. Adaptation of a nursing home culture change research instrument for frontline staff quality improvement use. Psychol Serv. 2017;14(3):337-346.

7. Mills WL, Pimentel CB, Palmer JA, et al. Applying a theory-driven framework to guide quality improvement efforts in nursing homes: the LOCK model. Gerontologist. 2018;58(3):598-605.

8. Caravon P, Hundt AS, Karsh B, et al. Work system design for patient safety: the SEIPS model. Quality & Safety in Health Care. 2006;15(suppl 1), i50-i58.

9. Yanes AF, McElroy LM, Abecassis ZA, Holl J, Woods D, Ladner DP. Observation for assessment of clinician performance: a narrative review. BMJ Qual Saf. 2016;25(1):46-55.

10. Gittell JH. Supervisory span, relational coordination and flight departure performance: a reassessment of postbureaucracy theory. Organ Sci. 2011;12(4):468-483.

11. Gittell JH. New Directions for Relational Coordination Theory. In Spreitzer GM, Cameron KS, eds. The Oxford Handbook of Positive Organizational Scholarship. Oxford University Press: New York; 2012:400-411.

12. Weinberg DB, Lusenhop RW, Gittell JH, Kautz CM. Coordination between formal providers and informal caregivers. Health Care Manage Rev. 2007;32(2):140-149.

13. Phillips J, Hebish LJ, Mann S, Ching JM, Blackmore CC. Engaging frontline leaders and staff in real-time improvement. Jt Comm J Qual Patient Saf. 2016;42(4):170-183.

14. Farrell D, Brady C, Frank B. Meeting the Leadership Challenge in Long-Term Care: What You Do Matters. Health Professions Press: Baltimore, MD; 2011.

15. Brady C, Farrell D, Frank B. A Long-Term Leaders’ Guide to High Performance: Doing Better Together. Health Professions Press: Baltimore, MD; 2018.

16. Bradley EH, Curry LA, Ramanadhan S, Rowe L, Nembhard IM, Krumholz HM. Research in action: using positive deviance to improve quality of health care. Implement Sci. 2009;4:25.

17. Marsh DR, Schroeder DG, Dearden KA, Sternin J, Sternin M. The power of positive deviance. BMJ. 2004; 329(7475):1177-1179.

18. Vogt K, Johnson F, Fraser V, et al. An innovative, strengths-based, peer mentoring approach to professional development for registered dietitians. Can J Diet Pract Res. 2015;76(4):185-189.

19. Beckett P, Field J, Molloy L, Yu N, Holmes D, Pile E. Practice what you preach: developing person-centered culture in inpatient mental health settings through strengths-based, transformational leadership. Issues Ment Health Nurs. 2013;34(8):595-601.

20. Hartmann CW, Mills WL, Pimentel CB, et al. Impact of intervention to improve nursing home resident-staff interactions and engagement. Gerontologist. 2018;58(4):e291-e301.

21. Institute for Healthcare Improvement. The breakthrough series: IHI’s collaborative model for achieving breakthrough improvement. http://www.ihi.org/resources/Pages/IHIWhitePapers/TheBreakthroughSeriesIHIsCollaborativeModelforAchievingBreakthroughImprovement.aspx. Published 2003. Accessed April 9, 2019.

Issue
Federal Practitioner - 36(5)a
Issue
Federal Practitioner - 36(5)a
Page Number
228-231
Page Number
228-231
Publications
Publications
Topics
Article Type
Sections
Disallow All Ads
Content Gating
No Gating (article Unlocked/Free)
Alternative CME
Disqus Comments
Default
Eyebrow Default
PROGRAM PROFILE
Use ProPublica
Hide sidebar & use full width
render the right sidebar.
Article PDF Media

Infection or not infection, that is the question—Is procalcitonin the answer?

Article Type
Changed
Wed, 05/01/2019 - 07:57
Display Headline
Infection or not infection, that is the question—Is procalcitonin the answer?

Two ongoing challenges in managing patients with a potential or real infection are how to distinguish early on between bacterial infection and sterile inflammation or sepsis syndrome and how to determine the optimal duration of antibiotic therapy. Both have implications for the patient—ie, starting appropriate antibiotic or alternative therapy early and avoiding adverse effects of unnecessarily prolonged antibiotic use—but also for society, particularly by limiting unnecessary antibiotic use, which contributes to the worldwide problem of antibiotic resistance.

Diagnostic algorithms have been proposed to help recognize infection in chronic obstructive pulmonary disease, rhinosinusitis syndrome, acute arthritis, pharyngitis, and possible sepsis. The algorithms have included laboratory tests and potential biomarkers, but all are imperfect despite achieving various degrees of acceptance in practice.

In this issue of the Journal, Dr. Fakheri updates us on using the data on serum procalcitonin levels to guide starting and stopping antibiotics in different clinical scenarios. As I read the paper, I wondered what was different about procalcitonin that might allow it to succeed where seemingly similar biomarkers like C-reactive protein (CRP) and the erythrocyte sedimentation rate (ESR) have failed.

Procalcitonin is the approximately 15,000-kD product of the CALC1 gene and the precursor of calcitonin. Not surprisingly, then, it is increased in patients with thyroid medullary carcinoma, and it is also often elevated in nonthyroid neuroendocrine malignancies. Proteolytic cleavage of procalcitonin to active calcitonin takes place mainly or only in the thyroid, and under normal homeostatic conditions, procalcitonin is almost unmeasurable in the circulation. However, under major stress such as systemic inflammation, sepsis, or burns, the CALC1 gene is activated in parenchymal cells in many organs, and procalcitonin is synthesized and released. Notably, under these conditions, the procalcitonin does not seem to be of thyroid origin; hence, calcitonin levels do not rise markedly. The physiologic role of nonthyroidal procalcitonin is unknown.

Procalcitonin synthesis and secretion is turned on in nonthyroid tissue by multiple cytokines; the cytokines most likely relevant to its association with inflammation and infections are interleukin (IL) 1 beta, tumor necrosis factor (TNF) alpha, and IL-6. Since these same mediators drive the acute-phase response and elicit the increase in circulating CRP and fibrinogen (the major contributor to the ESR), the obvious question is why procalcitonin might be a more reliable biomarker to distinguish bacterial infection from inflammation or a viral infection than the CRP level or ESR. And although it does indeed seem to do so in several conditions, as Dr. Fakheri discusses, the explanation is not obvious. But it is intriguing to hypothesize.

Induction of procalcitonin by endotoxin-stimulated cytokines is rapid and seems to be slightly faster than that of CRP, although there may be issues of assay sensitivity. The half-life of procalcitonin is similar to that of CRP (about 24 hours). Its degradation does not seem to be altered in renal insufficiency, and its synthesis seems to rapidly shut off as the cytokine level drops. But interestingly, and perhaps relevant to its possible unique biomarker behavior, its synthesis seems to depend on factors other than the increase in inflammatory cytokines such as IL-6. Under certain circumstances, in the same patient, there is a discrepancy between the levels of procalcitonin and CRP.

In a small study of patients with pulmonary embolism and fever, IL-6 levels increased in many with an expected accompanying increase in CRP and ESR, but procalcitonin did not markedly rise,1 although all 3 markers rose as expected in patients with bacterial pneumonia.

Even more provocative is another study in 69 patients with systemic lupus erythematosus and bacterial infection (43 patients had sepsis, 11 of whom died). The CRP level rose dramatically in the infected patients, but procalcitonin did not.2

The intriguing aspect of this, assuming it holds true in other studies, is that interferon activity is high in lupus and many viral infections, and if interferon can suppress CALC1 gene activation3 but leave CRP activation unaffected, this may provide a clue as to why CRP but not procalcitonin is elevated in serious viral infections, thus allowing procalcitonin to more effectively distinguish bacterial from viral and other nonbacterial inflammatory responses.

The two studies I mention are small, some conflicting results have been published, and the results cannot yet be generalized. Plus, it has long been recognized there is sometimes discordance in a given patient between the elevation in ESR and CRP, not readily explained by the presence of a paraprotein, rheologic factors, or the different time course of decay in the ESR and CRP response. Whatever the explanation, procalcitonin’s biology is interesting, and clinical study results show promise. While tracking procalcitonin levels is not uniformly useful (eg, there is no convincing value in using procalcitonin in the diagnosis of prosthetic joint infections), there is accumulating evidence that it can guide us to using shorter but still effective courses of antibiotics in several clinical scenarios. Hopefully, more frequent use of the test will make a dent in our apparent excess use of antibiotics in patients with nonbacterial upper-respiratory infections.

References
  1. Köktürk N, Kanbay A, Bukan N, Ekim N. The value of serum procalcitonin in differential diagnosis of pulmonary embolism and community acquired pneumonia. Clin App Thromb Hemostasis 2011; 17(5):519–525. doi:10.1177/1076029610375425
  2. El-Serougy E, Zayed HS, Ibrahim NM, Maged LA. Procalcitonin and C-reactive protein as markers of infection in systemic lupus erythematosus: the controversy continues. Lupus 2018 Jan 1:961203318777101. doi:10.1177/0961203318777101 (e-pub ahead of print)
  3. Linscheid P, Seboek D, Nylen ES, et al. In vitro and in vivo calcitonin I gene expression in parenchymal cells: a novel product of human adipose tissue. Endocrinology 2003; 144(12): 5578–5584. doi:10.1210/en.2003-0854
Article PDF
Author and Disclosure Information
Issue
Cleveland Clinic Journal of Medicine - 86(5)
Publications
Topics
Page Number
297-298
Legacy Keywords
procalcitonin, infection, antibiotic therapy, C-reactive protein CRP, erythrocyte sedimentation rate, ESR, Brian Mandell
Sections
Author and Disclosure Information
Author and Disclosure Information
Article PDF
Article PDF
Related Articles

Two ongoing challenges in managing patients with a potential or real infection are how to distinguish early on between bacterial infection and sterile inflammation or sepsis syndrome and how to determine the optimal duration of antibiotic therapy. Both have implications for the patient—ie, starting appropriate antibiotic or alternative therapy early and avoiding adverse effects of unnecessarily prolonged antibiotic use—but also for society, particularly by limiting unnecessary antibiotic use, which contributes to the worldwide problem of antibiotic resistance.

Diagnostic algorithms have been proposed to help recognize infection in chronic obstructive pulmonary disease, rhinosinusitis syndrome, acute arthritis, pharyngitis, and possible sepsis. The algorithms have included laboratory tests and potential biomarkers, but all are imperfect despite achieving various degrees of acceptance in practice.

In this issue of the Journal, Dr. Fakheri updates us on using the data on serum procalcitonin levels to guide starting and stopping antibiotics in different clinical scenarios. As I read the paper, I wondered what was different about procalcitonin that might allow it to succeed where seemingly similar biomarkers like C-reactive protein (CRP) and the erythrocyte sedimentation rate (ESR) have failed.

Procalcitonin is the approximately 15,000-kD product of the CALC1 gene and the precursor of calcitonin. Not surprisingly, then, it is increased in patients with thyroid medullary carcinoma, and it is also often elevated in nonthyroid neuroendocrine malignancies. Proteolytic cleavage of procalcitonin to active calcitonin takes place mainly or only in the thyroid, and under normal homeostatic conditions, procalcitonin is almost unmeasurable in the circulation. However, under major stress such as systemic inflammation, sepsis, or burns, the CALC1 gene is activated in parenchymal cells in many organs, and procalcitonin is synthesized and released. Notably, under these conditions, the procalcitonin does not seem to be of thyroid origin; hence, calcitonin levels do not rise markedly. The physiologic role of nonthyroidal procalcitonin is unknown.

Procalcitonin synthesis and secretion is turned on in nonthyroid tissue by multiple cytokines; the cytokines most likely relevant to its association with inflammation and infections are interleukin (IL) 1 beta, tumor necrosis factor (TNF) alpha, and IL-6. Since these same mediators drive the acute-phase response and elicit the increase in circulating CRP and fibrinogen (the major contributor to the ESR), the obvious question is why procalcitonin might be a more reliable biomarker to distinguish bacterial infection from inflammation or a viral infection than the CRP level or ESR. And although it does indeed seem to do so in several conditions, as Dr. Fakheri discusses, the explanation is not obvious. But it is intriguing to hypothesize.

Induction of procalcitonin by endotoxin-stimulated cytokines is rapid and seems to be slightly faster than that of CRP, although there may be issues of assay sensitivity. The half-life of procalcitonin is similar to that of CRP (about 24 hours). Its degradation does not seem to be altered in renal insufficiency, and its synthesis seems to rapidly shut off as the cytokine level drops. But interestingly, and perhaps relevant to its possible unique biomarker behavior, its synthesis seems to depend on factors other than the increase in inflammatory cytokines such as IL-6. Under certain circumstances, in the same patient, there is a discrepancy between the levels of procalcitonin and CRP.

In a small study of patients with pulmonary embolism and fever, IL-6 levels increased in many with an expected accompanying increase in CRP and ESR, but procalcitonin did not markedly rise,1 although all 3 markers rose as expected in patients with bacterial pneumonia.

Even more provocative is another study in 69 patients with systemic lupus erythematosus and bacterial infection (43 patients had sepsis, 11 of whom died). The CRP level rose dramatically in the infected patients, but procalcitonin did not.2

The intriguing aspect of this, assuming it holds true in other studies, is that interferon activity is high in lupus and many viral infections, and if interferon can suppress CALC1 gene activation3 but leave CRP activation unaffected, this may provide a clue as to why CRP but not procalcitonin is elevated in serious viral infections, thus allowing procalcitonin to more effectively distinguish bacterial from viral and other nonbacterial inflammatory responses.

The two studies I mention are small, some conflicting results have been published, and the results cannot yet be generalized. Plus, it has long been recognized there is sometimes discordance in a given patient between the elevation in ESR and CRP, not readily explained by the presence of a paraprotein, rheologic factors, or the different time course of decay in the ESR and CRP response. Whatever the explanation, procalcitonin’s biology is interesting, and clinical study results show promise. While tracking procalcitonin levels is not uniformly useful (eg, there is no convincing value in using procalcitonin in the diagnosis of prosthetic joint infections), there is accumulating evidence that it can guide us to using shorter but still effective courses of antibiotics in several clinical scenarios. Hopefully, more frequent use of the test will make a dent in our apparent excess use of antibiotics in patients with nonbacterial upper-respiratory infections.

Two ongoing challenges in managing patients with a potential or real infection are how to distinguish early on between bacterial infection and sterile inflammation or sepsis syndrome and how to determine the optimal duration of antibiotic therapy. Both have implications for the patient—ie, starting appropriate antibiotic or alternative therapy early and avoiding adverse effects of unnecessarily prolonged antibiotic use—but also for society, particularly by limiting unnecessary antibiotic use, which contributes to the worldwide problem of antibiotic resistance.

Diagnostic algorithms have been proposed to help recognize infection in chronic obstructive pulmonary disease, rhinosinusitis syndrome, acute arthritis, pharyngitis, and possible sepsis. The algorithms have included laboratory tests and potential biomarkers, but all are imperfect despite achieving various degrees of acceptance in practice.

In this issue of the Journal, Dr. Fakheri updates us on using the data on serum procalcitonin levels to guide starting and stopping antibiotics in different clinical scenarios. As I read the paper, I wondered what was different about procalcitonin that might allow it to succeed where seemingly similar biomarkers like C-reactive protein (CRP) and the erythrocyte sedimentation rate (ESR) have failed.

Procalcitonin is the approximately 15,000-kD product of the CALC1 gene and the precursor of calcitonin. Not surprisingly, then, it is increased in patients with thyroid medullary carcinoma, and it is also often elevated in nonthyroid neuroendocrine malignancies. Proteolytic cleavage of procalcitonin to active calcitonin takes place mainly or only in the thyroid, and under normal homeostatic conditions, procalcitonin is almost unmeasurable in the circulation. However, under major stress such as systemic inflammation, sepsis, or burns, the CALC1 gene is activated in parenchymal cells in many organs, and procalcitonin is synthesized and released. Notably, under these conditions, the procalcitonin does not seem to be of thyroid origin; hence, calcitonin levels do not rise markedly. The physiologic role of nonthyroidal procalcitonin is unknown.

Procalcitonin synthesis and secretion is turned on in nonthyroid tissue by multiple cytokines; the cytokines most likely relevant to its association with inflammation and infections are interleukin (IL) 1 beta, tumor necrosis factor (TNF) alpha, and IL-6. Since these same mediators drive the acute-phase response and elicit the increase in circulating CRP and fibrinogen (the major contributor to the ESR), the obvious question is why procalcitonin might be a more reliable biomarker to distinguish bacterial infection from inflammation or a viral infection than the CRP level or ESR. And although it does indeed seem to do so in several conditions, as Dr. Fakheri discusses, the explanation is not obvious. But it is intriguing to hypothesize.

Induction of procalcitonin by endotoxin-stimulated cytokines is rapid and seems to be slightly faster than that of CRP, although there may be issues of assay sensitivity. The half-life of procalcitonin is similar to that of CRP (about 24 hours). Its degradation does not seem to be altered in renal insufficiency, and its synthesis seems to rapidly shut off as the cytokine level drops. But interestingly, and perhaps relevant to its possible unique biomarker behavior, its synthesis seems to depend on factors other than the increase in inflammatory cytokines such as IL-6. Under certain circumstances, in the same patient, there is a discrepancy between the levels of procalcitonin and CRP.

In a small study of patients with pulmonary embolism and fever, IL-6 levels increased in many with an expected accompanying increase in CRP and ESR, but procalcitonin did not markedly rise,1 although all 3 markers rose as expected in patients with bacterial pneumonia.

Even more provocative is another study in 69 patients with systemic lupus erythematosus and bacterial infection (43 patients had sepsis, 11 of whom died). The CRP level rose dramatically in the infected patients, but procalcitonin did not.2

The intriguing aspect of this, assuming it holds true in other studies, is that interferon activity is high in lupus and many viral infections, and if interferon can suppress CALC1 gene activation3 but leave CRP activation unaffected, this may provide a clue as to why CRP but not procalcitonin is elevated in serious viral infections, thus allowing procalcitonin to more effectively distinguish bacterial from viral and other nonbacterial inflammatory responses.

The two studies I mention are small, some conflicting results have been published, and the results cannot yet be generalized. Plus, it has long been recognized there is sometimes discordance in a given patient between the elevation in ESR and CRP, not readily explained by the presence of a paraprotein, rheologic factors, or the different time course of decay in the ESR and CRP response. Whatever the explanation, procalcitonin’s biology is interesting, and clinical study results show promise. While tracking procalcitonin levels is not uniformly useful (eg, there is no convincing value in using procalcitonin in the diagnosis of prosthetic joint infections), there is accumulating evidence that it can guide us to using shorter but still effective courses of antibiotics in several clinical scenarios. Hopefully, more frequent use of the test will make a dent in our apparent excess use of antibiotics in patients with nonbacterial upper-respiratory infections.

References
  1. Köktürk N, Kanbay A, Bukan N, Ekim N. The value of serum procalcitonin in differential diagnosis of pulmonary embolism and community acquired pneumonia. Clin App Thromb Hemostasis 2011; 17(5):519–525. doi:10.1177/1076029610375425
  2. El-Serougy E, Zayed HS, Ibrahim NM, Maged LA. Procalcitonin and C-reactive protein as markers of infection in systemic lupus erythematosus: the controversy continues. Lupus 2018 Jan 1:961203318777101. doi:10.1177/0961203318777101 (e-pub ahead of print)
  3. Linscheid P, Seboek D, Nylen ES, et al. In vitro and in vivo calcitonin I gene expression in parenchymal cells: a novel product of human adipose tissue. Endocrinology 2003; 144(12): 5578–5584. doi:10.1210/en.2003-0854
References
  1. Köktürk N, Kanbay A, Bukan N, Ekim N. The value of serum procalcitonin in differential diagnosis of pulmonary embolism and community acquired pneumonia. Clin App Thromb Hemostasis 2011; 17(5):519–525. doi:10.1177/1076029610375425
  2. El-Serougy E, Zayed HS, Ibrahim NM, Maged LA. Procalcitonin and C-reactive protein as markers of infection in systemic lupus erythematosus: the controversy continues. Lupus 2018 Jan 1:961203318777101. doi:10.1177/0961203318777101 (e-pub ahead of print)
  3. Linscheid P, Seboek D, Nylen ES, et al. In vitro and in vivo calcitonin I gene expression in parenchymal cells: a novel product of human adipose tissue. Endocrinology 2003; 144(12): 5578–5584. doi:10.1210/en.2003-0854
Issue
Cleveland Clinic Journal of Medicine - 86(5)
Issue
Cleveland Clinic Journal of Medicine - 86(5)
Page Number
297-298
Page Number
297-298
Publications
Publications
Topics
Article Type
Display Headline
Infection or not infection, that is the question—Is procalcitonin the answer?
Display Headline
Infection or not infection, that is the question—Is procalcitonin the answer?
Legacy Keywords
procalcitonin, infection, antibiotic therapy, C-reactive protein CRP, erythrocyte sedimentation rate, ESR, Brian Mandell
Legacy Keywords
procalcitonin, infection, antibiotic therapy, C-reactive protein CRP, erythrocyte sedimentation rate, ESR, Brian Mandell
Sections
Disallow All Ads
Content Gating
No Gating (article Unlocked/Free)
Alternative CME
Disqus Comments
Default
Gate On Date
Wed, 04/24/2019 - 07:45
Un-Gate On Date
Wed, 04/24/2019 - 07:45
Use ProPublica
CFC Schedule Remove Status
Wed, 04/24/2019 - 07:45
Hide sidebar & use full width
render the right sidebar.
Article PDF Media

Leadership and Professional Development: The Healing Power of Laughter

Article Type
Changed
Tue, 06/11/2019 - 10:06

“The most radical act anyone can commit is to be happy.”
—Patch Adams

Patch Adams understood that laughter was important not only in healing, but also for filling the souls of those who care for patients. Each of us has a well within us, full of compassion, caring, and healing. Yet we daily face fear, pain, frustration, exhaustion, grief, and loss. All of these can deplete us while our patients are expecting more. There is perhaps no quicker way to replenish our wells than by the simple act of laughing.

As we take on the responsibilities of the world, many of us come to believe that laughter is something only children do. Research shows that children laugh about 400 times a day, but adults on average laugh only about 15 times. Especially in a healthcare environment plagued by burnout, we tend to become serious and don a stoic professional face. Some of us even believe that laughing makes us less professional.

As already mentioned, laughter brings physiological benefits to the body. It lessens people’s pain, so if anything, we need to be spreading more healing laughter in all of our interactions. It is like a bee pollinating flowers and bringing them to life. But how can you as a busy hospitalist do this? Here are five ways to bring smiles and giggles to the health care:

  • Smile. Smiling is contagious. So called “mirror neurons” (important in early human development) allow babies to mimic facial and emotional responses and fire in response to sensory input. Have you ever noticed when someone yawns, others in a room will yawn as well? Those are mirror neurons at work. Smiling and laughter activate mirror neurons in the brain of primates and humans.1 This is why sitcoms often include laugh tracks—hearing the laughter makes us laugh. So laugh and watch: others will join you.
  • Have some jokes ready. According to research those who can tell a good joke are viewed as more competent. Some data even suggests that employees with a good sense of humor are more likely to get a raise or promotion.2 However, humor can be tricky, as it is subjective. So, keep your jokes simple, nonoffensive, and short. Remember to know and read your audience.
  • Plan silly times. Theme days replete with outfits or with sundries that may reflect your patients tastes or those of your inpatient teams can add smiles and joy while breaking a dismal routine.
  • Be a good sport. Self-deprecation can be a way not only to bring a smile or two, but can help diffuse a tense situation. Being a good sport not only helps people spread joy to others but is a good way to be seen in a positive light by employers.
  • Celebrate success and fun. Encourage smiling, pleasure, and laughing. When managers and administrators look like they are enjoying themselves, they set the company culture that it is a fun place to work.
 

 

Laughter is the best medicine. It not only heals others, but also helps lighten our daily loads, and brings a smile to our face and everyone we meet. Consider trying this opportunity to bring you and those around you a world of good.

Disclosures

The author has nothing to disclose.

 

References

1. Rizzolatti G, Craighero, L. The mirror-neuron system. Annu Rev Neurosci . 2004;27(1):169–192. doi:10.1146/annurev.neuro.27.070203.144230. PubMed
2. Kristof-Brown AL. (2000). Perceived applicant fit: Distinguishing between recruiters’ perceptions of person–job and person–organization fit.
Personnel Psychol . 2000;53:643-671. 

Article PDF
Issue
Journal of Hospital Medicine 14(5)
Topics
Page Number
320
Sections
Article PDF
Article PDF

“The most radical act anyone can commit is to be happy.”
—Patch Adams

Patch Adams understood that laughter was important not only in healing, but also for filling the souls of those who care for patients. Each of us has a well within us, full of compassion, caring, and healing. Yet we daily face fear, pain, frustration, exhaustion, grief, and loss. All of these can deplete us while our patients are expecting more. There is perhaps no quicker way to replenish our wells than by the simple act of laughing.

As we take on the responsibilities of the world, many of us come to believe that laughter is something only children do. Research shows that children laugh about 400 times a day, but adults on average laugh only about 15 times. Especially in a healthcare environment plagued by burnout, we tend to become serious and don a stoic professional face. Some of us even believe that laughing makes us less professional.

As already mentioned, laughter brings physiological benefits to the body. It lessens people’s pain, so if anything, we need to be spreading more healing laughter in all of our interactions. It is like a bee pollinating flowers and bringing them to life. But how can you as a busy hospitalist do this? Here are five ways to bring smiles and giggles to the health care:

  • Smile. Smiling is contagious. So called “mirror neurons” (important in early human development) allow babies to mimic facial and emotional responses and fire in response to sensory input. Have you ever noticed when someone yawns, others in a room will yawn as well? Those are mirror neurons at work. Smiling and laughter activate mirror neurons in the brain of primates and humans.1 This is why sitcoms often include laugh tracks—hearing the laughter makes us laugh. So laugh and watch: others will join you.
  • Have some jokes ready. According to research those who can tell a good joke are viewed as more competent. Some data even suggests that employees with a good sense of humor are more likely to get a raise or promotion.2 However, humor can be tricky, as it is subjective. So, keep your jokes simple, nonoffensive, and short. Remember to know and read your audience.
  • Plan silly times. Theme days replete with outfits or with sundries that may reflect your patients tastes or those of your inpatient teams can add smiles and joy while breaking a dismal routine.
  • Be a good sport. Self-deprecation can be a way not only to bring a smile or two, but can help diffuse a tense situation. Being a good sport not only helps people spread joy to others but is a good way to be seen in a positive light by employers.
  • Celebrate success and fun. Encourage smiling, pleasure, and laughing. When managers and administrators look like they are enjoying themselves, they set the company culture that it is a fun place to work.
 

 

Laughter is the best medicine. It not only heals others, but also helps lighten our daily loads, and brings a smile to our face and everyone we meet. Consider trying this opportunity to bring you and those around you a world of good.

Disclosures

The author has nothing to disclose.

 

“The most radical act anyone can commit is to be happy.”
—Patch Adams

Patch Adams understood that laughter was important not only in healing, but also for filling the souls of those who care for patients. Each of us has a well within us, full of compassion, caring, and healing. Yet we daily face fear, pain, frustration, exhaustion, grief, and loss. All of these can deplete us while our patients are expecting more. There is perhaps no quicker way to replenish our wells than by the simple act of laughing.

As we take on the responsibilities of the world, many of us come to believe that laughter is something only children do. Research shows that children laugh about 400 times a day, but adults on average laugh only about 15 times. Especially in a healthcare environment plagued by burnout, we tend to become serious and don a stoic professional face. Some of us even believe that laughing makes us less professional.

As already mentioned, laughter brings physiological benefits to the body. It lessens people’s pain, so if anything, we need to be spreading more healing laughter in all of our interactions. It is like a bee pollinating flowers and bringing them to life. But how can you as a busy hospitalist do this? Here are five ways to bring smiles and giggles to the health care:

  • Smile. Smiling is contagious. So called “mirror neurons” (important in early human development) allow babies to mimic facial and emotional responses and fire in response to sensory input. Have you ever noticed when someone yawns, others in a room will yawn as well? Those are mirror neurons at work. Smiling and laughter activate mirror neurons in the brain of primates and humans.1 This is why sitcoms often include laugh tracks—hearing the laughter makes us laugh. So laugh and watch: others will join you.
  • Have some jokes ready. According to research those who can tell a good joke are viewed as more competent. Some data even suggests that employees with a good sense of humor are more likely to get a raise or promotion.2 However, humor can be tricky, as it is subjective. So, keep your jokes simple, nonoffensive, and short. Remember to know and read your audience.
  • Plan silly times. Theme days replete with outfits or with sundries that may reflect your patients tastes or those of your inpatient teams can add smiles and joy while breaking a dismal routine.
  • Be a good sport. Self-deprecation can be a way not only to bring a smile or two, but can help diffuse a tense situation. Being a good sport not only helps people spread joy to others but is a good way to be seen in a positive light by employers.
  • Celebrate success and fun. Encourage smiling, pleasure, and laughing. When managers and administrators look like they are enjoying themselves, they set the company culture that it is a fun place to work.
 

 

Laughter is the best medicine. It not only heals others, but also helps lighten our daily loads, and brings a smile to our face and everyone we meet. Consider trying this opportunity to bring you and those around you a world of good.

Disclosures

The author has nothing to disclose.

 

References

1. Rizzolatti G, Craighero, L. The mirror-neuron system. Annu Rev Neurosci . 2004;27(1):169–192. doi:10.1146/annurev.neuro.27.070203.144230. PubMed
2. Kristof-Brown AL. (2000). Perceived applicant fit: Distinguishing between recruiters’ perceptions of person–job and person–organization fit.
Personnel Psychol . 2000;53:643-671. 

References

1. Rizzolatti G, Craighero, L. The mirror-neuron system. Annu Rev Neurosci . 2004;27(1):169–192. doi:10.1146/annurev.neuro.27.070203.144230. PubMed
2. Kristof-Brown AL. (2000). Perceived applicant fit: Distinguishing between recruiters’ perceptions of person–job and person–organization fit.
Personnel Psychol . 2000;53:643-671. 

Issue
Journal of Hospital Medicine 14(5)
Issue
Journal of Hospital Medicine 14(5)
Page Number
320
Page Number
320
Topics
Article Type
Sections
Article Source

© 2019 Society of Hospital Medicine

Disallow All Ads
Correspondence Location
Corresponding Author: Betty-Ann Heggie, B.Ed.; E-mail; [email protected].
Content Gating
Open Access (article Unlocked/Open Access)
Alternative CME
Disqus Comments
Default
Use ProPublica
Hide sidebar & use full width
render the right sidebar.
Article PDF Media

Electronic health records linked to lower patient safety

Article Type
Changed
Fri, 04/26/2019 - 14:34

Higher reliance on electronic health records (EHRs) in ambulatory oncology practice was significantly associated with reduced safety actions among oncology nurses and prescribers, according to results of a statewide survey.

“The purpose of this study was to investigate the degree to which EHRs, satisfaction with technology, and clinician communication enable a safety culture in ambulatory oncology treatment settings,” wrote Minal R. Patel, PhD, MPH, of the University of Michigan, Ann Arbor, and colleagues. The report is published in the Journal of Oncology Practice.

The researchers conducted a statewide survey of 297 oncology nurses and prescribers in 29 ambulatory oncology practices in Michigan. They obtained quantitative data for May to October 2017 from clinician surveys and practice logs at these clinical sites.

The study methodology was built by use of the sociotechnical framework, which examined how EHR technologies influenced the safe administration of chemotherapy.

Eligible survey participants included physicians, nurses, physician assistants, and nurse practitioners who cared for adult patients receiving infusion treatments for cancer.

A total of 438 clinicians were recruited and confirmed to be eligible, and 297 (68%) completed a survey.

After analysis, the researchers found that higher reliance on electronic health records in practice was associated with reduced safety scores (P less than .001). The mean safety score was reported to be 5.3 (standard deviation, 1.1; practice-level range, 4.9-5.4).

In an opposite manner, increased satisfaction with technology and better-quality communication were associated with higher safety actions.

The researchers acknowledged a key limitation of the study was cross-sectional design. As a result, confounding factors could influence the findings.

“Careful attention to technology adoption and updates coupled with high-quality communication skills across clinicians are promising strategies to administer high-risk treatments safely in ambulatory oncology settings,” they concluded.

The study was supported by grant funding from the Agency for Healthcare Research and Quality and the National Cancer Institute. No conflicts of interest were reported.

SOURCE: Patel MR et al. J Oncol Pract. 2019 Apr 22. doi: 10.1200/JOP.18.00507.

Publications
Topics
Sections

Higher reliance on electronic health records (EHRs) in ambulatory oncology practice was significantly associated with reduced safety actions among oncology nurses and prescribers, according to results of a statewide survey.

“The purpose of this study was to investigate the degree to which EHRs, satisfaction with technology, and clinician communication enable a safety culture in ambulatory oncology treatment settings,” wrote Minal R. Patel, PhD, MPH, of the University of Michigan, Ann Arbor, and colleagues. The report is published in the Journal of Oncology Practice.

The researchers conducted a statewide survey of 297 oncology nurses and prescribers in 29 ambulatory oncology practices in Michigan. They obtained quantitative data for May to October 2017 from clinician surveys and practice logs at these clinical sites.

The study methodology was built by use of the sociotechnical framework, which examined how EHR technologies influenced the safe administration of chemotherapy.

Eligible survey participants included physicians, nurses, physician assistants, and nurse practitioners who cared for adult patients receiving infusion treatments for cancer.

A total of 438 clinicians were recruited and confirmed to be eligible, and 297 (68%) completed a survey.

After analysis, the researchers found that higher reliance on electronic health records in practice was associated with reduced safety scores (P less than .001). The mean safety score was reported to be 5.3 (standard deviation, 1.1; practice-level range, 4.9-5.4).

In an opposite manner, increased satisfaction with technology and better-quality communication were associated with higher safety actions.

The researchers acknowledged a key limitation of the study was cross-sectional design. As a result, confounding factors could influence the findings.

“Careful attention to technology adoption and updates coupled with high-quality communication skills across clinicians are promising strategies to administer high-risk treatments safely in ambulatory oncology settings,” they concluded.

The study was supported by grant funding from the Agency for Healthcare Research and Quality and the National Cancer Institute. No conflicts of interest were reported.

SOURCE: Patel MR et al. J Oncol Pract. 2019 Apr 22. doi: 10.1200/JOP.18.00507.

Higher reliance on electronic health records (EHRs) in ambulatory oncology practice was significantly associated with reduced safety actions among oncology nurses and prescribers, according to results of a statewide survey.

“The purpose of this study was to investigate the degree to which EHRs, satisfaction with technology, and clinician communication enable a safety culture in ambulatory oncology treatment settings,” wrote Minal R. Patel, PhD, MPH, of the University of Michigan, Ann Arbor, and colleagues. The report is published in the Journal of Oncology Practice.

The researchers conducted a statewide survey of 297 oncology nurses and prescribers in 29 ambulatory oncology practices in Michigan. They obtained quantitative data for May to October 2017 from clinician surveys and practice logs at these clinical sites.

The study methodology was built by use of the sociotechnical framework, which examined how EHR technologies influenced the safe administration of chemotherapy.

Eligible survey participants included physicians, nurses, physician assistants, and nurse practitioners who cared for adult patients receiving infusion treatments for cancer.

A total of 438 clinicians were recruited and confirmed to be eligible, and 297 (68%) completed a survey.

After analysis, the researchers found that higher reliance on electronic health records in practice was associated with reduced safety scores (P less than .001). The mean safety score was reported to be 5.3 (standard deviation, 1.1; practice-level range, 4.9-5.4).

In an opposite manner, increased satisfaction with technology and better-quality communication were associated with higher safety actions.

The researchers acknowledged a key limitation of the study was cross-sectional design. As a result, confounding factors could influence the findings.

“Careful attention to technology adoption and updates coupled with high-quality communication skills across clinicians are promising strategies to administer high-risk treatments safely in ambulatory oncology settings,” they concluded.

The study was supported by grant funding from the Agency for Healthcare Research and Quality and the National Cancer Institute. No conflicts of interest were reported.

SOURCE: Patel MR et al. J Oncol Pract. 2019 Apr 22. doi: 10.1200/JOP.18.00507.

Publications
Publications
Topics
Article Type
Sections
Article Source

FROM JOURNAL OF ONCOLOGY PRACTICE

Disallow All Ads
Content Gating
No Gating (article Unlocked/Free)
Alternative CME
Disqus Comments
Default
Use ProPublica
Hide sidebar & use full width
render the right sidebar.

Focus on Science, Not Format: Introducing No Hassle Submissions to the Journal of Hospital Medicine

Article Type
Changed
Sat, 05/25/2019 - 23:59

The Journal of Hospital Medicine® is committed to continually improving the author experience. Our goal is to allow authors to focus more time on communicating their message and less time on navigating the submission and publication process. We commit to three initial areas of emphasis: (1) Make it easy for authors to submit their work; (2) Make timely disposition decisions; and (3) Facilitate dissemination of work that we publish.

We are pleased to introduce a new “No hassle” process for initial original research and brief report manuscript submissions. There is no universally followed format for manuscript submission to medical journals.1-3 As a result, authors spend considerable time reformatting manuscripts for submission to meet each journal’s unique requirements before knowing whether or not their manuscript will be accepted for publication—or even sent for peer review. To streamline the submission process and eliminate unnecessary and burdensome reformatting, we have eased formatting requirements for initial manuscript submissions. We will even accept all manuscript elements in a single PDF (portable document format) file in another journal’s format if your manuscript was submitted elsewhere first but not accepted for publication. Tables and figures can be included in the single document or uploaded separately, depending on your preference. Of course, common elements necessary to assess a manuscript, including declaration of funding sources and conflicts of interest, are required on the title page.1 Journal-specific formatting and signed disclosure and copyright forms will be deferred until a revision request.

We also seek to make timely decisions. Our rapid turnaround allows authors to submit elsewhere expeditiously if not accepted by the Journal of Hospital Medicine. We reject approximately 50% of original research and brief report manuscripts without formal peer review. The rationale for this approach is two-fold. We want to be respectful of how we engage our peer reviewers and we would rather not have them spend time reviewing manuscripts that we are unlikely to publish. We also want to be respectful of our authors’ time. If we are unlikely to publish a manuscript based on lower priority scores assigned by the Editor-in-Chief and other journal editors, we prefer to return the manuscript to authors for timely submission elsewhere. Our average time from submission to rejection without formal peer review is 1.3 days (median, <1 day). If we send a manuscript out for peer review, our time from submission to first decision is 23 days. Further, if we request a manuscript revision, we sincerely hope to publish the manuscript. Thus, most manuscripts for which we request a revision are ultimately accepted for publication. We are also tracking how quickly we can publish accepted manuscripts with a goal of 120 or fewer days from submission to publication and 60 or fewer days from acceptance to publication.

We highlight our published research in many ways to facilitate dissemination. We promote articles through formal press releases, tweets, visual abstracts, and, more recently, graphic medicine abstracts or comics. Select articles are discussed through our online journal club (#JHMChat).4 Other synergistic methods of dissemination are being planned and we’ll share these ideas with you in the coming year.

We are grateful to receive a large number of submissions and are honored that authors view the Journal of Hospital Medicine as an important venue to showcase their work. We continually strive to improve the author experience and welcome your input.

 

 

 

References

1. International Committee of Medical Journal Editors. Recommendations for the conduct, reporting, editing, and publication of scholarly work in medical journals. Updated December 2018. www.icmje.org/recommendations/browse/. Accessed April 2, 2019. PubMed
2. Schriger DL, Arora S, Altman DG. The content of medical journal instructions for authors. Ann Emerg Med. 2006;48(6):743-749. doi: 10.1016/j.annemergmed.2006.03.028 PubMed
3. Barron JP. The uniform requirements for manuscripts submitted to biomedical journals recommended by the International Committee of Medical Journal Editors. Chest. 2006;129(4):1098-1099. doi: 10.1378/chest.129.4.1098PubMed
4. Wray CM, Auerbach AD, Arora VM. The adoption of an online journal club to improve research dissemination and social media engagement among hospitalists. J Hosp Med. 2018;13(11):764-769. doi: 10.12788/jhm.2987. PubMed

Article PDF
Issue
Journal of Hospital Medicine 14(5)
Topics
Page Number
265. Published online first April 17, 2019.
Sections
Article PDF
Article PDF

The Journal of Hospital Medicine® is committed to continually improving the author experience. Our goal is to allow authors to focus more time on communicating their message and less time on navigating the submission and publication process. We commit to three initial areas of emphasis: (1) Make it easy for authors to submit their work; (2) Make timely disposition decisions; and (3) Facilitate dissemination of work that we publish.

We are pleased to introduce a new “No hassle” process for initial original research and brief report manuscript submissions. There is no universally followed format for manuscript submission to medical journals.1-3 As a result, authors spend considerable time reformatting manuscripts for submission to meet each journal’s unique requirements before knowing whether or not their manuscript will be accepted for publication—or even sent for peer review. To streamline the submission process and eliminate unnecessary and burdensome reformatting, we have eased formatting requirements for initial manuscript submissions. We will even accept all manuscript elements in a single PDF (portable document format) file in another journal’s format if your manuscript was submitted elsewhere first but not accepted for publication. Tables and figures can be included in the single document or uploaded separately, depending on your preference. Of course, common elements necessary to assess a manuscript, including declaration of funding sources and conflicts of interest, are required on the title page.1 Journal-specific formatting and signed disclosure and copyright forms will be deferred until a revision request.

We also seek to make timely decisions. Our rapid turnaround allows authors to submit elsewhere expeditiously if not accepted by the Journal of Hospital Medicine. We reject approximately 50% of original research and brief report manuscripts without formal peer review. The rationale for this approach is two-fold. We want to be respectful of how we engage our peer reviewers and we would rather not have them spend time reviewing manuscripts that we are unlikely to publish. We also want to be respectful of our authors’ time. If we are unlikely to publish a manuscript based on lower priority scores assigned by the Editor-in-Chief and other journal editors, we prefer to return the manuscript to authors for timely submission elsewhere. Our average time from submission to rejection without formal peer review is 1.3 days (median, <1 day). If we send a manuscript out for peer review, our time from submission to first decision is 23 days. Further, if we request a manuscript revision, we sincerely hope to publish the manuscript. Thus, most manuscripts for which we request a revision are ultimately accepted for publication. We are also tracking how quickly we can publish accepted manuscripts with a goal of 120 or fewer days from submission to publication and 60 or fewer days from acceptance to publication.

We highlight our published research in many ways to facilitate dissemination. We promote articles through formal press releases, tweets, visual abstracts, and, more recently, graphic medicine abstracts or comics. Select articles are discussed through our online journal club (#JHMChat).4 Other synergistic methods of dissemination are being planned and we’ll share these ideas with you in the coming year.

We are grateful to receive a large number of submissions and are honored that authors view the Journal of Hospital Medicine as an important venue to showcase their work. We continually strive to improve the author experience and welcome your input.

 

 

 

The Journal of Hospital Medicine® is committed to continually improving the author experience. Our goal is to allow authors to focus more time on communicating their message and less time on navigating the submission and publication process. We commit to three initial areas of emphasis: (1) Make it easy for authors to submit their work; (2) Make timely disposition decisions; and (3) Facilitate dissemination of work that we publish.

We are pleased to introduce a new “No hassle” process for initial original research and brief report manuscript submissions. There is no universally followed format for manuscript submission to medical journals.1-3 As a result, authors spend considerable time reformatting manuscripts for submission to meet each journal’s unique requirements before knowing whether or not their manuscript will be accepted for publication—or even sent for peer review. To streamline the submission process and eliminate unnecessary and burdensome reformatting, we have eased formatting requirements for initial manuscript submissions. We will even accept all manuscript elements in a single PDF (portable document format) file in another journal’s format if your manuscript was submitted elsewhere first but not accepted for publication. Tables and figures can be included in the single document or uploaded separately, depending on your preference. Of course, common elements necessary to assess a manuscript, including declaration of funding sources and conflicts of interest, are required on the title page.1 Journal-specific formatting and signed disclosure and copyright forms will be deferred until a revision request.

We also seek to make timely decisions. Our rapid turnaround allows authors to submit elsewhere expeditiously if not accepted by the Journal of Hospital Medicine. We reject approximately 50% of original research and brief report manuscripts without formal peer review. The rationale for this approach is two-fold. We want to be respectful of how we engage our peer reviewers and we would rather not have them spend time reviewing manuscripts that we are unlikely to publish. We also want to be respectful of our authors’ time. If we are unlikely to publish a manuscript based on lower priority scores assigned by the Editor-in-Chief and other journal editors, we prefer to return the manuscript to authors for timely submission elsewhere. Our average time from submission to rejection without formal peer review is 1.3 days (median, <1 day). If we send a manuscript out for peer review, our time from submission to first decision is 23 days. Further, if we request a manuscript revision, we sincerely hope to publish the manuscript. Thus, most manuscripts for which we request a revision are ultimately accepted for publication. We are also tracking how quickly we can publish accepted manuscripts with a goal of 120 or fewer days from submission to publication and 60 or fewer days from acceptance to publication.

We highlight our published research in many ways to facilitate dissemination. We promote articles through formal press releases, tweets, visual abstracts, and, more recently, graphic medicine abstracts or comics. Select articles are discussed through our online journal club (#JHMChat).4 Other synergistic methods of dissemination are being planned and we’ll share these ideas with you in the coming year.

We are grateful to receive a large number of submissions and are honored that authors view the Journal of Hospital Medicine as an important venue to showcase their work. We continually strive to improve the author experience and welcome your input.

 

 

 

References

1. International Committee of Medical Journal Editors. Recommendations for the conduct, reporting, editing, and publication of scholarly work in medical journals. Updated December 2018. www.icmje.org/recommendations/browse/. Accessed April 2, 2019. PubMed
2. Schriger DL, Arora S, Altman DG. The content of medical journal instructions for authors. Ann Emerg Med. 2006;48(6):743-749. doi: 10.1016/j.annemergmed.2006.03.028 PubMed
3. Barron JP. The uniform requirements for manuscripts submitted to biomedical journals recommended by the International Committee of Medical Journal Editors. Chest. 2006;129(4):1098-1099. doi: 10.1378/chest.129.4.1098PubMed
4. Wray CM, Auerbach AD, Arora VM. The adoption of an online journal club to improve research dissemination and social media engagement among hospitalists. J Hosp Med. 2018;13(11):764-769. doi: 10.12788/jhm.2987. PubMed

References

1. International Committee of Medical Journal Editors. Recommendations for the conduct, reporting, editing, and publication of scholarly work in medical journals. Updated December 2018. www.icmje.org/recommendations/browse/. Accessed April 2, 2019. PubMed
2. Schriger DL, Arora S, Altman DG. The content of medical journal instructions for authors. Ann Emerg Med. 2006;48(6):743-749. doi: 10.1016/j.annemergmed.2006.03.028 PubMed
3. Barron JP. The uniform requirements for manuscripts submitted to biomedical journals recommended by the International Committee of Medical Journal Editors. Chest. 2006;129(4):1098-1099. doi: 10.1378/chest.129.4.1098PubMed
4. Wray CM, Auerbach AD, Arora VM. The adoption of an online journal club to improve research dissemination and social media engagement among hospitalists. J Hosp Med. 2018;13(11):764-769. doi: 10.12788/jhm.2987. PubMed

Issue
Journal of Hospital Medicine 14(5)
Issue
Journal of Hospital Medicine 14(5)
Page Number
265. Published online first April 17, 2019.
Page Number
265. Published online first April 17, 2019.
Topics
Article Type
Sections
Article Source

© 2019 Society of Hospital Medicine

Disallow All Ads
Correspondence Location
[email protected]; Telephone: (513) 636-6222; Twitter: @SamirShahMD
Content Gating
Open Access (article Unlocked/Open Access)
Alternative CME
Disqus Comments
Default
Use ProPublica
Hide sidebar & use full width
render the right sidebar.
Article PDF Media

Things We Do For No Reason: HIT Testing in Low Probability Patients

Article Type
Changed
Tue, 09/21/2021 - 11:11

Inspired by the ABIM Foundation’s Choosing Wisely® campaign, the “Things We Do for No Reason” series reviews practices which have become common parts of hospital care but which may provide little value to our patients. Practices reviewed in the TWDFNR series do not represent “black and white” conclusions or clinical practice standards, but are meant as a starting place for research and active discussions among hospitalists and patients. We invite you to be part of that discussion.

CLINICAL SCENARIO

A 59-year-old man with cirrhosis secondary to nonalcoholic steatohepatitis was admitted to the intensive care unit (ICU) for management of hepatorenal syndrome and work-up for liver transplantation. On admission, his platelet count was 90 × 109/L (normal 150-400 × 109/L), and he was started on thromboprophylaxis with unfractionated heparin (UFH) 5,000 units subcutaneously twice daily. His platelet count began to fall two days after admission. He did have a history of prior heparin exposure associated with his hemodialysis sessions in the past 30 days. During this period, he also had an episode of fever, and antibiotics were initiated for a presumed line infection. He also required periodic vasopressor support for hypotension. His platelet count reached 14 × 109/L by the end of two weeks. He did not have any symptoms of thrombosis, skin necrosis, or reaction to heparin exposure.

BACKGROUND

Thrombocytopenia is common, especially during critical illness, occurring in up to 50% of patients.1 In this population, thrombocytopenia is often due to sepsis, hemorrhage, liver dysfunction, and drug reactions.1,2 Heparin-induced thrombocytopenia (HIT) is an acquired thrombotic drug reaction resulting from platelet activation secondary to antibodies formed against the heparin-modified platelet factor 4 (PF4) complexes.3 This leads to platelet aggregation and dysregulation of the coagulation cascade, which can result in arterial or venous thromboembolic events in up to 50% of patients.3 Mortality associated with HIT can be as high as 30% in this critically ill population.3 Diagnosis of HIT can be made initially through the enzyme-linked immunosorbent assay (ELISA). Management of HIT involves immediate cessation of heparin and initiation of therapeutic anticoagulation with nonheparin agents in order to prevent or treat the thrombotic events.4,5

The true incidence of HIT remains low, occurring in 0.2% to 5% of patients exposed to heparin and less than 1% in the ICU population.2,3,6,7 However, given the high incidence of thrombocytopenia in the ICU, the diagnosis of HIT is often considered, resulting in over-testing in this population. Studies suggest that more than 200 ELISAs are requested per year at many hospitals.8,9 This can lead to significant clinical and economic consequences.

WHY YOU MIGHT THINK HIT TESTING WITH ELISA IS HELPFUL

 

 

Thrombocytopenia is common in hospitalized patients while heparin is frequently used for thromboprophylaxis or therapeutic anticoagulation. As a result, a diagnosis of HIT is often considered.1 The high stakes of the inpatient environment, coupled with the increased frequency of thrombocytopenia and heparin exposure, has led to increased use of HIT testing in this population.10

The most widely available diagnostic test for HIT is the ELISA which detects anti-PF4-heparin antibodies but also nonpathogenic antibodies.11 As a result, the ELISA has a sensitivity close to 100%, allowing physicians to rule out HIT if the test is negative, as indicated by an optical density (OD) of less than 0.4.7 Confirmatory testing with the functional serotonin release assay (SRA) is the reference standard as it confers both a high sensitivity and specificity for HIT.11 Due to technical aspects, SRA, unlike the ELISA, is not available in every center and is often outsourced to external labs. Turn-around time for external SRA testing can vary from days to weeks versus hours for the ELISA. The cost for SRA is approximately $120 (USD) per test compared to $30 (USD) per ELISA. Therefore, the ELISA is the recommended initial test due to its quick turn-around time and lower costs.12,13 For these reasons, the SRA test should not be used initially, but rather to confirm the diagnosis of HIT in patients with a positive ELISA.

WHY YOU SHOULD NOT TEST LOW PROBABILITY PATIENTS FOR HIT

The “4T’s” scoring system is a clinical scoring system that estimates the pretest probability of HIT using clinical and basic laboratory parameters (Table).14 The 4T’s score provides a pretest probability for HIT using four parameters: platelet count, timing of platelet fall, presence of thrombotic events, and the likelihood of another cause of thrombocytopenia. Based on these parameters, the pretest probability for HIT can be divided into three categories: low (4T’s score of ≤3), intermediate (score 4-5), or high (score 6-8).14-16

Validation of the 4T’s score has shown that a low probability score carries a negative predictive value of 99% in a patient population with varying HIT prevalence rates.14 Therefore, having a low score is sufficient to rule out HIT without the need for further laboratory testing.14-16 Although the HIT ELISA confers high sensitivity, due to its detection of nonpathogenic antibodies, its specificity can range from 74% to 84%.15 Therefore, in the setting of a low 4T’s score, HIT testing is not only unnecessary, it can be harmful due to the risk of treating a false positive result. For instance, assuming an average HIT prevalence of 1% and a false positive rate of 16% (specificity 84%), 1/17 (5.6%) patients with a positive ELISA will have HIT if testing is pursued in an indiscriminate manner. The American Society of Hematology Choosing Wisely® Campaign has highlighted this concern by advising physicians that they should “not test or treat for suspected HIT in patients with a low pretest probability of HIT.”17

False positive results on HIT tests are not a trivial concern. The most recognizable adverse event associated with HIT treatment is an elevated risk of bleeding while receiving nonheparin agents. Availability of nonheparin anticoagulants vary by center; however, the most commonly used agents include argatroban, danaparoid, bivalirudin, and off-label fondaparinux.4 Due to its short half-life and hepatic clearance, argatroban is commonly used for cases of confirmed or suspected HIT. A retrospective study assessing the bleeding risk of critically ill patients on argatroban therapy suggests a major bleeding risk of 10% within two days of argatroban initiation.18 In addition, factors such as the presence of elevated bilirubin, major surgery, weight >90 kg, and platelet count <70 × 109/L were found to be associated with increased risk for major bleeding.18 These identified risk factors are very common in the inpatient setting. As a result, monitoring and titration of argatroban can be challenging.

Over-diagnosis and over-treatment can also lead to significant costs to the healthcare system. A retrospective study assessing the use of HIT testing found that out of 218 HIT ELISA’s sent over a one-year period at a single institution, 161 (74%) were sent inappropriately (ie, in patients with a low pretest probability), with only one resulting in confirmed HIT by SRA. This incurred an additional cost of $33,000 (USD) for testing alone.8 A retrospective study of 85 patients assessed the costs of treating patients with a false positive HIT assay. They found that the average duration of treatment with a nonheparin agent was three days and the total cost per patient was $982 (USD).19 Treatment with a nonheparin agent such as argatroban costs more than $700 (USD) per day while the continuation of unfractionated heparin for prophylaxis costs less than $10 (USD) per day.20Lastly, a diagnosis of HIT can also result in late consequences due to heparin re-exposure. Clinicians may be wary of exposing patients to heparin in situations where heparin may be the most appropriate agent such as cardiovascular surgery, percutaneous interventions, routine thromboprophylaxis, or therapeutic anticoagulation. In these situations when heparin is the agent of choice, determining safety for re-exposure requires further antibody testing which may delay procedures or result in the use of alternative agents with their associated risks and cost implications.4

 

 

WHEN HIT TESTING WITH ELISA MAY BE HELPFUL

Laboratory testing for HIT is appropriate when the pretest probability for HIT is intermediate or high based on the 4T’s score.14-16 Studies assessing the application of the 4T’s score have shown that a moderate or high pretest probability carries a probability of having true HIT in 14% and 64% of the cases respectively.14 However, due to the subjective nature of the 4T’s score components, it is important to recognize that in nonexpert hands, the 4T’s scoring system can suffer from a lack of interrater reliability.16

As discussed above, a negative ELISA (OD < 0.4) helps to rule out HIT and allow heparin to be safely reintroduced without any further testing. If ELISA is positive (OD ≥ 0.4) confirmation testing with SRA should be performed.5 However, studies suggest that the magnitude of the OD is associated with increased likelihood for true HIT, with an OD of greater than 2.00 associated with a positive SRA approximately 90% of the time.21 This suggests that if OD values are strongly positive (≥2.00), SRA can be deferred.5

Due to the SRA limited availability, confirmatory testing is not always possible or in some situations, SRA results may be negative despite a positive OD. In both these cases, discussion with the Hematology service is recommended.

WHAT WE SHOULD DO INSTEAD OF SENDING ELISA

When presented with a case of thrombocytopenia, it is important for clinicians to consider a broad approach in their differential diagnosis. Hospitalists should investigate common etiologies, consider the coagulation parameters, liver enzymes, nutritional status, peripheral blood smear, and a detailed history and physical exam to identify other common potential cause such as sepsis.

The 4T’s score should be applied in patients who have had recent heparin exposure. A score of ≤3 indicates a low pretest probability; therefore, HIT is unlikely and further testing is not needed. A score of ≥4 indicates an intermediate or high pretest probability and should prompt clinicians to consider further HIT testing with ELISA. In these situations, heparin should be held, and nonheparin agents should be initiated to prevent thromboembolic complications. In their study of ICU patients, Pierce et al. found that 17% of patients did not have a concurrent cessation of heparin and initiation of alternative agents despite a high clinical suspicion for HIT.1 Lastly, if hospitalists have concerns regarding HIT testing or management, expert consultation with the Hematology service is recommended.

RECOMMENDATIONS

  • Consider a broad differential diagnosis when presented with a hospitalized patient with new thrombocytopenia given the low incidence of HIT (<5%).
  • Apply the 4T’s score in those who have thrombocytopenia and recent heparin exposure. A low scores 4T’s score (≤3) predicts a low pretest probability and further testing is not required.
  • Patients with moderate or high 4T’s score (≥4) should have the ELISA test. During this time, heparin should be discontinued and nonheparin agents initiated while waiting for test results.
  • Confirmatory testing with SRA should be performed for all positive ELISAs; however, they can be deferred in patients with strongly positive OD (≥2.00) on ELISA.
 

 

 

CONCLUSION

In the opening clinical scenario, the 4T’s score would have been 2 (1 point for the platelet count, 1 point for the platelet count fall after 10 days, 0 points for thrombosis, and 0 points for an alternative cause of thrombocytopenia), indicating a low pretest probability. Further HIT testing should be deferred as the likelihood for HIT is low. In this case, the more likely etiology for his thrombocytopenia would be sepsis. Therefore, heparin can be safely reinitiated once the platelet count recovers. This case helps to illustrate the importance of keeping a broad differential in cases of thrombocytopenia in the hospitalized patient while concurrently applying the 4T’s score to determine appropriateness for further HIT testing. Ultimately by choosing wisely, we can help reduce the cost and safety implications of a falsely positive HIT diagnosis.

What do you do?

Do you think this is a low-value practice? Is this truly a “Thing We Do for No Reason”? Let us know what you do in your practice and propose ideas for other “Things We Do for No Reason” topics. Please join in the conversation online at Twitter (#TWDFNR)/Facebook and don’t forget to “Like It” on Facebook or retweet it on Twitter.

Disclosures

The authors report no conflict of interest.

Files
References

1. Pierce W, Mazur J, Greenberg C, Mueller J, Foster J, Lazarchick J. Evaluation of heparin-induced thrombocytopenia (HIT) laboratory testing and the 4Ts scoring system in the intensive care unit. Ann Clin Lab Sci. 2013;43(4):429-435. PubMed
2. Harada MY, Hoang DM, Zaw AA, et al. Overtreatment of heparin-induced thrombocytopenia in the surgical ICU. Crit Care Med. 2017;45(1):28-34. doi:10.1097/ccm.0000000000002002. PubMed
3. Warkentin TE, Sheppard JAI, Heels-Ansdell D, et al. Heparin-induced thrombocytopenia in medical-surgical critical illness. Chest. 2013;144(3):848-858. doi: 10.1378/chest.13-0057. PubMed
4. Linkins LA, Dans AL, Moores LK, et al. Treatment and prevention of heparin-induced thrombocytopenia. Chest. 2012;141(2):e495S-e530S. doi: 10.1378/chest.11-2303. PubMed
5. Cuker A, Arepally GM, Chong BH, et al. American Society of Hematology 2018 guidelines for management of venous thromboembolism: heparin-induced thrombocytopenia. Blood Adv. 2018;2(22):3360-3392. doi: 10.1182/bloodadvances.2018024489. PubMed
6. Lo GK, Juhl D, Warkentin TE, Sigouin CS, Eichler P, Greinacher A. Evaluation of pretest clinical score (4 T’s) for the diagnosis of heparin-induced thrombocytopenia in two clinical settings. J Thromb Haemost. 2006;4(4):759-765. doi: 10.1111/j.1538-7836.2006.01787.x PubMed
7. Cuker A, Cines DB. How I treat heparin-induced thrombocytopenia. Blood. 2012;119(10):2209-2218. doi: 10.1182/blood-2011-11-376293. PubMed
8. Elmer P, Passero FC, Xavier M. Retrospective Analysis of Heparin-Induced Thrombocytopenia Management at a Large Tertiary Hospital. J Hematol. 2014;3(2):27-33. doi: http://dx.doi.org/10.14740/jh157w. 
9. Goldman R, Ustun B, Levine RL. Retrospective cost analysis of testing for HIT antibodies in a community hospital. Blood. 2008;112(11):4544.
10. Cuker A. Heparin-induced thrombocytopenia (HIT) in 2011: an epidemic of overdiagnosis. Thromb Haemost. 2011;106(6):993-994. doi: 10.1160/TH11-09-0677. 
11. Warkentin TE. Heparin-induced thrombocytopenia in critically ill patients. Semin Thromb Hemost. 2015;41(5):49-60. doi: 10.1055/s-0034-1398381. PubMed
12. Caton S, O’Brien E, Pannelay AJ, Cook RG. Assessing the clinical and cost impact of on-demand immunoassay testing for the diagnosis of heparin-induced thrombocytopenia. Thromb Res. 2016;140:155-162. doi: 10.1016/j.thromres.2016.01.025 PubMed
13. Nanwa N, Mittmann N, Knowles S, et al. The direct medical costs associated with suspected heparin-induced thrombocytopenia. Pharmacoeconomics. 2011;29(6):511-520. doi: 10.2165/11584330-000000000-00000. PubMed
14. Cuker A, Gimotty PA, Crowther MA, Warkentin TE. Predictive value of the 4Ts scoring system for heparin-induced thrombocytopenia: a systematic review and meta-analysis. Blood. 2012;120(20):4160-4167. doi: 10.1182/blood-2012-07-443051. PubMed
15. Fiorenza MA, Frazee EN, Personett HA, Dierkhising RA, Schramm GE. Assessment of a modified 4T scoring system for heparin-induced thrombocytopenia in critically ill patients. J Crit Care. 2014;29(3):426-431. doi: 10.1016/j.jcrc.2013.12.010. PubMed
16. Crowther M, Cook D, Guyatt G, et al. Heparin-induced thrombocytopenia in the critically ill: interpreting the 4Ts test in a randomized trial. J Crit Care. 2014;29(3):470.e7-470.e15 doi: 10.1016/j.jcrc.2014.02.004. PubMed
17. Hicks LK, Bering H, Carson KR, et al. The ASH Choosing Wisely campaign: five hematologic tests and treatments to question. Blood. 2013;122(24):3879-3883. doi: 10.1182/blood-2013-07-518423. PubMed
18. Doepker B, Mount KL, Ryder LJ, Gerlach AT, Murphy CV, Philips GS. Bleeding risk factors associated with argatroban therapy in the critically ill. J Thromb Thrombolysis. 2012;34(4):491-498. doi: 10.1007/s11239-012-0758-y. PubMed
19. Marler J, Unzaga J, Stelts S, Oliphant CS. Consequences of treating false positive heparin-induced thrombocytopenia. J Thromb Thrombolysis. 2015;40(4):512-514. doi: 10.1007/s11239-015-1236-0. PubMed
20. Fowler RA, Mittmann N, Geerts W, et al. Cost-effectiveness of dalteparin vs unfractionated heparin for the prevention of venous thromboembolism in critically ill patients. JAMA. 2014;312(20):2135-2145. doi: 10.1001/jama.2014.15101. PubMed
21. Warkentin TE, Sheppard JI, Moore JC, Sigouin CS, Kelton JG. Quantitative interpretation of optical density measurements using PF4-dependent enzyme-immunoassays. J Thromb Haemost. 2008;6(8):1304-1312. doi: 10.1111/j.1538-7836.2008.03025.x. PubMed

Article PDF
Issue
Journal of Hospital Medicine 14(6)
Topics
Page Number
374-376. Published online first April 8, 2019.
Sections
Files
Files
Article PDF
Article PDF

Inspired by the ABIM Foundation’s Choosing Wisely® campaign, the “Things We Do for No Reason” series reviews practices which have become common parts of hospital care but which may provide little value to our patients. Practices reviewed in the TWDFNR series do not represent “black and white” conclusions or clinical practice standards, but are meant as a starting place for research and active discussions among hospitalists and patients. We invite you to be part of that discussion.

CLINICAL SCENARIO

A 59-year-old man with cirrhosis secondary to nonalcoholic steatohepatitis was admitted to the intensive care unit (ICU) for management of hepatorenal syndrome and work-up for liver transplantation. On admission, his platelet count was 90 × 109/L (normal 150-400 × 109/L), and he was started on thromboprophylaxis with unfractionated heparin (UFH) 5,000 units subcutaneously twice daily. His platelet count began to fall two days after admission. He did have a history of prior heparin exposure associated with his hemodialysis sessions in the past 30 days. During this period, he also had an episode of fever, and antibiotics were initiated for a presumed line infection. He also required periodic vasopressor support for hypotension. His platelet count reached 14 × 109/L by the end of two weeks. He did not have any symptoms of thrombosis, skin necrosis, or reaction to heparin exposure.

BACKGROUND

Thrombocytopenia is common, especially during critical illness, occurring in up to 50% of patients.1 In this population, thrombocytopenia is often due to sepsis, hemorrhage, liver dysfunction, and drug reactions.1,2 Heparin-induced thrombocytopenia (HIT) is an acquired thrombotic drug reaction resulting from platelet activation secondary to antibodies formed against the heparin-modified platelet factor 4 (PF4) complexes.3 This leads to platelet aggregation and dysregulation of the coagulation cascade, which can result in arterial or venous thromboembolic events in up to 50% of patients.3 Mortality associated with HIT can be as high as 30% in this critically ill population.3 Diagnosis of HIT can be made initially through the enzyme-linked immunosorbent assay (ELISA). Management of HIT involves immediate cessation of heparin and initiation of therapeutic anticoagulation with nonheparin agents in order to prevent or treat the thrombotic events.4,5

The true incidence of HIT remains low, occurring in 0.2% to 5% of patients exposed to heparin and less than 1% in the ICU population.2,3,6,7 However, given the high incidence of thrombocytopenia in the ICU, the diagnosis of HIT is often considered, resulting in over-testing in this population. Studies suggest that more than 200 ELISAs are requested per year at many hospitals.8,9 This can lead to significant clinical and economic consequences.

WHY YOU MIGHT THINK HIT TESTING WITH ELISA IS HELPFUL

 

 

Thrombocytopenia is common in hospitalized patients while heparin is frequently used for thromboprophylaxis or therapeutic anticoagulation. As a result, a diagnosis of HIT is often considered.1 The high stakes of the inpatient environment, coupled with the increased frequency of thrombocytopenia and heparin exposure, has led to increased use of HIT testing in this population.10

The most widely available diagnostic test for HIT is the ELISA which detects anti-PF4-heparin antibodies but also nonpathogenic antibodies.11 As a result, the ELISA has a sensitivity close to 100%, allowing physicians to rule out HIT if the test is negative, as indicated by an optical density (OD) of less than 0.4.7 Confirmatory testing with the functional serotonin release assay (SRA) is the reference standard as it confers both a high sensitivity and specificity for HIT.11 Due to technical aspects, SRA, unlike the ELISA, is not available in every center and is often outsourced to external labs. Turn-around time for external SRA testing can vary from days to weeks versus hours for the ELISA. The cost for SRA is approximately $120 (USD) per test compared to $30 (USD) per ELISA. Therefore, the ELISA is the recommended initial test due to its quick turn-around time and lower costs.12,13 For these reasons, the SRA test should not be used initially, but rather to confirm the diagnosis of HIT in patients with a positive ELISA.

WHY YOU SHOULD NOT TEST LOW PROBABILITY PATIENTS FOR HIT

The “4T’s” scoring system is a clinical scoring system that estimates the pretest probability of HIT using clinical and basic laboratory parameters (Table).14 The 4T’s score provides a pretest probability for HIT using four parameters: platelet count, timing of platelet fall, presence of thrombotic events, and the likelihood of another cause of thrombocytopenia. Based on these parameters, the pretest probability for HIT can be divided into three categories: low (4T’s score of ≤3), intermediate (score 4-5), or high (score 6-8).14-16

Validation of the 4T’s score has shown that a low probability score carries a negative predictive value of 99% in a patient population with varying HIT prevalence rates.14 Therefore, having a low score is sufficient to rule out HIT without the need for further laboratory testing.14-16 Although the HIT ELISA confers high sensitivity, due to its detection of nonpathogenic antibodies, its specificity can range from 74% to 84%.15 Therefore, in the setting of a low 4T’s score, HIT testing is not only unnecessary, it can be harmful due to the risk of treating a false positive result. For instance, assuming an average HIT prevalence of 1% and a false positive rate of 16% (specificity 84%), 1/17 (5.6%) patients with a positive ELISA will have HIT if testing is pursued in an indiscriminate manner. The American Society of Hematology Choosing Wisely® Campaign has highlighted this concern by advising physicians that they should “not test or treat for suspected HIT in patients with a low pretest probability of HIT.”17

False positive results on HIT tests are not a trivial concern. The most recognizable adverse event associated with HIT treatment is an elevated risk of bleeding while receiving nonheparin agents. Availability of nonheparin anticoagulants vary by center; however, the most commonly used agents include argatroban, danaparoid, bivalirudin, and off-label fondaparinux.4 Due to its short half-life and hepatic clearance, argatroban is commonly used for cases of confirmed or suspected HIT. A retrospective study assessing the bleeding risk of critically ill patients on argatroban therapy suggests a major bleeding risk of 10% within two days of argatroban initiation.18 In addition, factors such as the presence of elevated bilirubin, major surgery, weight >90 kg, and platelet count <70 × 109/L were found to be associated with increased risk for major bleeding.18 These identified risk factors are very common in the inpatient setting. As a result, monitoring and titration of argatroban can be challenging.

Over-diagnosis and over-treatment can also lead to significant costs to the healthcare system. A retrospective study assessing the use of HIT testing found that out of 218 HIT ELISA’s sent over a one-year period at a single institution, 161 (74%) were sent inappropriately (ie, in patients with a low pretest probability), with only one resulting in confirmed HIT by SRA. This incurred an additional cost of $33,000 (USD) for testing alone.8 A retrospective study of 85 patients assessed the costs of treating patients with a false positive HIT assay. They found that the average duration of treatment with a nonheparin agent was three days and the total cost per patient was $982 (USD).19 Treatment with a nonheparin agent such as argatroban costs more than $700 (USD) per day while the continuation of unfractionated heparin for prophylaxis costs less than $10 (USD) per day.20Lastly, a diagnosis of HIT can also result in late consequences due to heparin re-exposure. Clinicians may be wary of exposing patients to heparin in situations where heparin may be the most appropriate agent such as cardiovascular surgery, percutaneous interventions, routine thromboprophylaxis, or therapeutic anticoagulation. In these situations when heparin is the agent of choice, determining safety for re-exposure requires further antibody testing which may delay procedures or result in the use of alternative agents with their associated risks and cost implications.4

 

 

WHEN HIT TESTING WITH ELISA MAY BE HELPFUL

Laboratory testing for HIT is appropriate when the pretest probability for HIT is intermediate or high based on the 4T’s score.14-16 Studies assessing the application of the 4T’s score have shown that a moderate or high pretest probability carries a probability of having true HIT in 14% and 64% of the cases respectively.14 However, due to the subjective nature of the 4T’s score components, it is important to recognize that in nonexpert hands, the 4T’s scoring system can suffer from a lack of interrater reliability.16

As discussed above, a negative ELISA (OD < 0.4) helps to rule out HIT and allow heparin to be safely reintroduced without any further testing. If ELISA is positive (OD ≥ 0.4) confirmation testing with SRA should be performed.5 However, studies suggest that the magnitude of the OD is associated with increased likelihood for true HIT, with an OD of greater than 2.00 associated with a positive SRA approximately 90% of the time.21 This suggests that if OD values are strongly positive (≥2.00), SRA can be deferred.5

Due to the SRA limited availability, confirmatory testing is not always possible or in some situations, SRA results may be negative despite a positive OD. In both these cases, discussion with the Hematology service is recommended.

WHAT WE SHOULD DO INSTEAD OF SENDING ELISA

When presented with a case of thrombocytopenia, it is important for clinicians to consider a broad approach in their differential diagnosis. Hospitalists should investigate common etiologies, consider the coagulation parameters, liver enzymes, nutritional status, peripheral blood smear, and a detailed history and physical exam to identify other common potential cause such as sepsis.

The 4T’s score should be applied in patients who have had recent heparin exposure. A score of ≤3 indicates a low pretest probability; therefore, HIT is unlikely and further testing is not needed. A score of ≥4 indicates an intermediate or high pretest probability and should prompt clinicians to consider further HIT testing with ELISA. In these situations, heparin should be held, and nonheparin agents should be initiated to prevent thromboembolic complications. In their study of ICU patients, Pierce et al. found that 17% of patients did not have a concurrent cessation of heparin and initiation of alternative agents despite a high clinical suspicion for HIT.1 Lastly, if hospitalists have concerns regarding HIT testing or management, expert consultation with the Hematology service is recommended.

RECOMMENDATIONS

  • Consider a broad differential diagnosis when presented with a hospitalized patient with new thrombocytopenia given the low incidence of HIT (<5%).
  • Apply the 4T’s score in those who have thrombocytopenia and recent heparin exposure. A low scores 4T’s score (≤3) predicts a low pretest probability and further testing is not required.
  • Patients with moderate or high 4T’s score (≥4) should have the ELISA test. During this time, heparin should be discontinued and nonheparin agents initiated while waiting for test results.
  • Confirmatory testing with SRA should be performed for all positive ELISAs; however, they can be deferred in patients with strongly positive OD (≥2.00) on ELISA.
 

 

 

CONCLUSION

In the opening clinical scenario, the 4T’s score would have been 2 (1 point for the platelet count, 1 point for the platelet count fall after 10 days, 0 points for thrombosis, and 0 points for an alternative cause of thrombocytopenia), indicating a low pretest probability. Further HIT testing should be deferred as the likelihood for HIT is low. In this case, the more likely etiology for his thrombocytopenia would be sepsis. Therefore, heparin can be safely reinitiated once the platelet count recovers. This case helps to illustrate the importance of keeping a broad differential in cases of thrombocytopenia in the hospitalized patient while concurrently applying the 4T’s score to determine appropriateness for further HIT testing. Ultimately by choosing wisely, we can help reduce the cost and safety implications of a falsely positive HIT diagnosis.

What do you do?

Do you think this is a low-value practice? Is this truly a “Thing We Do for No Reason”? Let us know what you do in your practice and propose ideas for other “Things We Do for No Reason” topics. Please join in the conversation online at Twitter (#TWDFNR)/Facebook and don’t forget to “Like It” on Facebook or retweet it on Twitter.

Disclosures

The authors report no conflict of interest.

Inspired by the ABIM Foundation’s Choosing Wisely® campaign, the “Things We Do for No Reason” series reviews practices which have become common parts of hospital care but which may provide little value to our patients. Practices reviewed in the TWDFNR series do not represent “black and white” conclusions or clinical practice standards, but are meant as a starting place for research and active discussions among hospitalists and patients. We invite you to be part of that discussion.

CLINICAL SCENARIO

A 59-year-old man with cirrhosis secondary to nonalcoholic steatohepatitis was admitted to the intensive care unit (ICU) for management of hepatorenal syndrome and work-up for liver transplantation. On admission, his platelet count was 90 × 109/L (normal 150-400 × 109/L), and he was started on thromboprophylaxis with unfractionated heparin (UFH) 5,000 units subcutaneously twice daily. His platelet count began to fall two days after admission. He did have a history of prior heparin exposure associated with his hemodialysis sessions in the past 30 days. During this period, he also had an episode of fever, and antibiotics were initiated for a presumed line infection. He also required periodic vasopressor support for hypotension. His platelet count reached 14 × 109/L by the end of two weeks. He did not have any symptoms of thrombosis, skin necrosis, or reaction to heparin exposure.

BACKGROUND

Thrombocytopenia is common, especially during critical illness, occurring in up to 50% of patients.1 In this population, thrombocytopenia is often due to sepsis, hemorrhage, liver dysfunction, and drug reactions.1,2 Heparin-induced thrombocytopenia (HIT) is an acquired thrombotic drug reaction resulting from platelet activation secondary to antibodies formed against the heparin-modified platelet factor 4 (PF4) complexes.3 This leads to platelet aggregation and dysregulation of the coagulation cascade, which can result in arterial or venous thromboembolic events in up to 50% of patients.3 Mortality associated with HIT can be as high as 30% in this critically ill population.3 Diagnosis of HIT can be made initially through the enzyme-linked immunosorbent assay (ELISA). Management of HIT involves immediate cessation of heparin and initiation of therapeutic anticoagulation with nonheparin agents in order to prevent or treat the thrombotic events.4,5

The true incidence of HIT remains low, occurring in 0.2% to 5% of patients exposed to heparin and less than 1% in the ICU population.2,3,6,7 However, given the high incidence of thrombocytopenia in the ICU, the diagnosis of HIT is often considered, resulting in over-testing in this population. Studies suggest that more than 200 ELISAs are requested per year at many hospitals.8,9 This can lead to significant clinical and economic consequences.

WHY YOU MIGHT THINK HIT TESTING WITH ELISA IS HELPFUL

 

 

Thrombocytopenia is common in hospitalized patients while heparin is frequently used for thromboprophylaxis or therapeutic anticoagulation. As a result, a diagnosis of HIT is often considered.1 The high stakes of the inpatient environment, coupled with the increased frequency of thrombocytopenia and heparin exposure, has led to increased use of HIT testing in this population.10

The most widely available diagnostic test for HIT is the ELISA which detects anti-PF4-heparin antibodies but also nonpathogenic antibodies.11 As a result, the ELISA has a sensitivity close to 100%, allowing physicians to rule out HIT if the test is negative, as indicated by an optical density (OD) of less than 0.4.7 Confirmatory testing with the functional serotonin release assay (SRA) is the reference standard as it confers both a high sensitivity and specificity for HIT.11 Due to technical aspects, SRA, unlike the ELISA, is not available in every center and is often outsourced to external labs. Turn-around time for external SRA testing can vary from days to weeks versus hours for the ELISA. The cost for SRA is approximately $120 (USD) per test compared to $30 (USD) per ELISA. Therefore, the ELISA is the recommended initial test due to its quick turn-around time and lower costs.12,13 For these reasons, the SRA test should not be used initially, but rather to confirm the diagnosis of HIT in patients with a positive ELISA.

WHY YOU SHOULD NOT TEST LOW PROBABILITY PATIENTS FOR HIT

The “4T’s” scoring system is a clinical scoring system that estimates the pretest probability of HIT using clinical and basic laboratory parameters (Table).14 The 4T’s score provides a pretest probability for HIT using four parameters: platelet count, timing of platelet fall, presence of thrombotic events, and the likelihood of another cause of thrombocytopenia. Based on these parameters, the pretest probability for HIT can be divided into three categories: low (4T’s score of ≤3), intermediate (score 4-5), or high (score 6-8).14-16

Validation of the 4T’s score has shown that a low probability score carries a negative predictive value of 99% in a patient population with varying HIT prevalence rates.14 Therefore, having a low score is sufficient to rule out HIT without the need for further laboratory testing.14-16 Although the HIT ELISA confers high sensitivity, due to its detection of nonpathogenic antibodies, its specificity can range from 74% to 84%.15 Therefore, in the setting of a low 4T’s score, HIT testing is not only unnecessary, it can be harmful due to the risk of treating a false positive result. For instance, assuming an average HIT prevalence of 1% and a false positive rate of 16% (specificity 84%), 1/17 (5.6%) patients with a positive ELISA will have HIT if testing is pursued in an indiscriminate manner. The American Society of Hematology Choosing Wisely® Campaign has highlighted this concern by advising physicians that they should “not test or treat for suspected HIT in patients with a low pretest probability of HIT.”17

False positive results on HIT tests are not a trivial concern. The most recognizable adverse event associated with HIT treatment is an elevated risk of bleeding while receiving nonheparin agents. Availability of nonheparin anticoagulants vary by center; however, the most commonly used agents include argatroban, danaparoid, bivalirudin, and off-label fondaparinux.4 Due to its short half-life and hepatic clearance, argatroban is commonly used for cases of confirmed or suspected HIT. A retrospective study assessing the bleeding risk of critically ill patients on argatroban therapy suggests a major bleeding risk of 10% within two days of argatroban initiation.18 In addition, factors such as the presence of elevated bilirubin, major surgery, weight >90 kg, and platelet count <70 × 109/L were found to be associated with increased risk for major bleeding.18 These identified risk factors are very common in the inpatient setting. As a result, monitoring and titration of argatroban can be challenging.

Over-diagnosis and over-treatment can also lead to significant costs to the healthcare system. A retrospective study assessing the use of HIT testing found that out of 218 HIT ELISA’s sent over a one-year period at a single institution, 161 (74%) were sent inappropriately (ie, in patients with a low pretest probability), with only one resulting in confirmed HIT by SRA. This incurred an additional cost of $33,000 (USD) for testing alone.8 A retrospective study of 85 patients assessed the costs of treating patients with a false positive HIT assay. They found that the average duration of treatment with a nonheparin agent was three days and the total cost per patient was $982 (USD).19 Treatment with a nonheparin agent such as argatroban costs more than $700 (USD) per day while the continuation of unfractionated heparin for prophylaxis costs less than $10 (USD) per day.20Lastly, a diagnosis of HIT can also result in late consequences due to heparin re-exposure. Clinicians may be wary of exposing patients to heparin in situations where heparin may be the most appropriate agent such as cardiovascular surgery, percutaneous interventions, routine thromboprophylaxis, or therapeutic anticoagulation. In these situations when heparin is the agent of choice, determining safety for re-exposure requires further antibody testing which may delay procedures or result in the use of alternative agents with their associated risks and cost implications.4

 

 

WHEN HIT TESTING WITH ELISA MAY BE HELPFUL

Laboratory testing for HIT is appropriate when the pretest probability for HIT is intermediate or high based on the 4T’s score.14-16 Studies assessing the application of the 4T’s score have shown that a moderate or high pretest probability carries a probability of having true HIT in 14% and 64% of the cases respectively.14 However, due to the subjective nature of the 4T’s score components, it is important to recognize that in nonexpert hands, the 4T’s scoring system can suffer from a lack of interrater reliability.16

As discussed above, a negative ELISA (OD < 0.4) helps to rule out HIT and allow heparin to be safely reintroduced without any further testing. If ELISA is positive (OD ≥ 0.4) confirmation testing with SRA should be performed.5 However, studies suggest that the magnitude of the OD is associated with increased likelihood for true HIT, with an OD of greater than 2.00 associated with a positive SRA approximately 90% of the time.21 This suggests that if OD values are strongly positive (≥2.00), SRA can be deferred.5

Due to the SRA limited availability, confirmatory testing is not always possible or in some situations, SRA results may be negative despite a positive OD. In both these cases, discussion with the Hematology service is recommended.

WHAT WE SHOULD DO INSTEAD OF SENDING ELISA

When presented with a case of thrombocytopenia, it is important for clinicians to consider a broad approach in their differential diagnosis. Hospitalists should investigate common etiologies, consider the coagulation parameters, liver enzymes, nutritional status, peripheral blood smear, and a detailed history and physical exam to identify other common potential cause such as sepsis.

The 4T’s score should be applied in patients who have had recent heparin exposure. A score of ≤3 indicates a low pretest probability; therefore, HIT is unlikely and further testing is not needed. A score of ≥4 indicates an intermediate or high pretest probability and should prompt clinicians to consider further HIT testing with ELISA. In these situations, heparin should be held, and nonheparin agents should be initiated to prevent thromboembolic complications. In their study of ICU patients, Pierce et al. found that 17% of patients did not have a concurrent cessation of heparin and initiation of alternative agents despite a high clinical suspicion for HIT.1 Lastly, if hospitalists have concerns regarding HIT testing or management, expert consultation with the Hematology service is recommended.

RECOMMENDATIONS

  • Consider a broad differential diagnosis when presented with a hospitalized patient with new thrombocytopenia given the low incidence of HIT (<5%).
  • Apply the 4T’s score in those who have thrombocytopenia and recent heparin exposure. A low scores 4T’s score (≤3) predicts a low pretest probability and further testing is not required.
  • Patients with moderate or high 4T’s score (≥4) should have the ELISA test. During this time, heparin should be discontinued and nonheparin agents initiated while waiting for test results.
  • Confirmatory testing with SRA should be performed for all positive ELISAs; however, they can be deferred in patients with strongly positive OD (≥2.00) on ELISA.
 

 

 

CONCLUSION

In the opening clinical scenario, the 4T’s score would have been 2 (1 point for the platelet count, 1 point for the platelet count fall after 10 days, 0 points for thrombosis, and 0 points for an alternative cause of thrombocytopenia), indicating a low pretest probability. Further HIT testing should be deferred as the likelihood for HIT is low. In this case, the more likely etiology for his thrombocytopenia would be sepsis. Therefore, heparin can be safely reinitiated once the platelet count recovers. This case helps to illustrate the importance of keeping a broad differential in cases of thrombocytopenia in the hospitalized patient while concurrently applying the 4T’s score to determine appropriateness for further HIT testing. Ultimately by choosing wisely, we can help reduce the cost and safety implications of a falsely positive HIT diagnosis.

What do you do?

Do you think this is a low-value practice? Is this truly a “Thing We Do for No Reason”? Let us know what you do in your practice and propose ideas for other “Things We Do for No Reason” topics. Please join in the conversation online at Twitter (#TWDFNR)/Facebook and don’t forget to “Like It” on Facebook or retweet it on Twitter.

Disclosures

The authors report no conflict of interest.

References

1. Pierce W, Mazur J, Greenberg C, Mueller J, Foster J, Lazarchick J. Evaluation of heparin-induced thrombocytopenia (HIT) laboratory testing and the 4Ts scoring system in the intensive care unit. Ann Clin Lab Sci. 2013;43(4):429-435. PubMed
2. Harada MY, Hoang DM, Zaw AA, et al. Overtreatment of heparin-induced thrombocytopenia in the surgical ICU. Crit Care Med. 2017;45(1):28-34. doi:10.1097/ccm.0000000000002002. PubMed
3. Warkentin TE, Sheppard JAI, Heels-Ansdell D, et al. Heparin-induced thrombocytopenia in medical-surgical critical illness. Chest. 2013;144(3):848-858. doi: 10.1378/chest.13-0057. PubMed
4. Linkins LA, Dans AL, Moores LK, et al. Treatment and prevention of heparin-induced thrombocytopenia. Chest. 2012;141(2):e495S-e530S. doi: 10.1378/chest.11-2303. PubMed
5. Cuker A, Arepally GM, Chong BH, et al. American Society of Hematology 2018 guidelines for management of venous thromboembolism: heparin-induced thrombocytopenia. Blood Adv. 2018;2(22):3360-3392. doi: 10.1182/bloodadvances.2018024489. PubMed
6. Lo GK, Juhl D, Warkentin TE, Sigouin CS, Eichler P, Greinacher A. Evaluation of pretest clinical score (4 T’s) for the diagnosis of heparin-induced thrombocytopenia in two clinical settings. J Thromb Haemost. 2006;4(4):759-765. doi: 10.1111/j.1538-7836.2006.01787.x PubMed
7. Cuker A, Cines DB. How I treat heparin-induced thrombocytopenia. Blood. 2012;119(10):2209-2218. doi: 10.1182/blood-2011-11-376293. PubMed
8. Elmer P, Passero FC, Xavier M. Retrospective Analysis of Heparin-Induced Thrombocytopenia Management at a Large Tertiary Hospital. J Hematol. 2014;3(2):27-33. doi: http://dx.doi.org/10.14740/jh157w. 
9. Goldman R, Ustun B, Levine RL. Retrospective cost analysis of testing for HIT antibodies in a community hospital. Blood. 2008;112(11):4544.
10. Cuker A. Heparin-induced thrombocytopenia (HIT) in 2011: an epidemic of overdiagnosis. Thromb Haemost. 2011;106(6):993-994. doi: 10.1160/TH11-09-0677. 
11. Warkentin TE. Heparin-induced thrombocytopenia in critically ill patients. Semin Thromb Hemost. 2015;41(5):49-60. doi: 10.1055/s-0034-1398381. PubMed
12. Caton S, O’Brien E, Pannelay AJ, Cook RG. Assessing the clinical and cost impact of on-demand immunoassay testing for the diagnosis of heparin-induced thrombocytopenia. Thromb Res. 2016;140:155-162. doi: 10.1016/j.thromres.2016.01.025 PubMed
13. Nanwa N, Mittmann N, Knowles S, et al. The direct medical costs associated with suspected heparin-induced thrombocytopenia. Pharmacoeconomics. 2011;29(6):511-520. doi: 10.2165/11584330-000000000-00000. PubMed
14. Cuker A, Gimotty PA, Crowther MA, Warkentin TE. Predictive value of the 4Ts scoring system for heparin-induced thrombocytopenia: a systematic review and meta-analysis. Blood. 2012;120(20):4160-4167. doi: 10.1182/blood-2012-07-443051. PubMed
15. Fiorenza MA, Frazee EN, Personett HA, Dierkhising RA, Schramm GE. Assessment of a modified 4T scoring system for heparin-induced thrombocytopenia in critically ill patients. J Crit Care. 2014;29(3):426-431. doi: 10.1016/j.jcrc.2013.12.010. PubMed
16. Crowther M, Cook D, Guyatt G, et al. Heparin-induced thrombocytopenia in the critically ill: interpreting the 4Ts test in a randomized trial. J Crit Care. 2014;29(3):470.e7-470.e15 doi: 10.1016/j.jcrc.2014.02.004. PubMed
17. Hicks LK, Bering H, Carson KR, et al. The ASH Choosing Wisely campaign: five hematologic tests and treatments to question. Blood. 2013;122(24):3879-3883. doi: 10.1182/blood-2013-07-518423. PubMed
18. Doepker B, Mount KL, Ryder LJ, Gerlach AT, Murphy CV, Philips GS. Bleeding risk factors associated with argatroban therapy in the critically ill. J Thromb Thrombolysis. 2012;34(4):491-498. doi: 10.1007/s11239-012-0758-y. PubMed
19. Marler J, Unzaga J, Stelts S, Oliphant CS. Consequences of treating false positive heparin-induced thrombocytopenia. J Thromb Thrombolysis. 2015;40(4):512-514. doi: 10.1007/s11239-015-1236-0. PubMed
20. Fowler RA, Mittmann N, Geerts W, et al. Cost-effectiveness of dalteparin vs unfractionated heparin for the prevention of venous thromboembolism in critically ill patients. JAMA. 2014;312(20):2135-2145. doi: 10.1001/jama.2014.15101. PubMed
21. Warkentin TE, Sheppard JI, Moore JC, Sigouin CS, Kelton JG. Quantitative interpretation of optical density measurements using PF4-dependent enzyme-immunoassays. J Thromb Haemost. 2008;6(8):1304-1312. doi: 10.1111/j.1538-7836.2008.03025.x. PubMed

References

1. Pierce W, Mazur J, Greenberg C, Mueller J, Foster J, Lazarchick J. Evaluation of heparin-induced thrombocytopenia (HIT) laboratory testing and the 4Ts scoring system in the intensive care unit. Ann Clin Lab Sci. 2013;43(4):429-435. PubMed
2. Harada MY, Hoang DM, Zaw AA, et al. Overtreatment of heparin-induced thrombocytopenia in the surgical ICU. Crit Care Med. 2017;45(1):28-34. doi:10.1097/ccm.0000000000002002. PubMed
3. Warkentin TE, Sheppard JAI, Heels-Ansdell D, et al. Heparin-induced thrombocytopenia in medical-surgical critical illness. Chest. 2013;144(3):848-858. doi: 10.1378/chest.13-0057. PubMed
4. Linkins LA, Dans AL, Moores LK, et al. Treatment and prevention of heparin-induced thrombocytopenia. Chest. 2012;141(2):e495S-e530S. doi: 10.1378/chest.11-2303. PubMed
5. Cuker A, Arepally GM, Chong BH, et al. American Society of Hematology 2018 guidelines for management of venous thromboembolism: heparin-induced thrombocytopenia. Blood Adv. 2018;2(22):3360-3392. doi: 10.1182/bloodadvances.2018024489. PubMed
6. Lo GK, Juhl D, Warkentin TE, Sigouin CS, Eichler P, Greinacher A. Evaluation of pretest clinical score (4 T’s) for the diagnosis of heparin-induced thrombocytopenia in two clinical settings. J Thromb Haemost. 2006;4(4):759-765. doi: 10.1111/j.1538-7836.2006.01787.x PubMed
7. Cuker A, Cines DB. How I treat heparin-induced thrombocytopenia. Blood. 2012;119(10):2209-2218. doi: 10.1182/blood-2011-11-376293. PubMed
8. Elmer P, Passero FC, Xavier M. Retrospective Analysis of Heparin-Induced Thrombocytopenia Management at a Large Tertiary Hospital. J Hematol. 2014;3(2):27-33. doi: http://dx.doi.org/10.14740/jh157w. 
9. Goldman R, Ustun B, Levine RL. Retrospective cost analysis of testing for HIT antibodies in a community hospital. Blood. 2008;112(11):4544.
10. Cuker A. Heparin-induced thrombocytopenia (HIT) in 2011: an epidemic of overdiagnosis. Thromb Haemost. 2011;106(6):993-994. doi: 10.1160/TH11-09-0677. 
11. Warkentin TE. Heparin-induced thrombocytopenia in critically ill patients. Semin Thromb Hemost. 2015;41(5):49-60. doi: 10.1055/s-0034-1398381. PubMed
12. Caton S, O’Brien E, Pannelay AJ, Cook RG. Assessing the clinical and cost impact of on-demand immunoassay testing for the diagnosis of heparin-induced thrombocytopenia. Thromb Res. 2016;140:155-162. doi: 10.1016/j.thromres.2016.01.025 PubMed
13. Nanwa N, Mittmann N, Knowles S, et al. The direct medical costs associated with suspected heparin-induced thrombocytopenia. Pharmacoeconomics. 2011;29(6):511-520. doi: 10.2165/11584330-000000000-00000. PubMed
14. Cuker A, Gimotty PA, Crowther MA, Warkentin TE. Predictive value of the 4Ts scoring system for heparin-induced thrombocytopenia: a systematic review and meta-analysis. Blood. 2012;120(20):4160-4167. doi: 10.1182/blood-2012-07-443051. PubMed
15. Fiorenza MA, Frazee EN, Personett HA, Dierkhising RA, Schramm GE. Assessment of a modified 4T scoring system for heparin-induced thrombocytopenia in critically ill patients. J Crit Care. 2014;29(3):426-431. doi: 10.1016/j.jcrc.2013.12.010. PubMed
16. Crowther M, Cook D, Guyatt G, et al. Heparin-induced thrombocytopenia in the critically ill: interpreting the 4Ts test in a randomized trial. J Crit Care. 2014;29(3):470.e7-470.e15 doi: 10.1016/j.jcrc.2014.02.004. PubMed
17. Hicks LK, Bering H, Carson KR, et al. The ASH Choosing Wisely campaign: five hematologic tests and treatments to question. Blood. 2013;122(24):3879-3883. doi: 10.1182/blood-2013-07-518423. PubMed
18. Doepker B, Mount KL, Ryder LJ, Gerlach AT, Murphy CV, Philips GS. Bleeding risk factors associated with argatroban therapy in the critically ill. J Thromb Thrombolysis. 2012;34(4):491-498. doi: 10.1007/s11239-012-0758-y. PubMed
19. Marler J, Unzaga J, Stelts S, Oliphant CS. Consequences of treating false positive heparin-induced thrombocytopenia. J Thromb Thrombolysis. 2015;40(4):512-514. doi: 10.1007/s11239-015-1236-0. PubMed
20. Fowler RA, Mittmann N, Geerts W, et al. Cost-effectiveness of dalteparin vs unfractionated heparin for the prevention of venous thromboembolism in critically ill patients. JAMA. 2014;312(20):2135-2145. doi: 10.1001/jama.2014.15101. PubMed
21. Warkentin TE, Sheppard JI, Moore JC, Sigouin CS, Kelton JG. Quantitative interpretation of optical density measurements using PF4-dependent enzyme-immunoassays. J Thromb Haemost. 2008;6(8):1304-1312. doi: 10.1111/j.1538-7836.2008.03025.x. PubMed

Issue
Journal of Hospital Medicine 14(6)
Issue
Journal of Hospital Medicine 14(6)
Page Number
374-376. Published online first April 8, 2019.
Page Number
374-376. Published online first April 8, 2019.
Topics
Article Type
Sections
Article Source

© 2019 Society of Hospital Medicine

Disallow All Ads
Correspondence Location
Eddy Fan, MD, PhD; E-mail: [email protected]; Telephone: 416-340-5483, Twitter: @efan75
Content Gating
Open Access (article Unlocked/Open Access)
Alternative CME
Disqus Comments
Default
Use ProPublica
Hide sidebar & use full width
render the right sidebar.
Attach Teaching Materials
Conference Recap Checkbox
Not Conference Recap
Clinical Edge
Display the Slideshow in this Article
Medscape Article
Display survey writer
Reuters content
Disable Inline Native ads
WebMD Article
Article PDF Media
Attach Teaching Materials
Media Files

Occupational Hazard: Disruptive Behavior in Patients

Article Type
Changed
Mon, 05/13/2019 - 11:05
Accurate reporting of disruptive behavior enables the development of strategies that provide for the safe delivery of health care to patients.

While private or other public health care organizations can refuse to care for patients who have displayed disruptive behavior (DB), the VA Response to Disruptive Behavior of Patients law (38 CFR §17.107) prohibits the Veterans Health Administration (VHA) of the Department of Veterans Affairs (VA) from refusing care to veterans who display DB.1 The VHA defines DB as any behavior that is intimidating, threatening, or dangerous or that has, or could, jeopardize the health or safety of patients, VHA staff, or others.2

VA Response to DB Law

The VA Response to Disruptive Behavior of Patients requires the VHA to provide alternative care options that minimize risk while ensuring services; for example, providing care at a different location and/or time when additional staff are available to assist and monitor the patient. This can provide a unique opportunity to capture data on DB and the results of alternative forms of caring for this population. DB may represent a symptom of a health problem. Further, patients who are refused care because of DB may pose a threat to the community if their medical conditions are not treated or managed properly.

The reason public health care organizations refuse care to persons who display DB is clear: DBs hinder business operations, are financially taxing, and put health care workers at risk.3-10 “In 2009, the VHA spent close to $5.5 million on workers’ compensation and medical expenditures for 425 incidents–or about $130,000 per DB incident (Hodgson M, Drummond D, Van Male L. Unpublished data, 2010).” In another study, 106 of 762 nurses in 1 hospital system reported an assault by a patient, and 30 required medical attention, which resulted in a total cost of $94,156.8 From 2002 to 2013, incidents of serious workplace violence requiring days off for an injured worker to recover on average were 4 times more common in health care than in other industries.6-11 Incidents of patient violence and aggression toward staff transcend specialization; however, hospital nurses and staff from the emergency, rehabilitation and gerontology departments, psychiatric unit, and home-based services are more susceptible and vulnerable to DB incidents than are other types of employees.8,10-19

Data reported by health care staff suggest that patients rather than staff members or visitors initiate > 70% of serious physical attacks against health care workers.9,13,20-23 A 2015 study of VHA health care providers (HCPs) found that > 60% had experienced some form of DB, verbal abuse being the most prevalent, followed by sexual abuse and physical abuse.20 Of 72,000 VHA staff responding to a nationwide survey, 13% experienced, on average, ≥ 1 assault by a veteran (eg, something was thrown at them; they were pushed, kicked, slapped; or were threatened or injured by a weapon).8,21Although 13% may seem small, the incidents may have lasting financial and emotional distress. Risk factors associated with DB include medication nonadherence, history of drug and alcohol use, disappointment with care, history of violence, and untreated mental health concerns.19,24,25 Also, unmarried and young patients are more likely to display violence against health care workers.26

To meet its legal obligations and deliver empathetic care, the VHA documents and analyzes data on all patients who exhibit DB. A local DB Committee (DBC) reviews the data, whether it occurs in an inpatient or outpatient setting, such as community-based outpatient clinics. Once a DB incident is reported, the DBC begins an evidence-based risk evaluation, including the option of contacting the persons who displayed or experienced the DB. Goals are to (1) prevent future DB incidents; (2) detect vulnerabilities in the environment; and (3) collaborate with HCPs and patients to provide optimal care while improving the patient/provider interactions.

 

 

Effects of Disruptive Behavior

DB has negative consequences for both patients and health care workers and results in poor evaluations of care from both groups.27-32 Aside from interfering with safe medical care, DB also impacts care for other patients by delaying access to care and increasing appointment wait times due to employee absenteeism and staff shortages.3,4,20,32,33 For HCPs, patient violence is associated with unwillingness to provide care, briefer treatment periods, and decreases in occupational satisfaction, performance, and commitment.10,28,31 Coping with DB can compromise the HCP’s ability to stay focused and engaged in providing health care, increasing errors.9,15,31

Harmful health effects experienced by HCPs who have been victims of DB include fear, mood disorders, anxiety, all symptoms of psychological distress and posttraumatic stress disorder (PTSD).10,22,30,34-36 In a study of the impact on productivity of PTSD triggered by job-related DB, PTSD symptoms were associated with withdrawal from or minimizing encounters with patients, job turnover, and troubles with thinking.35,36 Nurses with PTSD symptoms who stayed on the job had difficulty staying cognitively focused and managing “higher level work demands that required attention to detail or communication skills.”36 Due to the detrimental impact of DB, it is reasonable to expect a decrease in the quality of care rendered to patients by impacted employees. The quality of care for all patients of HCPs who have experienced a DB is poorer than that of patients of HCPs who have not experienced a DB.29

Reporting Disruptive Behavior

The literature suggests that consistent and effective DB reporting is pivotal to improving the outcome and quality of care for those displaying DB.37-39 To provide high-quality health services to veterans who display DB, the VHA must promote the management and reporting of DB. Without knowledge of the full spectrum of DB events at VHA facilities, efforts to prevent or manage DB and ensure safety may have limited impact.7,37 Reports can be used for clinical decision making to optimize staff training in delivery of quality care while assuring staff safety. More than 80% of DB incidents occur during interactions with patients, thus this is a clinical issue that can affect the outcome of patient care.8,21

Documented DB reports are used to analyze the degree, frequency, and nature of incidents, which might reveal risk factors and develop preventive efforts and training for specific hazards.8,39 Some have argued that implementing a standardized DB reporting system is a crucial first step toward minimizing hazards and improving health care.38,40,41

When DB incidents were recorded through a hospital electronic reporting system and discussed in meetings, staff reported: (1) increased awareness of DB; (2) improved ability to manage DB incidents; and (3) amplified reporting of incidents.38,41,42 These findings support similar results from studies of an intervention implemented at VA Community Living Centers (CLCs) from 2013 to 2017: Staff Training in Assisted Living Residences (STAR-VA).4,12,19 The aim of STAR-VA was to minimize challenging dementia-related DB in CLCs. The intervention initially was established to train direct-care, assisted-living staff to provide better care to older patients displaying DB. Data revealed that documentation of DBs was, the first step to ensuring staff and patient safety.18,40

 

 

VHA Reporting System

In 2013, the VA Office of Inspector General (OIG) found no standardized documentation of DB events across the VA health care system.42 Instead, DB events were documented in multiple records in various locations, including administrative and progress notes in the electronic health record (EHR), police reports, e-mails, or letters submitted to DBC chairs.42 This situation reduced administrators’ ability to consider all relevant information and render appropriate decisions in DB cases.42 In 2015, based on OIG recommendations, the VHA implemented the Disruptive Behavior Reporting System (DBRS) nationwide, which allowed all VHA staff to report DB events. The DBRS was designed to address factors likely to impede reporting and management of DB, namely, complexity of and lack of access to a central reporting system.43,44 The DBRS is currently the primary VHA tool to document DB events.

The DBRS consists of 32 questions in 5 sections relating to the (1) location and time of DB event; (2) reporter; (3) disrupter; (4) DB event details; and (5) the person who experienced (experiencer) the event. The system also provides a list of the types of DB, such as inappropriate communication, bullying and/or intimidation, verbal or written threat of physical harm, physical violence, sexual harassment, sexual assault, and property damage. The DBRS has the potential to provide useful data on DB and DB reporting, such as the typical staff entering data and the number and/or types of DB occurring.

The DBRS complements the preexisting VHA policies and committees for care of veterans who display DB.1-3,14,21,24,25 The VHA Workplace Violence Prevention Program (WVPP) required facilities to submit data on DB events through a Workplace Behavioral Risk report. Data for the report were obtained from police reports, patient safety reports, DBC records, and notes in the EHR. Following implementations of DBRS, the number of DB events per year became a part of facility performance standards.

VHA is creating novel approaches to handling DB that allow health care workers to render care in a safe and effective manner guided by documented information. For example, DBCs can recommend the use of Category I Patient Record Flags (PRFs) following documented DB, which informs staff of the potential risk of DB and provides guidance on protective methods to use when meeting with the patient.2,21,24 A survey of 140 VA hospital chiefs of staff indicated that DBC procedures were related to a decrease in the rates of assaults.1 Additionally, VA provides training for staff in techniques to promote personal safety, such as identifying signs that precede DB, using verbal deescalation, and practicing therapeutic containment.

Resistance to Reporting

Many health care employees and employers are reticent to report DBs.22,31,43,45-48 Studies suggest health care organizations can cultivate a culture that is resistant to reporting DB.49,50 This complicates the ability of the health care system to design and maintain safety protocols and safer treatment plans.3,41,51 Worldwide, < 30% of DBs are reported.47 One barrier may be that supervisors may not wish to acknowledge DBs on their units or may not provide sufficient staff time for training or reporting.31,46,47 HCPs may worry that a DB report will stigmatize patients, especially those who are elderly or have cognitive impairment, brain injury, psychological illness, or developmental disability. Patients with cognitive conditions are reportedly 20% more likely to be violent toward caregivers and providers.31 A dementia diagnosis, for example, is associated with a high likelihood for DB.30,52 More than 80% of DB events displayed by patients with dementia may go unreported.26,31,50,52

 

 

Some clinicians may attribute DB to physiologic conditions that need to be treated, not reported. However, employers can face various legal liabilities if steps are not taken to protect employees.47,51 Federal and state statutes require that organizations provide a healthy and safe employment environment for workers. This requires that employers institute reasonable protective measures, such as procedures to intervene, policies on addressing DB incidents, and/or training to minimize or deescalate DB.51,53 Also, employees may sue employers if security measures are inadequate or deficient in properly investigating current and past evidence of DB or identifying vulnerabilities in the workplace. Unwillingness to investigate DB and safety-related workplace concerns have contributed to increased workplace violence and legal liability.52,53 The mission of caring and trust is consistent with assuring a safe environment.

Training and Empathetic Care

To combat cultural resistance to reporting DBs, more and perhaps different contextual approaches to education and training may be needed that address ethical dilemmas and concerns of providers. The success of training relies on administrators supporting staff in reporting DB. Training must address providers’ conflicting beliefs and assist with identifying strategies to provide the best possible care for patients who display DB.1,38 HCPs are less likely to document a DB if they feel that administrators are creating documentation that will have negative consequences for a patient. Thus, leadership is responsible for ensuring that misconceptions are dispelled through training and other efforts and information on how reported DB data will be used is communicated through strategic channels.

Education and training must consider empathic care that attempts to understand why patients behave as they do through the information gathered.55 Empathy in health care is multifaceted: It involves comprehending a patient’s viewpoint, circumstances, and feelings and the capacity to analyze whether one is comprehending these accurately in order to demonstrate supportive care.54,55

Improving patient and staff interaction once a problematic behavior is identified is the aim of empathic care. Increasing empathic care can improve compassionate, patient-centered interactions that begin once the patient seeks care. This approach has proven to decrease DB by patients with dementia and improve their care, lessen staff problems during interactions, and increase staff morale.20 Experts call for the adoption of an interpersonal approach to patient encounters, and there is evidence that creating organizational change by moving toward compassionate care can lead to a positive impact for patients.54,55

Future Studies

There are growth opportunities in utilization of the DBRS. Analysis of the DBRS database by the VA Central Office (VACO) showed that the system is underutilized by facilities across the VA system.56 In response to this current underutilization, VACO is taking steps to close these gaps through increasing training to staff and promotion of the use of the DBRS. A 2015 pilot study of VHA providers showed that > 70% of providers had experienced a DB as defined by VHA, but only 34% of them reported their most recently experienced DB within the past 12 months.20 Thus, DBRS use must be studied within the context that patient-perpetrated DB is underreported in health care organizations.5,9,29,41,43,57,58 Studies addressing national DBRS utilization patterns and the cost associated with implementing the DBRS also are needed. One study suggests that there is an association between measures of facility complexity and staff perceptions of safety, which should be considered in analyzing DBRS usage.57 Studies addressing the role of the DBRS and misconceptions that the tool may represent a punitive tool also are needed. VHA should consider how the attribution “disruptive behavior” assigns a negative connotation and leads HCPs to avoid using the DBRS. Additionally, DB reporting may increase when HCPs understand that DB reporting is part of the comprehensive, consultative strategy to provide the best care to patients.

 

 

Conclusion

Accurate reporting of DB events enables the development of strategies for multidisciplinary teams to work together to minimize hazards and to provide interventions that provide for the safe delivery of health care to all patients. Improving reporting ensures there is an accurate representation of how disruptive events impact care provided within a facility—and what types of variables may be associated with increased risk for these types of events.

Additionally, ensuring that reporting is maximized also provides the VHA with opportunities for DBCs to offer evidence-based risk assessment of violence and consultation to staff members who may benefit from improved competencies in working with patients who display DB. These potential improvements are consistent with the VHA I CARE values and will provide data that can inform recommendations for health care in other agencies/health care organizations.

Acknowledgments
This work was supported by the Center of Innovation on Disability and Rehabilitation Research (CINDRR) of the Health Services Research and Development Service, Office of Research and Development, Department of Veterans Affairs.

References

1. Hodgson MJ, Mohr DC, Drummond DJ, Bell M, Van Male L. Managing disruptive patients in health care: necessary solutions to a difficult problem. Am J Ind Med. 2012;55(11):1009-1017.

2. US Department of Veterans Affairs, Veterans Health Administration. VHA Directive 2010-053. Patient Record Flags. https://www.va.gov/vhapublications/ViewPublication.asp?pub_ID=2341 Published December 3, 2010. Accessed March 29, 2019.

3. US Department of Veterans Affairs, Veterans Health Administration. VHA Directive 2012-026. Sexual Assaults and Other Defined Public Safety Incidents in VHA Facilities. https://www.va.gov/vhapublications/ViewPublication.asp?pub_ID=2797. Published September 27, 2012. Accessed March 29, 2019.

4. Curyto KJ, McCurry SM, Luci K, Karlin BE, Teri L, Karel MJ. Managing challenging behaviors of dementia in veterans: identifying and changing activators and consequences using STAR-VA. J Gerontol Nurs. 2017;43(2):33-43.

5. Speroni KG, Fitch T, Dawson E, Dugan L, Atherton M. Incidence and cost of nurse workplace violence perpetrated by hospital patients or patient visitors. J Emerg Nurs. 2014;40(3):218-228.

6. Phillips JP. Workplace violence against health care workers in the United States. NEJM. 2016;374(17):1661-1669.

7. Janocha JA, Smith RT. Workplace safety and health in the health care and social assistance industry, 2003–07. https://www.bls.gov/opub/mlr/cwc/workplace-safety-and-health-in-the-health-care-and-social-assistance-industry-2003-07.pdf. Published August 30, 2010. Accessed February 19, 2019.

8. US Department of Labor, Occupational Safety and Health Administration. Workplace violence in healthcare: understanding the challenge. https://www.osha.gov/Publications/OSHA3826.pdf. Published December 2015. Accessed February 19, 2019.

9. US Department of Labor, Occupational Safety and Health Administration. Prevention of Workplace Violence in Healthcare and Social Assistance. Occupational Safety and Health Administration, https://www.govinfo.gov/content/pkg/FR-2016-12-07/pdf/2016-29197.pdf. Accessed January 20, 2017.

10. Gerberich SG, Church TR, McGovern PM, et al. An epidemiological study of the magnitude and consequences of work related violence: the Minnesota Nurses’ Study. Occup Environ Med. 2004;61(6):495-503.

11. Sherman MF, Gershon RRM, Samar SM, Pearson JM, Canton AN, Damsky MR. Safety factors predictive of job satisfaction and job retention among home healthcare aides. J Occup Environ Med. 2008;50(12):1430-1441.

12. Karel MJ, Teri L, McConnell E, Visnic S, Karlin BE. Effectiveness of expanded implementation of STAR-VA for managing dementia-related behaviors among veterans. Gerontologist. 2016;56(1):126-134.

13. US Department of Labor, Bureau of Labor Statistics. Nonfatal occupational injuries and illnesses requiring days away from work. https://www.bls.gov/news.release/archives/osh2_11192015.htm. Published November 19, 2015.

14. Beech B, Leather P. Workplace violence in the health care sector: A review of staff training and integration of training evaluation models. Aggression Violent Behav. 2006;11(1):27-43.

15. Campbell CL, McCoy S, Burg MA, Hoffman N. Enhancing home care staff safety through reducing client aggression and violence in noninstitutional care settings: a systematic review. Home Health Care Manage Pract. 2014;26(1):3-10.

16. Gallant-Roman MA. Strategies and tools to reduce workplace violence. AAOHNJ. 2008;56(11):449-454.

17. Weinberger LE, Sreenivasan S, Smee DE, McGuire J, Garrick T. Balancing safety against obstruction to health care access: an examination of behavioral flags in the VA health care system. J Threat Assess Manage. 2018;5(1):35-41.

18. Elbogen EB, Johnson SC, Wagner HR, et al. Protective factors and risk modification of violence in Iraq and Afghanistan war veterans. J Clin Psychiatry. 2012;73(6):e767-e773.

19. Karlin BE, Visnic S, McGee JS, Teri L. Results from the multisite implementation of STAR-VA: a multicomponent psychosocial intervention for managing challenging dementia-related behaviors of veterans. Psychol Serv. 2014;11(2):200-208.

20. Semeah LM, Campbell CL, Cowper DC, Peet AC. Serving our homeless veterans: patient perpetrated violence as a barrier to health care access. J Pub Nonprofit Aff. 2017;3(2):223-234.

21. Hodgson MJ, Reed R, Craig T, et al. Violence in healthcare facilities: lessons from the Veterans Health Administration. J Occup Environ Med. 2004;46(11):1158-1165.

22. Farrell GA, Bobrowski C, Bobrowski P. Scoping workplace aggression in nursing: findings from an Australian study. J Adv Nurs. 2006;55(6):778-787.

23. Barling J, Rogers AG, Kelloway EK. Behind closed doors: in-home workers’ experience of sexual harassment and workplace violence. J Occup Health Psychol. 2001;6(3):255-269.

24. Pompeii LA, Schoenfisch AL, Lipscomb HJ, Dement JM, Smith CD, Upadhyaya M. Physical assault, physical threat, and verbal abuse perpetrated against hospital workers by patients or visitors in six U.S. hospitals. Am J Ind Med. 2015;58(11):1194-1204.

25. Sippel LM, Mota NP, Kachadourian LK, et al. The burden of hostility in U.S. veterans: results from the National Health and Resilience in Veterans Study. Psychiatry Res. 2016;243(suppl C):421-430.

26. Campbell C. Patient Violence and Aggression in Non-Institutional Health Care Settings: Predictors of Reporting By Healthcare Providers [doctoral dissertation]. Orlando: University of Central Florida; 2016.

27. Galinsky T, Feng HA, Streit J, et al. Risk factors associated with patient assaults of home healthcare workers. Rehabil Nurs. 2010;35(5):206-215.

28. Campbell CL. Incident reporting by health-care workers in noninstitutional care settings. Trauma, Violence Abuse. 2017;18(4):445-456.

29. Arnetz JE, Arnetz BB. Violence towards health care staff and possible effects on the quality of patient care. Soc Sci Med. 2001;52(3):417-427.

30. Gates D, Fitzwater E, Succop P. Relationships of stressors, strain, and anger to caregiver assaults. Issues Ment Health Nurs. 2003;24(8):775-793.

31. Brillhart B, Kruse B, Heard L. Safety concerns for rehabilitation nurses in home care. Rehabil Nurs. 2004;29(6):227-229.

32. Taylor H. Patient violence against clinicians: managing the risk. Innov Clin Neurosci. 2013;10(3):40-42.

33. US Department of Veterans Affairs, Office of Public and Intergovernmental Affairs. The Joint Commission releases results of surveys of the VA health care system. https://www.va.gov/opa/pressrel/pressrelease.cfm?id=2808. Updated August 5, 2014. Accessed February 19, 2019.

34. Büssing A, Höge T. Aggression and violence against home care workers. J Occup Health Psychol. 2004;9(3):206-219.

35. Geiger-Brown J, Muntaner C, McPhaul K, Lipscomb J, Trinkoff A. Abuse and violence during home care work as predictor of worker depression. Home Health Care Serv Q. 2007;26(1):59-77.

36. Gates DM, Gillespie GL, Succop P. Violence against nurses and its impact on stress and productivity. Nurs Econ. 2011;29(2):59-66.

37. Petterson IL, Arnetz BB. Psychosocial stressors and well-being in health care workers: the impact of an intervention program. Soc Sci Med. 1998;47(11):1763-1772.

38. Arnetz JE, Arnetz BB. Implementation and evaluation of a practical intervention programme for dealing with violence towards health care workers. J Adv Nurs. 2000;31(3):668-680.

39. Arnetz JE, Hamblin L, Russell J, et al. Preventing patient-to-worker violence in hospitals: outcome of a randomized controlled intervention. J Occup Environ Med. 2017;59(1):18-27.

40. Elbogen EB, Tomkins AJ, Pothuloori AP, Scalora MJ. Documentation of violence risk information in psychiatric hospital patient charts: an empirical examination. J Am Acad Psychiatry Law. 2003;31(1):58-64.

41. Winsvold Prang I, Jelson-Jorgensen LP. Should I report? A qualitative study of barriers to incident reporting among nurses working in nursing homes. Geriatr Nurs. 2014;35(6):441-447.

42. US Department of Veterans Affairs, Office of Inspector General. Healthcare inspection: management of disruptive patient behavior at VA medical facilities. Report No. 11-02585-129. https://www.va.gov/oig/pubs/VAOIG-11-02585-129.pdf. Published Mrach 7, 2013. Accessed February 21, 2019.

43. Lipscomb J, London M. Not Part of the Job: How to Take a Stand Against Violence in the Work Setting. Silver Spring, MD: American Nurses Association; 2015.

44. May DD, Grubbs LM. The extent, nature, and precipitating factors of nurse assault among three groups of registered nurses in a regional medical center. J Emerg Nurs. 2002;28(1):11-17.

45. Wharton TC, Ford BK. What is known about dementia care recipient violence and aggression against caregivers? J Gerontol Soc Work. 2014;57(5):460-477.

46. Brennan C, Worrall-Davies A, McMillan D, Gilbody S, House A. The hospital anxiety and depression scale: a diagnostic meta-analysis of case-finding ability. J Psychosom Res. 2010;69(4):371-378.

47. McPhaul K, Lipscomb J, Johnson J. Assessing risk for violence on home health visits. Home Healthc Nurse. 2010;28(5):278-289.

48. McPhaul KM, London M, Murrett K, Flannery K, Rosen J, Lipscomb J. Environmental evaluation for workplace violence in healthcare and social services. J Safety Res. 2008;39(2):237-250.

49. Kelly JA, Somlai AM, DiFranceisco WJ, et al. Bridging the gap between the science and service of HIV prevention: transferring effective research-based HIV prevention interventions to community AIDS service providers. Am J Public Health. 2000;90(7):1082-1088.

50. Pawlin S. Reporting violence. Emerg Nurse. 2008;16(4):16-21.

51. Brakel SJ. Legal liability and workplace violence. J Am Acad Psychiatry Law. 1998;26(4):553-562.

52. Neuman JH, Baron RA. Workplace violence and workplace aggression: evidence concerning specific forms, potential causes, and preferred targets. J Manage. 1998;24(3):391-419.53. Ferns T, Chojnacka I. Angels and swingers, matrons and sinners: nursing stereotypes. Br J Nurs. 2005;14(19):1028-1032.

54. Mercer SW, Reynolds WJ. Empathy and quality of care. Br J Gen Pract 2002;52(suppl):S9-S12.

55. Lee TH. An Epidemic of Empathy in Healthcare: How to Deliver Compassionate, Connected Patient Care That Creates a Competitive Advantage. Columbus, OH: McGraw-Hill Education; 2015.

56. US Department of Veterans Affairs, Veterans Health Administrastion. Veterans Health Administration workplace violence prevention program (WVPP): disruptive behavior reporting system utilization report. Published 2017. https://vaww.portal2.va.gov/sites/wvpp/Shared%20Documents/DBRS%20Utilization%20Reports/FY2017%20DBRS%20Quarterly%20Utilization%20Report%20(Quarter%201).pdf. [Source not verified.]

57. Campbell CL, Burg, MA, Gammonley D. Measures for incident reporting of patient violence and aggression towards healthcare providers: a systematic review. Aggression Violent Behav. 2015;25(part B):314-322.

58. Carney PT, West P, Neily J, Mills PD, Bagian JP. The effect of facility complexity on perceptions of safety climate in the operating room: size matters. Am J Med Qual. 2010;25(6):457-461.

Article PDF
Author and Disclosure Information

Luz Semeah is a Health Science Specialist, Diane Cowper- Ripley is Director, Magaly Freytes and Huanguang Jia are Research Health Scientists, all at the Center of Innovation on Disability and Rehabilitation Research (CINDRR) at the North Florida/South Georgia Veterans Health System (NF/SGVHS) in Gainesville, Florida. Colleen Campbell is a Licensed Clinical Social Worker, and Connie Uphold is a Health Scientist at CINDRR and the Associate Director of Implementation and Outcomes Research at the Geriatric Research Education and Clinical Center at NF/SGVHS. When this article was written, Destiny Hart was a Research Assistant at CINDRR and is currently a Student at the University of Florida in Gainesville. Diane Cowper-Ripley is an Affiliated Associate Professor in the Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida. Colleen Campbell is an Instructor at the University of Central Florida School of Social Work. Huanguang Jia is a Professor at the College of Public Health and Health Professions and Connie Uphold is an Associate Professor in the Department of Aging and Geriatrics Research, College of Medicine; both at the University of Florida.
Correspondence: Luz Semeah ([email protected])

Author disclosures
The authors report no actual or potential conflicts of interest with regard to this article.

Disclaimer
The opinions expressed herein are those of the authors and do not necessarily reflect those of Federal Practitioner, Frontline Medical Communications Inc., the US Government, or any of its agencies.

Issue
Federal Practitioner - 36(4)a
Publications
Topics
Page Number
158-163
Sections
Author and Disclosure Information

Luz Semeah is a Health Science Specialist, Diane Cowper- Ripley is Director, Magaly Freytes and Huanguang Jia are Research Health Scientists, all at the Center of Innovation on Disability and Rehabilitation Research (CINDRR) at the North Florida/South Georgia Veterans Health System (NF/SGVHS) in Gainesville, Florida. Colleen Campbell is a Licensed Clinical Social Worker, and Connie Uphold is a Health Scientist at CINDRR and the Associate Director of Implementation and Outcomes Research at the Geriatric Research Education and Clinical Center at NF/SGVHS. When this article was written, Destiny Hart was a Research Assistant at CINDRR and is currently a Student at the University of Florida in Gainesville. Diane Cowper-Ripley is an Affiliated Associate Professor in the Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida. Colleen Campbell is an Instructor at the University of Central Florida School of Social Work. Huanguang Jia is a Professor at the College of Public Health and Health Professions and Connie Uphold is an Associate Professor in the Department of Aging and Geriatrics Research, College of Medicine; both at the University of Florida.
Correspondence: Luz Semeah ([email protected])

Author disclosures
The authors report no actual or potential conflicts of interest with regard to this article.

Disclaimer
The opinions expressed herein are those of the authors and do not necessarily reflect those of Federal Practitioner, Frontline Medical Communications Inc., the US Government, or any of its agencies.

Author and Disclosure Information

Luz Semeah is a Health Science Specialist, Diane Cowper- Ripley is Director, Magaly Freytes and Huanguang Jia are Research Health Scientists, all at the Center of Innovation on Disability and Rehabilitation Research (CINDRR) at the North Florida/South Georgia Veterans Health System (NF/SGVHS) in Gainesville, Florida. Colleen Campbell is a Licensed Clinical Social Worker, and Connie Uphold is a Health Scientist at CINDRR and the Associate Director of Implementation and Outcomes Research at the Geriatric Research Education and Clinical Center at NF/SGVHS. When this article was written, Destiny Hart was a Research Assistant at CINDRR and is currently a Student at the University of Florida in Gainesville. Diane Cowper-Ripley is an Affiliated Associate Professor in the Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida. Colleen Campbell is an Instructor at the University of Central Florida School of Social Work. Huanguang Jia is a Professor at the College of Public Health and Health Professions and Connie Uphold is an Associate Professor in the Department of Aging and Geriatrics Research, College of Medicine; both at the University of Florida.
Correspondence: Luz Semeah ([email protected])

Author disclosures
The authors report no actual or potential conflicts of interest with regard to this article.

Disclaimer
The opinions expressed herein are those of the authors and do not necessarily reflect those of Federal Practitioner, Frontline Medical Communications Inc., the US Government, or any of its agencies.

Article PDF
Article PDF
Related Articles
Accurate reporting of disruptive behavior enables the development of strategies that provide for the safe delivery of health care to patients.
Accurate reporting of disruptive behavior enables the development of strategies that provide for the safe delivery of health care to patients.

While private or other public health care organizations can refuse to care for patients who have displayed disruptive behavior (DB), the VA Response to Disruptive Behavior of Patients law (38 CFR §17.107) prohibits the Veterans Health Administration (VHA) of the Department of Veterans Affairs (VA) from refusing care to veterans who display DB.1 The VHA defines DB as any behavior that is intimidating, threatening, or dangerous or that has, or could, jeopardize the health or safety of patients, VHA staff, or others.2

VA Response to DB Law

The VA Response to Disruptive Behavior of Patients requires the VHA to provide alternative care options that minimize risk while ensuring services; for example, providing care at a different location and/or time when additional staff are available to assist and monitor the patient. This can provide a unique opportunity to capture data on DB and the results of alternative forms of caring for this population. DB may represent a symptom of a health problem. Further, patients who are refused care because of DB may pose a threat to the community if their medical conditions are not treated or managed properly.

The reason public health care organizations refuse care to persons who display DB is clear: DBs hinder business operations, are financially taxing, and put health care workers at risk.3-10 “In 2009, the VHA spent close to $5.5 million on workers’ compensation and medical expenditures for 425 incidents–or about $130,000 per DB incident (Hodgson M, Drummond D, Van Male L. Unpublished data, 2010).” In another study, 106 of 762 nurses in 1 hospital system reported an assault by a patient, and 30 required medical attention, which resulted in a total cost of $94,156.8 From 2002 to 2013, incidents of serious workplace violence requiring days off for an injured worker to recover on average were 4 times more common in health care than in other industries.6-11 Incidents of patient violence and aggression toward staff transcend specialization; however, hospital nurses and staff from the emergency, rehabilitation and gerontology departments, psychiatric unit, and home-based services are more susceptible and vulnerable to DB incidents than are other types of employees.8,10-19

Data reported by health care staff suggest that patients rather than staff members or visitors initiate > 70% of serious physical attacks against health care workers.9,13,20-23 A 2015 study of VHA health care providers (HCPs) found that > 60% had experienced some form of DB, verbal abuse being the most prevalent, followed by sexual abuse and physical abuse.20 Of 72,000 VHA staff responding to a nationwide survey, 13% experienced, on average, ≥ 1 assault by a veteran (eg, something was thrown at them; they were pushed, kicked, slapped; or were threatened or injured by a weapon).8,21Although 13% may seem small, the incidents may have lasting financial and emotional distress. Risk factors associated with DB include medication nonadherence, history of drug and alcohol use, disappointment with care, history of violence, and untreated mental health concerns.19,24,25 Also, unmarried and young patients are more likely to display violence against health care workers.26

To meet its legal obligations and deliver empathetic care, the VHA documents and analyzes data on all patients who exhibit DB. A local DB Committee (DBC) reviews the data, whether it occurs in an inpatient or outpatient setting, such as community-based outpatient clinics. Once a DB incident is reported, the DBC begins an evidence-based risk evaluation, including the option of contacting the persons who displayed or experienced the DB. Goals are to (1) prevent future DB incidents; (2) detect vulnerabilities in the environment; and (3) collaborate with HCPs and patients to provide optimal care while improving the patient/provider interactions.

 

 

Effects of Disruptive Behavior

DB has negative consequences for both patients and health care workers and results in poor evaluations of care from both groups.27-32 Aside from interfering with safe medical care, DB also impacts care for other patients by delaying access to care and increasing appointment wait times due to employee absenteeism and staff shortages.3,4,20,32,33 For HCPs, patient violence is associated with unwillingness to provide care, briefer treatment periods, and decreases in occupational satisfaction, performance, and commitment.10,28,31 Coping with DB can compromise the HCP’s ability to stay focused and engaged in providing health care, increasing errors.9,15,31

Harmful health effects experienced by HCPs who have been victims of DB include fear, mood disorders, anxiety, all symptoms of psychological distress and posttraumatic stress disorder (PTSD).10,22,30,34-36 In a study of the impact on productivity of PTSD triggered by job-related DB, PTSD symptoms were associated with withdrawal from or minimizing encounters with patients, job turnover, and troubles with thinking.35,36 Nurses with PTSD symptoms who stayed on the job had difficulty staying cognitively focused and managing “higher level work demands that required attention to detail or communication skills.”36 Due to the detrimental impact of DB, it is reasonable to expect a decrease in the quality of care rendered to patients by impacted employees. The quality of care for all patients of HCPs who have experienced a DB is poorer than that of patients of HCPs who have not experienced a DB.29

Reporting Disruptive Behavior

The literature suggests that consistent and effective DB reporting is pivotal to improving the outcome and quality of care for those displaying DB.37-39 To provide high-quality health services to veterans who display DB, the VHA must promote the management and reporting of DB. Without knowledge of the full spectrum of DB events at VHA facilities, efforts to prevent or manage DB and ensure safety may have limited impact.7,37 Reports can be used for clinical decision making to optimize staff training in delivery of quality care while assuring staff safety. More than 80% of DB incidents occur during interactions with patients, thus this is a clinical issue that can affect the outcome of patient care.8,21

Documented DB reports are used to analyze the degree, frequency, and nature of incidents, which might reveal risk factors and develop preventive efforts and training for specific hazards.8,39 Some have argued that implementing a standardized DB reporting system is a crucial first step toward minimizing hazards and improving health care.38,40,41

When DB incidents were recorded through a hospital electronic reporting system and discussed in meetings, staff reported: (1) increased awareness of DB; (2) improved ability to manage DB incidents; and (3) amplified reporting of incidents.38,41,42 These findings support similar results from studies of an intervention implemented at VA Community Living Centers (CLCs) from 2013 to 2017: Staff Training in Assisted Living Residences (STAR-VA).4,12,19 The aim of STAR-VA was to minimize challenging dementia-related DB in CLCs. The intervention initially was established to train direct-care, assisted-living staff to provide better care to older patients displaying DB. Data revealed that documentation of DBs was, the first step to ensuring staff and patient safety.18,40

 

 

VHA Reporting System

In 2013, the VA Office of Inspector General (OIG) found no standardized documentation of DB events across the VA health care system.42 Instead, DB events were documented in multiple records in various locations, including administrative and progress notes in the electronic health record (EHR), police reports, e-mails, or letters submitted to DBC chairs.42 This situation reduced administrators’ ability to consider all relevant information and render appropriate decisions in DB cases.42 In 2015, based on OIG recommendations, the VHA implemented the Disruptive Behavior Reporting System (DBRS) nationwide, which allowed all VHA staff to report DB events. The DBRS was designed to address factors likely to impede reporting and management of DB, namely, complexity of and lack of access to a central reporting system.43,44 The DBRS is currently the primary VHA tool to document DB events.

The DBRS consists of 32 questions in 5 sections relating to the (1) location and time of DB event; (2) reporter; (3) disrupter; (4) DB event details; and (5) the person who experienced (experiencer) the event. The system also provides a list of the types of DB, such as inappropriate communication, bullying and/or intimidation, verbal or written threat of physical harm, physical violence, sexual harassment, sexual assault, and property damage. The DBRS has the potential to provide useful data on DB and DB reporting, such as the typical staff entering data and the number and/or types of DB occurring.

The DBRS complements the preexisting VHA policies and committees for care of veterans who display DB.1-3,14,21,24,25 The VHA Workplace Violence Prevention Program (WVPP) required facilities to submit data on DB events through a Workplace Behavioral Risk report. Data for the report were obtained from police reports, patient safety reports, DBC records, and notes in the EHR. Following implementations of DBRS, the number of DB events per year became a part of facility performance standards.

VHA is creating novel approaches to handling DB that allow health care workers to render care in a safe and effective manner guided by documented information. For example, DBCs can recommend the use of Category I Patient Record Flags (PRFs) following documented DB, which informs staff of the potential risk of DB and provides guidance on protective methods to use when meeting with the patient.2,21,24 A survey of 140 VA hospital chiefs of staff indicated that DBC procedures were related to a decrease in the rates of assaults.1 Additionally, VA provides training for staff in techniques to promote personal safety, such as identifying signs that precede DB, using verbal deescalation, and practicing therapeutic containment.

Resistance to Reporting

Many health care employees and employers are reticent to report DBs.22,31,43,45-48 Studies suggest health care organizations can cultivate a culture that is resistant to reporting DB.49,50 This complicates the ability of the health care system to design and maintain safety protocols and safer treatment plans.3,41,51 Worldwide, < 30% of DBs are reported.47 One barrier may be that supervisors may not wish to acknowledge DBs on their units or may not provide sufficient staff time for training or reporting.31,46,47 HCPs may worry that a DB report will stigmatize patients, especially those who are elderly or have cognitive impairment, brain injury, psychological illness, or developmental disability. Patients with cognitive conditions are reportedly 20% more likely to be violent toward caregivers and providers.31 A dementia diagnosis, for example, is associated with a high likelihood for DB.30,52 More than 80% of DB events displayed by patients with dementia may go unreported.26,31,50,52

 

 

Some clinicians may attribute DB to physiologic conditions that need to be treated, not reported. However, employers can face various legal liabilities if steps are not taken to protect employees.47,51 Federal and state statutes require that organizations provide a healthy and safe employment environment for workers. This requires that employers institute reasonable protective measures, such as procedures to intervene, policies on addressing DB incidents, and/or training to minimize or deescalate DB.51,53 Also, employees may sue employers if security measures are inadequate or deficient in properly investigating current and past evidence of DB or identifying vulnerabilities in the workplace. Unwillingness to investigate DB and safety-related workplace concerns have contributed to increased workplace violence and legal liability.52,53 The mission of caring and trust is consistent with assuring a safe environment.

Training and Empathetic Care

To combat cultural resistance to reporting DBs, more and perhaps different contextual approaches to education and training may be needed that address ethical dilemmas and concerns of providers. The success of training relies on administrators supporting staff in reporting DB. Training must address providers’ conflicting beliefs and assist with identifying strategies to provide the best possible care for patients who display DB.1,38 HCPs are less likely to document a DB if they feel that administrators are creating documentation that will have negative consequences for a patient. Thus, leadership is responsible for ensuring that misconceptions are dispelled through training and other efforts and information on how reported DB data will be used is communicated through strategic channels.

Education and training must consider empathic care that attempts to understand why patients behave as they do through the information gathered.55 Empathy in health care is multifaceted: It involves comprehending a patient’s viewpoint, circumstances, and feelings and the capacity to analyze whether one is comprehending these accurately in order to demonstrate supportive care.54,55

Improving patient and staff interaction once a problematic behavior is identified is the aim of empathic care. Increasing empathic care can improve compassionate, patient-centered interactions that begin once the patient seeks care. This approach has proven to decrease DB by patients with dementia and improve their care, lessen staff problems during interactions, and increase staff morale.20 Experts call for the adoption of an interpersonal approach to patient encounters, and there is evidence that creating organizational change by moving toward compassionate care can lead to a positive impact for patients.54,55

Future Studies

There are growth opportunities in utilization of the DBRS. Analysis of the DBRS database by the VA Central Office (VACO) showed that the system is underutilized by facilities across the VA system.56 In response to this current underutilization, VACO is taking steps to close these gaps through increasing training to staff and promotion of the use of the DBRS. A 2015 pilot study of VHA providers showed that > 70% of providers had experienced a DB as defined by VHA, but only 34% of them reported their most recently experienced DB within the past 12 months.20 Thus, DBRS use must be studied within the context that patient-perpetrated DB is underreported in health care organizations.5,9,29,41,43,57,58 Studies addressing national DBRS utilization patterns and the cost associated with implementing the DBRS also are needed. One study suggests that there is an association between measures of facility complexity and staff perceptions of safety, which should be considered in analyzing DBRS usage.57 Studies addressing the role of the DBRS and misconceptions that the tool may represent a punitive tool also are needed. VHA should consider how the attribution “disruptive behavior” assigns a negative connotation and leads HCPs to avoid using the DBRS. Additionally, DB reporting may increase when HCPs understand that DB reporting is part of the comprehensive, consultative strategy to provide the best care to patients.

 

 

Conclusion

Accurate reporting of DB events enables the development of strategies for multidisciplinary teams to work together to minimize hazards and to provide interventions that provide for the safe delivery of health care to all patients. Improving reporting ensures there is an accurate representation of how disruptive events impact care provided within a facility—and what types of variables may be associated with increased risk for these types of events.

Additionally, ensuring that reporting is maximized also provides the VHA with opportunities for DBCs to offer evidence-based risk assessment of violence and consultation to staff members who may benefit from improved competencies in working with patients who display DB. These potential improvements are consistent with the VHA I CARE values and will provide data that can inform recommendations for health care in other agencies/health care organizations.

Acknowledgments
This work was supported by the Center of Innovation on Disability and Rehabilitation Research (CINDRR) of the Health Services Research and Development Service, Office of Research and Development, Department of Veterans Affairs.

While private or other public health care organizations can refuse to care for patients who have displayed disruptive behavior (DB), the VA Response to Disruptive Behavior of Patients law (38 CFR §17.107) prohibits the Veterans Health Administration (VHA) of the Department of Veterans Affairs (VA) from refusing care to veterans who display DB.1 The VHA defines DB as any behavior that is intimidating, threatening, or dangerous or that has, or could, jeopardize the health or safety of patients, VHA staff, or others.2

VA Response to DB Law

The VA Response to Disruptive Behavior of Patients requires the VHA to provide alternative care options that minimize risk while ensuring services; for example, providing care at a different location and/or time when additional staff are available to assist and monitor the patient. This can provide a unique opportunity to capture data on DB and the results of alternative forms of caring for this population. DB may represent a symptom of a health problem. Further, patients who are refused care because of DB may pose a threat to the community if their medical conditions are not treated or managed properly.

The reason public health care organizations refuse care to persons who display DB is clear: DBs hinder business operations, are financially taxing, and put health care workers at risk.3-10 “In 2009, the VHA spent close to $5.5 million on workers’ compensation and medical expenditures for 425 incidents–or about $130,000 per DB incident (Hodgson M, Drummond D, Van Male L. Unpublished data, 2010).” In another study, 106 of 762 nurses in 1 hospital system reported an assault by a patient, and 30 required medical attention, which resulted in a total cost of $94,156.8 From 2002 to 2013, incidents of serious workplace violence requiring days off for an injured worker to recover on average were 4 times more common in health care than in other industries.6-11 Incidents of patient violence and aggression toward staff transcend specialization; however, hospital nurses and staff from the emergency, rehabilitation and gerontology departments, psychiatric unit, and home-based services are more susceptible and vulnerable to DB incidents than are other types of employees.8,10-19

Data reported by health care staff suggest that patients rather than staff members or visitors initiate > 70% of serious physical attacks against health care workers.9,13,20-23 A 2015 study of VHA health care providers (HCPs) found that > 60% had experienced some form of DB, verbal abuse being the most prevalent, followed by sexual abuse and physical abuse.20 Of 72,000 VHA staff responding to a nationwide survey, 13% experienced, on average, ≥ 1 assault by a veteran (eg, something was thrown at them; they were pushed, kicked, slapped; or were threatened or injured by a weapon).8,21Although 13% may seem small, the incidents may have lasting financial and emotional distress. Risk factors associated with DB include medication nonadherence, history of drug and alcohol use, disappointment with care, history of violence, and untreated mental health concerns.19,24,25 Also, unmarried and young patients are more likely to display violence against health care workers.26

To meet its legal obligations and deliver empathetic care, the VHA documents and analyzes data on all patients who exhibit DB. A local DB Committee (DBC) reviews the data, whether it occurs in an inpatient or outpatient setting, such as community-based outpatient clinics. Once a DB incident is reported, the DBC begins an evidence-based risk evaluation, including the option of contacting the persons who displayed or experienced the DB. Goals are to (1) prevent future DB incidents; (2) detect vulnerabilities in the environment; and (3) collaborate with HCPs and patients to provide optimal care while improving the patient/provider interactions.

 

 

Effects of Disruptive Behavior

DB has negative consequences for both patients and health care workers and results in poor evaluations of care from both groups.27-32 Aside from interfering with safe medical care, DB also impacts care for other patients by delaying access to care and increasing appointment wait times due to employee absenteeism and staff shortages.3,4,20,32,33 For HCPs, patient violence is associated with unwillingness to provide care, briefer treatment periods, and decreases in occupational satisfaction, performance, and commitment.10,28,31 Coping with DB can compromise the HCP’s ability to stay focused and engaged in providing health care, increasing errors.9,15,31

Harmful health effects experienced by HCPs who have been victims of DB include fear, mood disorders, anxiety, all symptoms of psychological distress and posttraumatic stress disorder (PTSD).10,22,30,34-36 In a study of the impact on productivity of PTSD triggered by job-related DB, PTSD symptoms were associated with withdrawal from or minimizing encounters with patients, job turnover, and troubles with thinking.35,36 Nurses with PTSD symptoms who stayed on the job had difficulty staying cognitively focused and managing “higher level work demands that required attention to detail or communication skills.”36 Due to the detrimental impact of DB, it is reasonable to expect a decrease in the quality of care rendered to patients by impacted employees. The quality of care for all patients of HCPs who have experienced a DB is poorer than that of patients of HCPs who have not experienced a DB.29

Reporting Disruptive Behavior

The literature suggests that consistent and effective DB reporting is pivotal to improving the outcome and quality of care for those displaying DB.37-39 To provide high-quality health services to veterans who display DB, the VHA must promote the management and reporting of DB. Without knowledge of the full spectrum of DB events at VHA facilities, efforts to prevent or manage DB and ensure safety may have limited impact.7,37 Reports can be used for clinical decision making to optimize staff training in delivery of quality care while assuring staff safety. More than 80% of DB incidents occur during interactions with patients, thus this is a clinical issue that can affect the outcome of patient care.8,21

Documented DB reports are used to analyze the degree, frequency, and nature of incidents, which might reveal risk factors and develop preventive efforts and training for specific hazards.8,39 Some have argued that implementing a standardized DB reporting system is a crucial first step toward minimizing hazards and improving health care.38,40,41

When DB incidents were recorded through a hospital electronic reporting system and discussed in meetings, staff reported: (1) increased awareness of DB; (2) improved ability to manage DB incidents; and (3) amplified reporting of incidents.38,41,42 These findings support similar results from studies of an intervention implemented at VA Community Living Centers (CLCs) from 2013 to 2017: Staff Training in Assisted Living Residences (STAR-VA).4,12,19 The aim of STAR-VA was to minimize challenging dementia-related DB in CLCs. The intervention initially was established to train direct-care, assisted-living staff to provide better care to older patients displaying DB. Data revealed that documentation of DBs was, the first step to ensuring staff and patient safety.18,40

 

 

VHA Reporting System

In 2013, the VA Office of Inspector General (OIG) found no standardized documentation of DB events across the VA health care system.42 Instead, DB events were documented in multiple records in various locations, including administrative and progress notes in the electronic health record (EHR), police reports, e-mails, or letters submitted to DBC chairs.42 This situation reduced administrators’ ability to consider all relevant information and render appropriate decisions in DB cases.42 In 2015, based on OIG recommendations, the VHA implemented the Disruptive Behavior Reporting System (DBRS) nationwide, which allowed all VHA staff to report DB events. The DBRS was designed to address factors likely to impede reporting and management of DB, namely, complexity of and lack of access to a central reporting system.43,44 The DBRS is currently the primary VHA tool to document DB events.

The DBRS consists of 32 questions in 5 sections relating to the (1) location and time of DB event; (2) reporter; (3) disrupter; (4) DB event details; and (5) the person who experienced (experiencer) the event. The system also provides a list of the types of DB, such as inappropriate communication, bullying and/or intimidation, verbal or written threat of physical harm, physical violence, sexual harassment, sexual assault, and property damage. The DBRS has the potential to provide useful data on DB and DB reporting, such as the typical staff entering data and the number and/or types of DB occurring.

The DBRS complements the preexisting VHA policies and committees for care of veterans who display DB.1-3,14,21,24,25 The VHA Workplace Violence Prevention Program (WVPP) required facilities to submit data on DB events through a Workplace Behavioral Risk report. Data for the report were obtained from police reports, patient safety reports, DBC records, and notes in the EHR. Following implementations of DBRS, the number of DB events per year became a part of facility performance standards.

VHA is creating novel approaches to handling DB that allow health care workers to render care in a safe and effective manner guided by documented information. For example, DBCs can recommend the use of Category I Patient Record Flags (PRFs) following documented DB, which informs staff of the potential risk of DB and provides guidance on protective methods to use when meeting with the patient.2,21,24 A survey of 140 VA hospital chiefs of staff indicated that DBC procedures were related to a decrease in the rates of assaults.1 Additionally, VA provides training for staff in techniques to promote personal safety, such as identifying signs that precede DB, using verbal deescalation, and practicing therapeutic containment.

Resistance to Reporting

Many health care employees and employers are reticent to report DBs.22,31,43,45-48 Studies suggest health care organizations can cultivate a culture that is resistant to reporting DB.49,50 This complicates the ability of the health care system to design and maintain safety protocols and safer treatment plans.3,41,51 Worldwide, < 30% of DBs are reported.47 One barrier may be that supervisors may not wish to acknowledge DBs on their units or may not provide sufficient staff time for training or reporting.31,46,47 HCPs may worry that a DB report will stigmatize patients, especially those who are elderly or have cognitive impairment, brain injury, psychological illness, or developmental disability. Patients with cognitive conditions are reportedly 20% more likely to be violent toward caregivers and providers.31 A dementia diagnosis, for example, is associated with a high likelihood for DB.30,52 More than 80% of DB events displayed by patients with dementia may go unreported.26,31,50,52

 

 

Some clinicians may attribute DB to physiologic conditions that need to be treated, not reported. However, employers can face various legal liabilities if steps are not taken to protect employees.47,51 Federal and state statutes require that organizations provide a healthy and safe employment environment for workers. This requires that employers institute reasonable protective measures, such as procedures to intervene, policies on addressing DB incidents, and/or training to minimize or deescalate DB.51,53 Also, employees may sue employers if security measures are inadequate or deficient in properly investigating current and past evidence of DB or identifying vulnerabilities in the workplace. Unwillingness to investigate DB and safety-related workplace concerns have contributed to increased workplace violence and legal liability.52,53 The mission of caring and trust is consistent with assuring a safe environment.

Training and Empathetic Care

To combat cultural resistance to reporting DBs, more and perhaps different contextual approaches to education and training may be needed that address ethical dilemmas and concerns of providers. The success of training relies on administrators supporting staff in reporting DB. Training must address providers’ conflicting beliefs and assist with identifying strategies to provide the best possible care for patients who display DB.1,38 HCPs are less likely to document a DB if they feel that administrators are creating documentation that will have negative consequences for a patient. Thus, leadership is responsible for ensuring that misconceptions are dispelled through training and other efforts and information on how reported DB data will be used is communicated through strategic channels.

Education and training must consider empathic care that attempts to understand why patients behave as they do through the information gathered.55 Empathy in health care is multifaceted: It involves comprehending a patient’s viewpoint, circumstances, and feelings and the capacity to analyze whether one is comprehending these accurately in order to demonstrate supportive care.54,55

Improving patient and staff interaction once a problematic behavior is identified is the aim of empathic care. Increasing empathic care can improve compassionate, patient-centered interactions that begin once the patient seeks care. This approach has proven to decrease DB by patients with dementia and improve their care, lessen staff problems during interactions, and increase staff morale.20 Experts call for the adoption of an interpersonal approach to patient encounters, and there is evidence that creating organizational change by moving toward compassionate care can lead to a positive impact for patients.54,55

Future Studies

There are growth opportunities in utilization of the DBRS. Analysis of the DBRS database by the VA Central Office (VACO) showed that the system is underutilized by facilities across the VA system.56 In response to this current underutilization, VACO is taking steps to close these gaps through increasing training to staff and promotion of the use of the DBRS. A 2015 pilot study of VHA providers showed that > 70% of providers had experienced a DB as defined by VHA, but only 34% of them reported their most recently experienced DB within the past 12 months.20 Thus, DBRS use must be studied within the context that patient-perpetrated DB is underreported in health care organizations.5,9,29,41,43,57,58 Studies addressing national DBRS utilization patterns and the cost associated with implementing the DBRS also are needed. One study suggests that there is an association between measures of facility complexity and staff perceptions of safety, which should be considered in analyzing DBRS usage.57 Studies addressing the role of the DBRS and misconceptions that the tool may represent a punitive tool also are needed. VHA should consider how the attribution “disruptive behavior” assigns a negative connotation and leads HCPs to avoid using the DBRS. Additionally, DB reporting may increase when HCPs understand that DB reporting is part of the comprehensive, consultative strategy to provide the best care to patients.

 

 

Conclusion

Accurate reporting of DB events enables the development of strategies for multidisciplinary teams to work together to minimize hazards and to provide interventions that provide for the safe delivery of health care to all patients. Improving reporting ensures there is an accurate representation of how disruptive events impact care provided within a facility—and what types of variables may be associated with increased risk for these types of events.

Additionally, ensuring that reporting is maximized also provides the VHA with opportunities for DBCs to offer evidence-based risk assessment of violence and consultation to staff members who may benefit from improved competencies in working with patients who display DB. These potential improvements are consistent with the VHA I CARE values and will provide data that can inform recommendations for health care in other agencies/health care organizations.

Acknowledgments
This work was supported by the Center of Innovation on Disability and Rehabilitation Research (CINDRR) of the Health Services Research and Development Service, Office of Research and Development, Department of Veterans Affairs.

References

1. Hodgson MJ, Mohr DC, Drummond DJ, Bell M, Van Male L. Managing disruptive patients in health care: necessary solutions to a difficult problem. Am J Ind Med. 2012;55(11):1009-1017.

2. US Department of Veterans Affairs, Veterans Health Administration. VHA Directive 2010-053. Patient Record Flags. https://www.va.gov/vhapublications/ViewPublication.asp?pub_ID=2341 Published December 3, 2010. Accessed March 29, 2019.

3. US Department of Veterans Affairs, Veterans Health Administration. VHA Directive 2012-026. Sexual Assaults and Other Defined Public Safety Incidents in VHA Facilities. https://www.va.gov/vhapublications/ViewPublication.asp?pub_ID=2797. Published September 27, 2012. Accessed March 29, 2019.

4. Curyto KJ, McCurry SM, Luci K, Karlin BE, Teri L, Karel MJ. Managing challenging behaviors of dementia in veterans: identifying and changing activators and consequences using STAR-VA. J Gerontol Nurs. 2017;43(2):33-43.

5. Speroni KG, Fitch T, Dawson E, Dugan L, Atherton M. Incidence and cost of nurse workplace violence perpetrated by hospital patients or patient visitors. J Emerg Nurs. 2014;40(3):218-228.

6. Phillips JP. Workplace violence against health care workers in the United States. NEJM. 2016;374(17):1661-1669.

7. Janocha JA, Smith RT. Workplace safety and health in the health care and social assistance industry, 2003–07. https://www.bls.gov/opub/mlr/cwc/workplace-safety-and-health-in-the-health-care-and-social-assistance-industry-2003-07.pdf. Published August 30, 2010. Accessed February 19, 2019.

8. US Department of Labor, Occupational Safety and Health Administration. Workplace violence in healthcare: understanding the challenge. https://www.osha.gov/Publications/OSHA3826.pdf. Published December 2015. Accessed February 19, 2019.

9. US Department of Labor, Occupational Safety and Health Administration. Prevention of Workplace Violence in Healthcare and Social Assistance. Occupational Safety and Health Administration, https://www.govinfo.gov/content/pkg/FR-2016-12-07/pdf/2016-29197.pdf. Accessed January 20, 2017.

10. Gerberich SG, Church TR, McGovern PM, et al. An epidemiological study of the magnitude and consequences of work related violence: the Minnesota Nurses’ Study. Occup Environ Med. 2004;61(6):495-503.

11. Sherman MF, Gershon RRM, Samar SM, Pearson JM, Canton AN, Damsky MR. Safety factors predictive of job satisfaction and job retention among home healthcare aides. J Occup Environ Med. 2008;50(12):1430-1441.

12. Karel MJ, Teri L, McConnell E, Visnic S, Karlin BE. Effectiveness of expanded implementation of STAR-VA for managing dementia-related behaviors among veterans. Gerontologist. 2016;56(1):126-134.

13. US Department of Labor, Bureau of Labor Statistics. Nonfatal occupational injuries and illnesses requiring days away from work. https://www.bls.gov/news.release/archives/osh2_11192015.htm. Published November 19, 2015.

14. Beech B, Leather P. Workplace violence in the health care sector: A review of staff training and integration of training evaluation models. Aggression Violent Behav. 2006;11(1):27-43.

15. Campbell CL, McCoy S, Burg MA, Hoffman N. Enhancing home care staff safety through reducing client aggression and violence in noninstitutional care settings: a systematic review. Home Health Care Manage Pract. 2014;26(1):3-10.

16. Gallant-Roman MA. Strategies and tools to reduce workplace violence. AAOHNJ. 2008;56(11):449-454.

17. Weinberger LE, Sreenivasan S, Smee DE, McGuire J, Garrick T. Balancing safety against obstruction to health care access: an examination of behavioral flags in the VA health care system. J Threat Assess Manage. 2018;5(1):35-41.

18. Elbogen EB, Johnson SC, Wagner HR, et al. Protective factors and risk modification of violence in Iraq and Afghanistan war veterans. J Clin Psychiatry. 2012;73(6):e767-e773.

19. Karlin BE, Visnic S, McGee JS, Teri L. Results from the multisite implementation of STAR-VA: a multicomponent psychosocial intervention for managing challenging dementia-related behaviors of veterans. Psychol Serv. 2014;11(2):200-208.

20. Semeah LM, Campbell CL, Cowper DC, Peet AC. Serving our homeless veterans: patient perpetrated violence as a barrier to health care access. J Pub Nonprofit Aff. 2017;3(2):223-234.

21. Hodgson MJ, Reed R, Craig T, et al. Violence in healthcare facilities: lessons from the Veterans Health Administration. J Occup Environ Med. 2004;46(11):1158-1165.

22. Farrell GA, Bobrowski C, Bobrowski P. Scoping workplace aggression in nursing: findings from an Australian study. J Adv Nurs. 2006;55(6):778-787.

23. Barling J, Rogers AG, Kelloway EK. Behind closed doors: in-home workers’ experience of sexual harassment and workplace violence. J Occup Health Psychol. 2001;6(3):255-269.

24. Pompeii LA, Schoenfisch AL, Lipscomb HJ, Dement JM, Smith CD, Upadhyaya M. Physical assault, physical threat, and verbal abuse perpetrated against hospital workers by patients or visitors in six U.S. hospitals. Am J Ind Med. 2015;58(11):1194-1204.

25. Sippel LM, Mota NP, Kachadourian LK, et al. The burden of hostility in U.S. veterans: results from the National Health and Resilience in Veterans Study. Psychiatry Res. 2016;243(suppl C):421-430.

26. Campbell C. Patient Violence and Aggression in Non-Institutional Health Care Settings: Predictors of Reporting By Healthcare Providers [doctoral dissertation]. Orlando: University of Central Florida; 2016.

27. Galinsky T, Feng HA, Streit J, et al. Risk factors associated with patient assaults of home healthcare workers. Rehabil Nurs. 2010;35(5):206-215.

28. Campbell CL. Incident reporting by health-care workers in noninstitutional care settings. Trauma, Violence Abuse. 2017;18(4):445-456.

29. Arnetz JE, Arnetz BB. Violence towards health care staff and possible effects on the quality of patient care. Soc Sci Med. 2001;52(3):417-427.

30. Gates D, Fitzwater E, Succop P. Relationships of stressors, strain, and anger to caregiver assaults. Issues Ment Health Nurs. 2003;24(8):775-793.

31. Brillhart B, Kruse B, Heard L. Safety concerns for rehabilitation nurses in home care. Rehabil Nurs. 2004;29(6):227-229.

32. Taylor H. Patient violence against clinicians: managing the risk. Innov Clin Neurosci. 2013;10(3):40-42.

33. US Department of Veterans Affairs, Office of Public and Intergovernmental Affairs. The Joint Commission releases results of surveys of the VA health care system. https://www.va.gov/opa/pressrel/pressrelease.cfm?id=2808. Updated August 5, 2014. Accessed February 19, 2019.

34. Büssing A, Höge T. Aggression and violence against home care workers. J Occup Health Psychol. 2004;9(3):206-219.

35. Geiger-Brown J, Muntaner C, McPhaul K, Lipscomb J, Trinkoff A. Abuse and violence during home care work as predictor of worker depression. Home Health Care Serv Q. 2007;26(1):59-77.

36. Gates DM, Gillespie GL, Succop P. Violence against nurses and its impact on stress and productivity. Nurs Econ. 2011;29(2):59-66.

37. Petterson IL, Arnetz BB. Psychosocial stressors and well-being in health care workers: the impact of an intervention program. Soc Sci Med. 1998;47(11):1763-1772.

38. Arnetz JE, Arnetz BB. Implementation and evaluation of a practical intervention programme for dealing with violence towards health care workers. J Adv Nurs. 2000;31(3):668-680.

39. Arnetz JE, Hamblin L, Russell J, et al. Preventing patient-to-worker violence in hospitals: outcome of a randomized controlled intervention. J Occup Environ Med. 2017;59(1):18-27.

40. Elbogen EB, Tomkins AJ, Pothuloori AP, Scalora MJ. Documentation of violence risk information in psychiatric hospital patient charts: an empirical examination. J Am Acad Psychiatry Law. 2003;31(1):58-64.

41. Winsvold Prang I, Jelson-Jorgensen LP. Should I report? A qualitative study of barriers to incident reporting among nurses working in nursing homes. Geriatr Nurs. 2014;35(6):441-447.

42. US Department of Veterans Affairs, Office of Inspector General. Healthcare inspection: management of disruptive patient behavior at VA medical facilities. Report No. 11-02585-129. https://www.va.gov/oig/pubs/VAOIG-11-02585-129.pdf. Published Mrach 7, 2013. Accessed February 21, 2019.

43. Lipscomb J, London M. Not Part of the Job: How to Take a Stand Against Violence in the Work Setting. Silver Spring, MD: American Nurses Association; 2015.

44. May DD, Grubbs LM. The extent, nature, and precipitating factors of nurse assault among three groups of registered nurses in a regional medical center. J Emerg Nurs. 2002;28(1):11-17.

45. Wharton TC, Ford BK. What is known about dementia care recipient violence and aggression against caregivers? J Gerontol Soc Work. 2014;57(5):460-477.

46. Brennan C, Worrall-Davies A, McMillan D, Gilbody S, House A. The hospital anxiety and depression scale: a diagnostic meta-analysis of case-finding ability. J Psychosom Res. 2010;69(4):371-378.

47. McPhaul K, Lipscomb J, Johnson J. Assessing risk for violence on home health visits. Home Healthc Nurse. 2010;28(5):278-289.

48. McPhaul KM, London M, Murrett K, Flannery K, Rosen J, Lipscomb J. Environmental evaluation for workplace violence in healthcare and social services. J Safety Res. 2008;39(2):237-250.

49. Kelly JA, Somlai AM, DiFranceisco WJ, et al. Bridging the gap between the science and service of HIV prevention: transferring effective research-based HIV prevention interventions to community AIDS service providers. Am J Public Health. 2000;90(7):1082-1088.

50. Pawlin S. Reporting violence. Emerg Nurse. 2008;16(4):16-21.

51. Brakel SJ. Legal liability and workplace violence. J Am Acad Psychiatry Law. 1998;26(4):553-562.

52. Neuman JH, Baron RA. Workplace violence and workplace aggression: evidence concerning specific forms, potential causes, and preferred targets. J Manage. 1998;24(3):391-419.53. Ferns T, Chojnacka I. Angels and swingers, matrons and sinners: nursing stereotypes. Br J Nurs. 2005;14(19):1028-1032.

54. Mercer SW, Reynolds WJ. Empathy and quality of care. Br J Gen Pract 2002;52(suppl):S9-S12.

55. Lee TH. An Epidemic of Empathy in Healthcare: How to Deliver Compassionate, Connected Patient Care That Creates a Competitive Advantage. Columbus, OH: McGraw-Hill Education; 2015.

56. US Department of Veterans Affairs, Veterans Health Administrastion. Veterans Health Administration workplace violence prevention program (WVPP): disruptive behavior reporting system utilization report. Published 2017. https://vaww.portal2.va.gov/sites/wvpp/Shared%20Documents/DBRS%20Utilization%20Reports/FY2017%20DBRS%20Quarterly%20Utilization%20Report%20(Quarter%201).pdf. [Source not verified.]

57. Campbell CL, Burg, MA, Gammonley D. Measures for incident reporting of patient violence and aggression towards healthcare providers: a systematic review. Aggression Violent Behav. 2015;25(part B):314-322.

58. Carney PT, West P, Neily J, Mills PD, Bagian JP. The effect of facility complexity on perceptions of safety climate in the operating room: size matters. Am J Med Qual. 2010;25(6):457-461.

References

1. Hodgson MJ, Mohr DC, Drummond DJ, Bell M, Van Male L. Managing disruptive patients in health care: necessary solutions to a difficult problem. Am J Ind Med. 2012;55(11):1009-1017.

2. US Department of Veterans Affairs, Veterans Health Administration. VHA Directive 2010-053. Patient Record Flags. https://www.va.gov/vhapublications/ViewPublication.asp?pub_ID=2341 Published December 3, 2010. Accessed March 29, 2019.

3. US Department of Veterans Affairs, Veterans Health Administration. VHA Directive 2012-026. Sexual Assaults and Other Defined Public Safety Incidents in VHA Facilities. https://www.va.gov/vhapublications/ViewPublication.asp?pub_ID=2797. Published September 27, 2012. Accessed March 29, 2019.

4. Curyto KJ, McCurry SM, Luci K, Karlin BE, Teri L, Karel MJ. Managing challenging behaviors of dementia in veterans: identifying and changing activators and consequences using STAR-VA. J Gerontol Nurs. 2017;43(2):33-43.

5. Speroni KG, Fitch T, Dawson E, Dugan L, Atherton M. Incidence and cost of nurse workplace violence perpetrated by hospital patients or patient visitors. J Emerg Nurs. 2014;40(3):218-228.

6. Phillips JP. Workplace violence against health care workers in the United States. NEJM. 2016;374(17):1661-1669.

7. Janocha JA, Smith RT. Workplace safety and health in the health care and social assistance industry, 2003–07. https://www.bls.gov/opub/mlr/cwc/workplace-safety-and-health-in-the-health-care-and-social-assistance-industry-2003-07.pdf. Published August 30, 2010. Accessed February 19, 2019.

8. US Department of Labor, Occupational Safety and Health Administration. Workplace violence in healthcare: understanding the challenge. https://www.osha.gov/Publications/OSHA3826.pdf. Published December 2015. Accessed February 19, 2019.

9. US Department of Labor, Occupational Safety and Health Administration. Prevention of Workplace Violence in Healthcare and Social Assistance. Occupational Safety and Health Administration, https://www.govinfo.gov/content/pkg/FR-2016-12-07/pdf/2016-29197.pdf. Accessed January 20, 2017.

10. Gerberich SG, Church TR, McGovern PM, et al. An epidemiological study of the magnitude and consequences of work related violence: the Minnesota Nurses’ Study. Occup Environ Med. 2004;61(6):495-503.

11. Sherman MF, Gershon RRM, Samar SM, Pearson JM, Canton AN, Damsky MR. Safety factors predictive of job satisfaction and job retention among home healthcare aides. J Occup Environ Med. 2008;50(12):1430-1441.

12. Karel MJ, Teri L, McConnell E, Visnic S, Karlin BE. Effectiveness of expanded implementation of STAR-VA for managing dementia-related behaviors among veterans. Gerontologist. 2016;56(1):126-134.

13. US Department of Labor, Bureau of Labor Statistics. Nonfatal occupational injuries and illnesses requiring days away from work. https://www.bls.gov/news.release/archives/osh2_11192015.htm. Published November 19, 2015.

14. Beech B, Leather P. Workplace violence in the health care sector: A review of staff training and integration of training evaluation models. Aggression Violent Behav. 2006;11(1):27-43.

15. Campbell CL, McCoy S, Burg MA, Hoffman N. Enhancing home care staff safety through reducing client aggression and violence in noninstitutional care settings: a systematic review. Home Health Care Manage Pract. 2014;26(1):3-10.

16. Gallant-Roman MA. Strategies and tools to reduce workplace violence. AAOHNJ. 2008;56(11):449-454.

17. Weinberger LE, Sreenivasan S, Smee DE, McGuire J, Garrick T. Balancing safety against obstruction to health care access: an examination of behavioral flags in the VA health care system. J Threat Assess Manage. 2018;5(1):35-41.

18. Elbogen EB, Johnson SC, Wagner HR, et al. Protective factors and risk modification of violence in Iraq and Afghanistan war veterans. J Clin Psychiatry. 2012;73(6):e767-e773.

19. Karlin BE, Visnic S, McGee JS, Teri L. Results from the multisite implementation of STAR-VA: a multicomponent psychosocial intervention for managing challenging dementia-related behaviors of veterans. Psychol Serv. 2014;11(2):200-208.

20. Semeah LM, Campbell CL, Cowper DC, Peet AC. Serving our homeless veterans: patient perpetrated violence as a barrier to health care access. J Pub Nonprofit Aff. 2017;3(2):223-234.

21. Hodgson MJ, Reed R, Craig T, et al. Violence in healthcare facilities: lessons from the Veterans Health Administration. J Occup Environ Med. 2004;46(11):1158-1165.

22. Farrell GA, Bobrowski C, Bobrowski P. Scoping workplace aggression in nursing: findings from an Australian study. J Adv Nurs. 2006;55(6):778-787.

23. Barling J, Rogers AG, Kelloway EK. Behind closed doors: in-home workers’ experience of sexual harassment and workplace violence. J Occup Health Psychol. 2001;6(3):255-269.

24. Pompeii LA, Schoenfisch AL, Lipscomb HJ, Dement JM, Smith CD, Upadhyaya M. Physical assault, physical threat, and verbal abuse perpetrated against hospital workers by patients or visitors in six U.S. hospitals. Am J Ind Med. 2015;58(11):1194-1204.

25. Sippel LM, Mota NP, Kachadourian LK, et al. The burden of hostility in U.S. veterans: results from the National Health and Resilience in Veterans Study. Psychiatry Res. 2016;243(suppl C):421-430.

26. Campbell C. Patient Violence and Aggression in Non-Institutional Health Care Settings: Predictors of Reporting By Healthcare Providers [doctoral dissertation]. Orlando: University of Central Florida; 2016.

27. Galinsky T, Feng HA, Streit J, et al. Risk factors associated with patient assaults of home healthcare workers. Rehabil Nurs. 2010;35(5):206-215.

28. Campbell CL. Incident reporting by health-care workers in noninstitutional care settings. Trauma, Violence Abuse. 2017;18(4):445-456.

29. Arnetz JE, Arnetz BB. Violence towards health care staff and possible effects on the quality of patient care. Soc Sci Med. 2001;52(3):417-427.

30. Gates D, Fitzwater E, Succop P. Relationships of stressors, strain, and anger to caregiver assaults. Issues Ment Health Nurs. 2003;24(8):775-793.

31. Brillhart B, Kruse B, Heard L. Safety concerns for rehabilitation nurses in home care. Rehabil Nurs. 2004;29(6):227-229.

32. Taylor H. Patient violence against clinicians: managing the risk. Innov Clin Neurosci. 2013;10(3):40-42.

33. US Department of Veterans Affairs, Office of Public and Intergovernmental Affairs. The Joint Commission releases results of surveys of the VA health care system. https://www.va.gov/opa/pressrel/pressrelease.cfm?id=2808. Updated August 5, 2014. Accessed February 19, 2019.

34. Büssing A, Höge T. Aggression and violence against home care workers. J Occup Health Psychol. 2004;9(3):206-219.

35. Geiger-Brown J, Muntaner C, McPhaul K, Lipscomb J, Trinkoff A. Abuse and violence during home care work as predictor of worker depression. Home Health Care Serv Q. 2007;26(1):59-77.

36. Gates DM, Gillespie GL, Succop P. Violence against nurses and its impact on stress and productivity. Nurs Econ. 2011;29(2):59-66.

37. Petterson IL, Arnetz BB. Psychosocial stressors and well-being in health care workers: the impact of an intervention program. Soc Sci Med. 1998;47(11):1763-1772.

38. Arnetz JE, Arnetz BB. Implementation and evaluation of a practical intervention programme for dealing with violence towards health care workers. J Adv Nurs. 2000;31(3):668-680.

39. Arnetz JE, Hamblin L, Russell J, et al. Preventing patient-to-worker violence in hospitals: outcome of a randomized controlled intervention. J Occup Environ Med. 2017;59(1):18-27.

40. Elbogen EB, Tomkins AJ, Pothuloori AP, Scalora MJ. Documentation of violence risk information in psychiatric hospital patient charts: an empirical examination. J Am Acad Psychiatry Law. 2003;31(1):58-64.

41. Winsvold Prang I, Jelson-Jorgensen LP. Should I report? A qualitative study of barriers to incident reporting among nurses working in nursing homes. Geriatr Nurs. 2014;35(6):441-447.

42. US Department of Veterans Affairs, Office of Inspector General. Healthcare inspection: management of disruptive patient behavior at VA medical facilities. Report No. 11-02585-129. https://www.va.gov/oig/pubs/VAOIG-11-02585-129.pdf. Published Mrach 7, 2013. Accessed February 21, 2019.

43. Lipscomb J, London M. Not Part of the Job: How to Take a Stand Against Violence in the Work Setting. Silver Spring, MD: American Nurses Association; 2015.

44. May DD, Grubbs LM. The extent, nature, and precipitating factors of nurse assault among three groups of registered nurses in a regional medical center. J Emerg Nurs. 2002;28(1):11-17.

45. Wharton TC, Ford BK. What is known about dementia care recipient violence and aggression against caregivers? J Gerontol Soc Work. 2014;57(5):460-477.

46. Brennan C, Worrall-Davies A, McMillan D, Gilbody S, House A. The hospital anxiety and depression scale: a diagnostic meta-analysis of case-finding ability. J Psychosom Res. 2010;69(4):371-378.

47. McPhaul K, Lipscomb J, Johnson J. Assessing risk for violence on home health visits. Home Healthc Nurse. 2010;28(5):278-289.

48. McPhaul KM, London M, Murrett K, Flannery K, Rosen J, Lipscomb J. Environmental evaluation for workplace violence in healthcare and social services. J Safety Res. 2008;39(2):237-250.

49. Kelly JA, Somlai AM, DiFranceisco WJ, et al. Bridging the gap between the science and service of HIV prevention: transferring effective research-based HIV prevention interventions to community AIDS service providers. Am J Public Health. 2000;90(7):1082-1088.

50. Pawlin S. Reporting violence. Emerg Nurse. 2008;16(4):16-21.

51. Brakel SJ. Legal liability and workplace violence. J Am Acad Psychiatry Law. 1998;26(4):553-562.

52. Neuman JH, Baron RA. Workplace violence and workplace aggression: evidence concerning specific forms, potential causes, and preferred targets. J Manage. 1998;24(3):391-419.53. Ferns T, Chojnacka I. Angels and swingers, matrons and sinners: nursing stereotypes. Br J Nurs. 2005;14(19):1028-1032.

54. Mercer SW, Reynolds WJ. Empathy and quality of care. Br J Gen Pract 2002;52(suppl):S9-S12.

55. Lee TH. An Epidemic of Empathy in Healthcare: How to Deliver Compassionate, Connected Patient Care That Creates a Competitive Advantage. Columbus, OH: McGraw-Hill Education; 2015.

56. US Department of Veterans Affairs, Veterans Health Administrastion. Veterans Health Administration workplace violence prevention program (WVPP): disruptive behavior reporting system utilization report. Published 2017. https://vaww.portal2.va.gov/sites/wvpp/Shared%20Documents/DBRS%20Utilization%20Reports/FY2017%20DBRS%20Quarterly%20Utilization%20Report%20(Quarter%201).pdf. [Source not verified.]

57. Campbell CL, Burg, MA, Gammonley D. Measures for incident reporting of patient violence and aggression towards healthcare providers: a systematic review. Aggression Violent Behav. 2015;25(part B):314-322.

58. Carney PT, West P, Neily J, Mills PD, Bagian JP. The effect of facility complexity on perceptions of safety climate in the operating room: size matters. Am J Med Qual. 2010;25(6):457-461.

Issue
Federal Practitioner - 36(4)a
Issue
Federal Practitioner - 36(4)a
Page Number
158-163
Page Number
158-163
Publications
Publications
Topics
Article Type
Sections
Disallow All Ads
Content Gating
No Gating (article Unlocked/Free)
Alternative CME
Disqus Comments
Default
Eyebrow Default
PROGRAM PROFILE
Use ProPublica
Hide sidebar & use full width
render the right sidebar.
Article PDF Media