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Hospital Readmissions and Preventability
Hospital readmissions cost Medicare $15 to $17 billion per year.[1, 2] In 2010, the Hospital Readmission Reduction Program (HRRP), created by the Patient Protection and Affordable Care Act, authorized the Centers for Medicare and Medicaid Services (CMS) to penalize hospitals with higher‐than‐expected readmission rates for certain index conditions.[3] Other payers may follow suit, so hospitals and health systems nationwide are devoting significant resources to reducing readmissions.[4, 5, 6]
Implicit in these efforts are the assumptions that a significant proportion of readmissions are preventable, and that preventable readmissions can be identified. Unfortunately, estimates of preventability vary widely.[7, 8] In this article, we examine how preventable readmissions have been defined, measured, and calculated, and explore the associated implications for readmission reduction efforts.
THE MEDICARE READMISSION METRIC
The medical literature reveals substantial heterogeneity in how readmissions are assessed. Time periods range from 14 days to 4 years, and readmissions may be counted differently depending on whether they are to the same hospital or to any hospital, whether they are for the same (or a related) condition or for any condition, whether a patient is allowed to count only once during the follow‐up period, how mortality is treated, and whether observation stays are considered.[9]
Despite a lack of consensus in the literature, the approach adopted by CMS is endorsed by the National Quality Forum (NQF)[10] and has become the de facto standard for calculating readmission rates. CMS derives risk‐standardized readmission rates for acute myocardial infarction (AMI), heart failure (HF), and pneumonia (PN), using administrative claims data for each Medicare fee‐for‐service beneficiary 65 years or older.[11, 12, 13, 14] CMS counts the first readmission (but not subsequent ones) for any cause within 30 days of the index discharge, including readmissions to other facilities. Certain planned readmissions for revascularization are excluded, as are patients who left against medical advice, transferred to another acute‐care hospital, or died during the index admission. Admissions to psychiatric, rehabilitation, cancer specialty, and children's hospitals[12] are also excluded, as well as patients classified as observation status for either hospital stay.[15] Only administrative data are used in readmission calculations (ie, there are no chart reviews or interviews with healthcare personnel or patients). Details are published online and updated at least annually.[15]
EFFECTS AND LIMITATIONS OF THE HRRP AND THE CMS READMISSION METRIC
Penalizing hospitals for higher‐than‐expected readmission rates based on the CMS metric has been successful in the sense that hospitals now feel more accountable for patient outcomes after discharge; they are implementing transitional care programs, improving communication, and building relationships with community programs.[4, 5, 16] Early data suggest a small decline in readmission rates of Medicare beneficiaries nationally.[17] Previously, such readmission rates were constant.[18]
Nevertheless, significant concerns with the current approach have surfaced.[19, 20, 21] First, why choose 30 days? This time horizon was believed to be long enough to identify readmissions attributable to an index admission and short enough to reflect hospital‐delivered care and transitions to the outpatient setting, and it allows for collaboration between hospitals and their communities to reduce readmissions.[3] However, some have argued that this time horizon has little scientific basis,[22] and that hospitals are unfairly held accountable for a timeframe when outcomes may largely be influenced by the quality of outpatient care or the development of new problems.[23, 24] Approximately one‐third of 30‐day readmissions occur within the first 7 days, and more than half (55.7%) occur within the first 14 days[22, 25]; such time frames may be more appropriate for hospital accountability.[26]
Second, spurred by the focus of CMS penalties, efforts to reduce readmissions have largely concerned patients admitted for HF, AMI, or PN, although these 3 medical conditions account for only 10% of Medicare hospitalizations.[18] Programs focused on a narrow patient population may not benefit other patients with high readmission rates, such as those with gastrointestinal or psychiatric problems,[2] or lead to improvements in the underlying processes of care that could benefit patients in additional ways. Indeed, research suggests that low readmission rates may not be related to other measures of hospital quality.[27, 28]
Third, public reporting and hospital penalties are based on 3‐year historical performance, in part to accumulate a large enough sample size for each diagnosis. Hospitals that seek real‐time performance monitoring are limited to tracking surrogate outcomes, such as readmissions back to their own facility.[29, 30] Moreover, because of the long performance time frame, hospitals that achieve rapid improvement may endure penalties precisely when they are attempting to sustain their achievements.
Fourth, the CMS approach utilizes a complex risk‐standardization methodology, which has only modest ability to predict readmissions and allow hospital comparisons.[9] There is no adjustment for community characteristics, even though practice patterns are significantly associated with readmission rates,[9, 31] and more than half of the variation in readmission rates across hospitals can be explained by characteristics of the community such as access to care.[32] Moreover, patient factors, such as race and socioeconomic status, are currently not included in an attempt to hold hospitals to similar standards regardless of their patient population. This is hotly contested, however, and critics note this policy penalizes hospitals for factors outside of their control, such as patients' ability to afford medications.[33] Indeed, the June 2013 Medicare Payment Advisory Committee (MedPAC) report to Congress recommended evaluating hospital performance against facilities with a like percentage of low‐income patients as a way to take into account socioeconomic status.[34]
Fifth, observation stays are excluded, so patients who remain in observation status during their index or subsequent hospitalization cannot be counted as a readmission. Prevalence of observation care has increased, raising concerns that inpatient admissions are being shifted to observation status, producing an artificial decline in readmissions.[35] Fortunately, recent population‐level data provide some reassuring evidence to the contrary.[36]
Finally, and perhaps most significantly, the current readmission metric does not consider preventability. Recent reviews have demonstrated that estimates of preventability vary widely in individual studies, ranging from 5% to 79%, depending on study methodology and setting.[7, 8] Across these studies, on average, only 23% of 30‐day readmissions appear to be avoidable.[8] Another way to consider the preventability of hospital readmissions is by noting that the most effective multimodal care‐transition interventions reduce readmission rates by only about 30%, and most interventions are much less effective.[26] The likely fact that only 23% to 30% of readmissions are preventable has profound implications for the anticipated results of hospital readmission reduction efforts. Interventions that are 75% effective in reducing preventable readmissions should be expected to produce only an 18% to 22% reduction in overall readmission rates.[37]
FOCUSING ON PREVENTABLE READMISSIONS
A greater focus on identifying and targeting preventable readmissions would offer a number of advantages over the present approach. First, it is more meaningful to compare hospitals based on their percentage of discharges resulting in a preventable readmission, than on the basis of highly complex risk standardization procedures for selected conditions. Second, a focus on preventable readmissions more clearly identifies and permits hospitals to target opportunities for improvement. Third, if the focus were on preventable readmissions for a large number of conditions, the necessary sample size could be obtained over a shorter period of time. Overall, such a preventable readmissions metric could serve as a more agile and undiluted performance indicator, as opposed to the present 3‐year rolling average rate of all‐cause readmissions for certain conditions, the majority of which are probably not preventable.
DEFINING PREVENTABILITY
Defining a preventable readmission is critically important. However, neither a consensus definition nor a validated standard for assessing preventable hospital readmissions exists. Different conceptual frameworks and terms (eg, avoidable, potentially preventable, or urgent readmission) complicate the issue.[38, 39, 40]
Although the CMS measure does not address preventability, it is helpful to consider whether other readmission metrics incorporate this concept. The United Health Group's (UHG, formerly Pacificare) All‐Cause Readmission Index, University HealthSystem Consortium's 30‐Day Readmission Rate (all cause), and 3M Health Information Systems' (3M) Potentially Preventable Readmissions (PPR) are 3 commonly used measures.
Of these, only the 3M PPR metric includes the concept of preventability. 3M created a proprietary matrix of 98,000 readmission‐index admission All Patient Refined Diagnosis Related Group pairs based on the review of several physicians and the logical assumption that a readmission for a clinically related diagnosis is potentially preventable.[24, 41] Readmission and index admissions are considered clinically related if any of the following occur: (1) medical readmission for continuation or recurrence of an initial, or closely related, condition; (2) medical readmission for acute decompensation of a chronic condition that was not the reason for the index admission but was plausibly related to care during or immediately afterward (eg, readmission for diabetes in a patient whose index admission was AMI); (3) medical readmission for acute complication plausibly related to care during index admission; (4) readmission for surgical procedure for continuation or recurrence of initial problem (eg, readmission for appendectomy following admission for abdominal pain and fever); or (5) readmission for surgical procedure to address complication resulting from care during index admission.[24, 41] The readmission time frame is not standardized and may be set by the user. Though conceptually appealing in some ways, CMS and the NQF have expressed concern about this specific approach because of the uncertain reliability of the relatedness of the admission‐readmission diagnosis dyads.[3]
In the research literature, only a few studies have examined the 3M PPR or other preventability assessments that rely on the relatedness of diagnostic codes.[8] Using the 3M PPR, a study showed that 78% of readmissions were classified as potentially preventable,[42] which explains why the 3M PPR and all‐cause readmission metric may correlate highly.[43] Others have demonstrated that ratings of hospital performance on readmission rates vary by a moderate to large amount, depending on whether the 3M PPR, CMS, or UHG methodology is used.[43, 44] An algorithm called SQLape[45, 46] is used in Switzerland to benchmark hospitals and defines potentially avoidable readmissions as being related to index diagnoses or complications of those conditions. It has recently been tested in the United States in a single‐center study,[47] and a multihospital study is underway.
Aside from these algorithms using related diagnosis codes, most ratings of preventability have relied on subjective assessments made primarily through a review of hospital records, and approximately one‐third also included data from clinic visits or interviews with the treating medical team or patients/families.[8] Unfortunately, these reports provide insufficient detail on how to apply their preventability criteria to subsequent readmission reviews. Studies did, however, provide categories of preventability into which readmissions could be organized (see Supporting Information, Appendix Table 1, in the online version of this article for details from a subset of studies cited in van Walraven's reviews that illustrate this point).
Assessment of preventability by clinician review can be challenging. In general, such assessments have considered readmissions resulting from factors within the hospital's control to be avoidable (eg, providing appropriate discharge instructions, reconciling medications, arranging timely postdischarge follow‐up appointments), whereas readmissions resulting from factors not within the hospital's control are unavoidable (eg, patient socioeconomic status, social support, disease progression). However, readmissions resulting from patient behaviors or social reasons could potentially be classified as avoidable or unavoidable depending on the circumstances. For example, if a patient decides not to take a prescribed antibiotic and is readmitted with worsening infection, this could be classified as an unavoidable readmission from the hospital's perspective. Alternatively, if the physician prescribing the antibiotic was inattentive to the cost of the medication and the patient would have taken a less expensive medication had it been prescribed, this could be classified as an avoidable readmission. Differing interpretations of contextual factors may partially account for the variability in clinical assessments of preventability.
Indeed, despite the lack of consensus around a standard method of defining preventability, hospitals and health systems are moving forward to address the issue and reduce readmissions. A recent survey by America's Essential Hospitals (previously the National Association of Public Hospitals and Health Systems), indicated that: (1) reducing readmissions was a high priority for the majority (86%) of members, (2) most had established interdisciplinary teams to address the issue, and (3) over half had a formal process for determining which readmissions were potentially preventable. Of the survey respondents, just over one‐third rely on staff review of individual patient charts or patient and family interviews, and slightly less than one‐third rely on other mechanisms such as external consultants, criteria developed by other entities, or the Institute for Clinical Systems Improvement methodology.[48] Approximately one‐fifth make use of 3M's PPR product, and slightly fewer use the list of the Agency for Healthcare Research and Quality's ambulatory care sensitive conditions (ACSCs). These are medical conditions for which it is believed that good outpatient care could prevent the need for hospitalization (eg, asthma, congestive heart failure, diabetes) or for which early intervention minimizes complications.[49] Hospitalization rates for ACSCs may represent a good measure of excess hospitalization, with a focus on the quality of outpatient care.
RECOMMENDATIONS
We recommend that reporting of hospital readmission rates be based on preventable or potentially preventable readmissions. Although we acknowledge the challenges in doing so, the advantages are notable. At minimum, a preventable readmission rate would more accurately reflect the true gap in care and therefore hospitals' real opportunity for improvement, without being obscured by readmissions that are not preventable.
Because readmission rates are used for public reporting and financial penalties for hospitals, we favor a measure of preventability that reflects the readmissions that the hospital or hospital system has the ability to prevent. This would not penalize hospitals for factors that are under the control of others, namely patients and caregivers, community supports, or society at large. We further recommend that this measure apply to a broader composite of unplanned care, inclusive of both inpatient and observation stays, which have little distinction in patients' eyes, and both represent potentially unnecessary utilization of acute‐care resources.[50] Such a measure would require development, validation, and appropriate vetting before it is implemented.
The first step is for researchers and policy makers to agree on how a measure of preventable or potentially preventable readmissions could be defined. A common element of preventability assessment is to identify the degree to which the reasons for readmission are related to the diagnoses of the index hospitalization. To be reliable and scalable, this measure will need to be based on algorithms that relate the index and readmission diagnoses, most likely using claims data. Choosing common medical and surgical conditions and developing a consensus‐based list of related readmission diagnoses is an important first step. It would also be important to include some less common conditions, because they may reflect very different aspects of hospital care.
An approach based on a list of related diagnoses would represent potentially preventable rehospitalizations. Generally, clinical review is required to determine actual preventability, taking into account patient factors such as a high level of illness or functional impairment that leads to clinical decompensation in spite of excellent management.[51, 52] Clinical review, like a root cause analysis, also provides greater insight into hospital processes that may warrant improvement. Therefore, even if an administrative measure of potentially preventable readmissions is implemented, hospitals may wish to continue performing detailed clinical review of some readmissions for quality improvement purposes. When clinical review becomes more standardized,[53] a combined approach that uses administrative data plus clinical verification and arbitration may be feasible, as with hospital‐acquired infections.
Similar work to develop related sets of admission and readmission diagnoses has already been undertaken in development of the 3M PPR and SQLape measures.[41, 46] However, the 3M PPR is a proprietary system that has low specificity and a high false‐positive rate for identifying preventable readmissions when compared to clinical review.[42] Moreover, neither measure has yet achieved the consensus required for widespread adoption in the United States. What is needed is a nonproprietary listing of related admission and readmission diagnoses, developed with the engagement of relevant stakeholders, that goes through a period of public comment and vetting by a body such as the NQF.
Until a validated measure of potentially preventable readmission can be developed, how could the current approach evolve toward preventability? The most feasible, rapidly implementable change would be to alter the readmission time horizon from 30 days to 7 or 15 days. A 30‐day period holds hospitals accountable for complications of outpatient care or new problems that may develop weeks after discharge. Even though this may foster shared accountability and collaboration among hospitals and outpatient or community settings, research has demonstrated that early readmissions (eg, within 715 days of discharge) are more likely preventable.[54] Second, consideration of the socioeconomic status of hospital patients, as recommended by MedPAC,[34] would improve on the current model by comparing hospitals to like facilities when determining penalties for excess readmission rates. Finally, adjustment for community factors, such as practice patterns and access to care, would enable readmission metrics to better reflect factors under the hospital's control.[32]
CONCLUSION
Holding hospitals accountable for the quality of acute and transitional care is an important policy initiative that has accelerated many improvements in discharge planning and care coordination. Optimally, the policies, public reporting, and penalties should target preventable readmissions, which may represent as little as one‐quarter of all readmissions. By summarizing some of the issues in defining preventability, we hope to foster continued refinement of quality metrics used in this arena.
Acknowledgements
We thank Eduard Vasilevskis, MD, MPH, for feedback on an earlier draft of this article. This manuscript was informed by a special report titled Preventable Readmissions, written by Julia Lavenberg, Joel Betesh, David Goldmann, Craig Kean, and Kendal Williams of the Penn Medicine Center for Evidence‐based Practice. The review was performed at the request of the Penn Medicine Chief Medical Officer Patrick J. Brennan to inform the development of local readmission prevention metrics, and is available at
Disclosures
Dr. Umscheid's contribution to this project was supported in part by the National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health, through grant UL1TR000003. Dr. Kripalani receives support from the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number R01HL109388, and from the Centers for Medicare and Medicaid Services under awards 1C1CMS331006‐01 and 1C1CMS330979‐01. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or Centers for Medicare and Medicaid Services.
- , . Physician Visits After Hospital Discharge: Implications for Reducing Readmissions. Washington, DC: National Institute for Health Care Reform; 2011. Report no. 6.
- , , . Rehospitalizations among patients in the Medicare fee‐for‐service program. N Engl J Med. 2009;360(14):1418–1428.
- Centers for Medicare and Medicaid Services, US Department of Health and Human Services. Medicare program: hospital inpatient prospective payment systems for acute care hospitals and the long‐term care hospital prospective payment system and FY 2012 rates. Fed Regist. 2011;76(160):51476–51846.
- , , , , , . Quality collaboratives and campaigns to reduce readmissions: what strategies are hospitals using? J Hosp Med. 2013;8:601–608.
- , , , , . Contemporary data about hospital strategies to reduce unplanned readmissions: what has changed [research letter]? JAMA Intern Med. 2014;174(1):154–156.
- , , , , . Interventions to reduce 30‐day rehospitalization: a systematic review. Ann Intern Med. 2011;155(8):520–528.
- , , , . Comparing methods to calculate hospital‐specific rates of early death or urgent readmission. CMAJ. 2012;184(15):E810–E817.
- , , , , . Proportion of hospital readmissions deemed avoidable: a systematic review. CMAJ. 2011;183(7):E391–E402.
- , , , et al. Risk prediction models for hospital readmission: a systematic review. JAMA. 2011;306(15):1688–1698.
- National Quality Forum. Patient outcomes: all‐cause readmissions expedited review 2011. Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id60(7):607–614.
- , , , , , . Data shows reduction in Medicare hospital readmission rates during 2012. Medicare Medicaid Res Rev. 2013;3(2):E1–E11.
- , . Thirty‐day readmissions—truth and consequences. N Engl J Med. 2012;366(15):1366–1369.
- , , , . Moving beyond readmission penalties: creating an ideal process to improve transitional care. J Hosp Med. 2013;8(2):102–109.
- , . A path forward on Medicare readmissions. N Engl J Med. 2013;368(13):1175–1177.
- American Hospital Association. TrendWatch: examining the drivers of readmissions and reducing unnecessary readmissions for better patient care. Washington, DC: American Hospital Association; 2011.
- , , , et al. Diagnoses and timing of 30‐day readmissions after hospitalization for heart failure, acute myocardial infarction, or pneumonia. JAMA. 2013;309(4):355–363.
- , . Characteristics of hospitals receiving penalties under the hospital readmissions reduction program. JAMA. 2013;309(4):342–343.
- , , , , , , et al. Identifying potentially preventable readmissions. Health Care Financ Rev. 2008;30(1):75–91.
- , , , et al. Use of hospital‐based acute care among patients recently discharged from the hospital. JAMA. 2013;309(4):364–371.
- , , , . Reducing hospital readmission rates: current strategies and future directions. Annu Rev Med. 2014;65:471–485.
- , , , et al. Relationship between hospital readmission and mortality rates for patients hospitalized with acute myocardial infarction, heart failure, or pneumonia. JAMA. 2013;309(6):587–593.
- , , , et al. Hospital performance measures and 30‐day readmission rates. J Gen Intern Med. 2013;28(3):377–385.
- , , , . Limitations of using same‐hospital readmission metrics. Int J Qual Health Care. 2013;25(6):633–639.
- , , , et al. Is same‐hospital readmission rate a good surrogate for all‐hospital readmission rate? Med Care. 2010;48(5):477–481.
- , , . The relationship between hospital admission rates and rehospitalizations. N Engl J Med. 2011;365(24):2287–2295.
- . Community factors and hospital readmission rates [published online April 9, 2014]. Health Serv Res. doi: 10.1111/1475–6773.12177.
- American Hospital Association. Hospital readmissions reduction program: factsheet. American Hospital Association. Available at: http://www.aha.org/content/13/fs‐readmissions.pdf. Published April 14, 2014. Accessed May 5, 2014.
- Medicare Payment Advisory Commission. Report to the congress: Medicare and the health care delivery system. Available at: http://www.medpac.gov/documents/Jun13_EntireReport.pdf. Published June 14, 2013. Accessed May 5, 2014.
- , , . Sharp rise in Medicare enrollees being held in hospitals for observation raises concerns about causes and consequences. Health Aff (Millwood). 2012;31(6):1251–1259.
- , , . Quality improvement of care transitions and the trend of composite hospital care. JAMA. 2014;311(10):1013–1014.
- , . When projecting required effectiveness of interventions for hospital readmission reduction, the percentage that is potentially avoidable must be considered. J Clin Epidemiol. 2013;66(6):688–690.
- , , . Urgent readmission rates can be used to infer differences in avoidable readmission rates between hospitals. J Clin Epidemiol. 2012;65(10):1124–1130.
- , , , , . Proportion of hospital readmissions deemed avoidable: a systematic review. CMAJ. 2011;183(7):E391–E402.
- , , , , , . Measuring and preventing potentially avoidable hospital readmissions: a review of the literature. Hong Kong Med J. 2010;16(5):383–389.
- 3M Health Information Systems. Potentially preventable readmissions classification system methodology: overview. 3M Health Information Systems; May 2008. Report No.: GRP‐139. Available at: http://multimedia.3m.com/mws/mediawebserver?66666UuZjcFSLXTtNXMtmxMEEVuQEcuZgVs6EVs6E666666‐‐. Accessed June 8, 2014.
- , , , , , . Manual and automated methods for identifying potentially preventable readmissions: a comparison in a large healthcare system. BMC Med Inform Decis Mak. 2014;14:28.
- , , , , , , et al. Comparing 2 methods of assessing 30‐day readmissions: what is the impact on hospital profiling in the Veterans Health Administration? Med Care. 2013;51(7):589–596.
- , . It's not six of one, half‐dozen the other: a comparative analysis of 3 rehospitalization measurement systems for Massachusetts. Academy Health Annual Research Meeting. Seattle, WA. 2011. Available at: http://www.academyhealth.org/files/2011/tuesday/boutwell.pdf. Accessed May 9, 2014.
- , , , , , . Validation of the potentially avoidable hospital readmission rate as a routine indicator of the quality of hospital care. Med Care. 2006;44(11):972–981.
- , , , , , . Measuring potentially avoidable hospital readmissions. J Clin Epidemiol. 2002;55:573–587.
- , , , . Potentially avoidable 30‐day hospital readmissions in medical patients: derivation and validation of a prediction model. JAMA Intern Med. 2013;173(8):632–638.
- National Association of Public Hospitals and Health Systems. NAPH members focus on reducing readmissions. Available at: www.naph.org. Published June 2011. Accessed October 19, 2011.
- Agency for Healthcare Research and Quality. AHRQ quality indicators: prevention quality indicators. Available at: http://www.qualityindicators.ahrq.gov/Modules/pqi_resources.aspx. Accessed February 11, 2014.
- , , , , , . Shifting the dialogue from hospital readmissions to unplanned care. Am J Manag Care. 2013;19(6):450–453.
- . Post‐hospital syndrome—an acquired, transient condition of generalized risk. N Engl J Med. 2013;368(2):100–102.
- , . The hospital‐dependent patient. N Engl J Med. 2014;370(8):694–697.
- , , , et al. The hospital medicine reengineering network (HOMERuN): a learning organization focused on improving hospital care. Acad Med. 2014;89(3):415–420.
- , , , et al. Incidence of potentially avoidable urgent readmissions and their relation to all‐cause urgent readmissions. CMAJ. 2011;183(14):E1067–E1072.
Hospital readmissions cost Medicare $15 to $17 billion per year.[1, 2] In 2010, the Hospital Readmission Reduction Program (HRRP), created by the Patient Protection and Affordable Care Act, authorized the Centers for Medicare and Medicaid Services (CMS) to penalize hospitals with higher‐than‐expected readmission rates for certain index conditions.[3] Other payers may follow suit, so hospitals and health systems nationwide are devoting significant resources to reducing readmissions.[4, 5, 6]
Implicit in these efforts are the assumptions that a significant proportion of readmissions are preventable, and that preventable readmissions can be identified. Unfortunately, estimates of preventability vary widely.[7, 8] In this article, we examine how preventable readmissions have been defined, measured, and calculated, and explore the associated implications for readmission reduction efforts.
THE MEDICARE READMISSION METRIC
The medical literature reveals substantial heterogeneity in how readmissions are assessed. Time periods range from 14 days to 4 years, and readmissions may be counted differently depending on whether they are to the same hospital or to any hospital, whether they are for the same (or a related) condition or for any condition, whether a patient is allowed to count only once during the follow‐up period, how mortality is treated, and whether observation stays are considered.[9]
Despite a lack of consensus in the literature, the approach adopted by CMS is endorsed by the National Quality Forum (NQF)[10] and has become the de facto standard for calculating readmission rates. CMS derives risk‐standardized readmission rates for acute myocardial infarction (AMI), heart failure (HF), and pneumonia (PN), using administrative claims data for each Medicare fee‐for‐service beneficiary 65 years or older.[11, 12, 13, 14] CMS counts the first readmission (but not subsequent ones) for any cause within 30 days of the index discharge, including readmissions to other facilities. Certain planned readmissions for revascularization are excluded, as are patients who left against medical advice, transferred to another acute‐care hospital, or died during the index admission. Admissions to psychiatric, rehabilitation, cancer specialty, and children's hospitals[12] are also excluded, as well as patients classified as observation status for either hospital stay.[15] Only administrative data are used in readmission calculations (ie, there are no chart reviews or interviews with healthcare personnel or patients). Details are published online and updated at least annually.[15]
EFFECTS AND LIMITATIONS OF THE HRRP AND THE CMS READMISSION METRIC
Penalizing hospitals for higher‐than‐expected readmission rates based on the CMS metric has been successful in the sense that hospitals now feel more accountable for patient outcomes after discharge; they are implementing transitional care programs, improving communication, and building relationships with community programs.[4, 5, 16] Early data suggest a small decline in readmission rates of Medicare beneficiaries nationally.[17] Previously, such readmission rates were constant.[18]
Nevertheless, significant concerns with the current approach have surfaced.[19, 20, 21] First, why choose 30 days? This time horizon was believed to be long enough to identify readmissions attributable to an index admission and short enough to reflect hospital‐delivered care and transitions to the outpatient setting, and it allows for collaboration between hospitals and their communities to reduce readmissions.[3] However, some have argued that this time horizon has little scientific basis,[22] and that hospitals are unfairly held accountable for a timeframe when outcomes may largely be influenced by the quality of outpatient care or the development of new problems.[23, 24] Approximately one‐third of 30‐day readmissions occur within the first 7 days, and more than half (55.7%) occur within the first 14 days[22, 25]; such time frames may be more appropriate for hospital accountability.[26]
Second, spurred by the focus of CMS penalties, efforts to reduce readmissions have largely concerned patients admitted for HF, AMI, or PN, although these 3 medical conditions account for only 10% of Medicare hospitalizations.[18] Programs focused on a narrow patient population may not benefit other patients with high readmission rates, such as those with gastrointestinal or psychiatric problems,[2] or lead to improvements in the underlying processes of care that could benefit patients in additional ways. Indeed, research suggests that low readmission rates may not be related to other measures of hospital quality.[27, 28]
Third, public reporting and hospital penalties are based on 3‐year historical performance, in part to accumulate a large enough sample size for each diagnosis. Hospitals that seek real‐time performance monitoring are limited to tracking surrogate outcomes, such as readmissions back to their own facility.[29, 30] Moreover, because of the long performance time frame, hospitals that achieve rapid improvement may endure penalties precisely when they are attempting to sustain their achievements.
Fourth, the CMS approach utilizes a complex risk‐standardization methodology, which has only modest ability to predict readmissions and allow hospital comparisons.[9] There is no adjustment for community characteristics, even though practice patterns are significantly associated with readmission rates,[9, 31] and more than half of the variation in readmission rates across hospitals can be explained by characteristics of the community such as access to care.[32] Moreover, patient factors, such as race and socioeconomic status, are currently not included in an attempt to hold hospitals to similar standards regardless of their patient population. This is hotly contested, however, and critics note this policy penalizes hospitals for factors outside of their control, such as patients' ability to afford medications.[33] Indeed, the June 2013 Medicare Payment Advisory Committee (MedPAC) report to Congress recommended evaluating hospital performance against facilities with a like percentage of low‐income patients as a way to take into account socioeconomic status.[34]
Fifth, observation stays are excluded, so patients who remain in observation status during their index or subsequent hospitalization cannot be counted as a readmission. Prevalence of observation care has increased, raising concerns that inpatient admissions are being shifted to observation status, producing an artificial decline in readmissions.[35] Fortunately, recent population‐level data provide some reassuring evidence to the contrary.[36]
Finally, and perhaps most significantly, the current readmission metric does not consider preventability. Recent reviews have demonstrated that estimates of preventability vary widely in individual studies, ranging from 5% to 79%, depending on study methodology and setting.[7, 8] Across these studies, on average, only 23% of 30‐day readmissions appear to be avoidable.[8] Another way to consider the preventability of hospital readmissions is by noting that the most effective multimodal care‐transition interventions reduce readmission rates by only about 30%, and most interventions are much less effective.[26] The likely fact that only 23% to 30% of readmissions are preventable has profound implications for the anticipated results of hospital readmission reduction efforts. Interventions that are 75% effective in reducing preventable readmissions should be expected to produce only an 18% to 22% reduction in overall readmission rates.[37]
FOCUSING ON PREVENTABLE READMISSIONS
A greater focus on identifying and targeting preventable readmissions would offer a number of advantages over the present approach. First, it is more meaningful to compare hospitals based on their percentage of discharges resulting in a preventable readmission, than on the basis of highly complex risk standardization procedures for selected conditions. Second, a focus on preventable readmissions more clearly identifies and permits hospitals to target opportunities for improvement. Third, if the focus were on preventable readmissions for a large number of conditions, the necessary sample size could be obtained over a shorter period of time. Overall, such a preventable readmissions metric could serve as a more agile and undiluted performance indicator, as opposed to the present 3‐year rolling average rate of all‐cause readmissions for certain conditions, the majority of which are probably not preventable.
DEFINING PREVENTABILITY
Defining a preventable readmission is critically important. However, neither a consensus definition nor a validated standard for assessing preventable hospital readmissions exists. Different conceptual frameworks and terms (eg, avoidable, potentially preventable, or urgent readmission) complicate the issue.[38, 39, 40]
Although the CMS measure does not address preventability, it is helpful to consider whether other readmission metrics incorporate this concept. The United Health Group's (UHG, formerly Pacificare) All‐Cause Readmission Index, University HealthSystem Consortium's 30‐Day Readmission Rate (all cause), and 3M Health Information Systems' (3M) Potentially Preventable Readmissions (PPR) are 3 commonly used measures.
Of these, only the 3M PPR metric includes the concept of preventability. 3M created a proprietary matrix of 98,000 readmission‐index admission All Patient Refined Diagnosis Related Group pairs based on the review of several physicians and the logical assumption that a readmission for a clinically related diagnosis is potentially preventable.[24, 41] Readmission and index admissions are considered clinically related if any of the following occur: (1) medical readmission for continuation or recurrence of an initial, or closely related, condition; (2) medical readmission for acute decompensation of a chronic condition that was not the reason for the index admission but was plausibly related to care during or immediately afterward (eg, readmission for diabetes in a patient whose index admission was AMI); (3) medical readmission for acute complication plausibly related to care during index admission; (4) readmission for surgical procedure for continuation or recurrence of initial problem (eg, readmission for appendectomy following admission for abdominal pain and fever); or (5) readmission for surgical procedure to address complication resulting from care during index admission.[24, 41] The readmission time frame is not standardized and may be set by the user. Though conceptually appealing in some ways, CMS and the NQF have expressed concern about this specific approach because of the uncertain reliability of the relatedness of the admission‐readmission diagnosis dyads.[3]
In the research literature, only a few studies have examined the 3M PPR or other preventability assessments that rely on the relatedness of diagnostic codes.[8] Using the 3M PPR, a study showed that 78% of readmissions were classified as potentially preventable,[42] which explains why the 3M PPR and all‐cause readmission metric may correlate highly.[43] Others have demonstrated that ratings of hospital performance on readmission rates vary by a moderate to large amount, depending on whether the 3M PPR, CMS, or UHG methodology is used.[43, 44] An algorithm called SQLape[45, 46] is used in Switzerland to benchmark hospitals and defines potentially avoidable readmissions as being related to index diagnoses or complications of those conditions. It has recently been tested in the United States in a single‐center study,[47] and a multihospital study is underway.
Aside from these algorithms using related diagnosis codes, most ratings of preventability have relied on subjective assessments made primarily through a review of hospital records, and approximately one‐third also included data from clinic visits or interviews with the treating medical team or patients/families.[8] Unfortunately, these reports provide insufficient detail on how to apply their preventability criteria to subsequent readmission reviews. Studies did, however, provide categories of preventability into which readmissions could be organized (see Supporting Information, Appendix Table 1, in the online version of this article for details from a subset of studies cited in van Walraven's reviews that illustrate this point).
Assessment of preventability by clinician review can be challenging. In general, such assessments have considered readmissions resulting from factors within the hospital's control to be avoidable (eg, providing appropriate discharge instructions, reconciling medications, arranging timely postdischarge follow‐up appointments), whereas readmissions resulting from factors not within the hospital's control are unavoidable (eg, patient socioeconomic status, social support, disease progression). However, readmissions resulting from patient behaviors or social reasons could potentially be classified as avoidable or unavoidable depending on the circumstances. For example, if a patient decides not to take a prescribed antibiotic and is readmitted with worsening infection, this could be classified as an unavoidable readmission from the hospital's perspective. Alternatively, if the physician prescribing the antibiotic was inattentive to the cost of the medication and the patient would have taken a less expensive medication had it been prescribed, this could be classified as an avoidable readmission. Differing interpretations of contextual factors may partially account for the variability in clinical assessments of preventability.
Indeed, despite the lack of consensus around a standard method of defining preventability, hospitals and health systems are moving forward to address the issue and reduce readmissions. A recent survey by America's Essential Hospitals (previously the National Association of Public Hospitals and Health Systems), indicated that: (1) reducing readmissions was a high priority for the majority (86%) of members, (2) most had established interdisciplinary teams to address the issue, and (3) over half had a formal process for determining which readmissions were potentially preventable. Of the survey respondents, just over one‐third rely on staff review of individual patient charts or patient and family interviews, and slightly less than one‐third rely on other mechanisms such as external consultants, criteria developed by other entities, or the Institute for Clinical Systems Improvement methodology.[48] Approximately one‐fifth make use of 3M's PPR product, and slightly fewer use the list of the Agency for Healthcare Research and Quality's ambulatory care sensitive conditions (ACSCs). These are medical conditions for which it is believed that good outpatient care could prevent the need for hospitalization (eg, asthma, congestive heart failure, diabetes) or for which early intervention minimizes complications.[49] Hospitalization rates for ACSCs may represent a good measure of excess hospitalization, with a focus on the quality of outpatient care.
RECOMMENDATIONS
We recommend that reporting of hospital readmission rates be based on preventable or potentially preventable readmissions. Although we acknowledge the challenges in doing so, the advantages are notable. At minimum, a preventable readmission rate would more accurately reflect the true gap in care and therefore hospitals' real opportunity for improvement, without being obscured by readmissions that are not preventable.
Because readmission rates are used for public reporting and financial penalties for hospitals, we favor a measure of preventability that reflects the readmissions that the hospital or hospital system has the ability to prevent. This would not penalize hospitals for factors that are under the control of others, namely patients and caregivers, community supports, or society at large. We further recommend that this measure apply to a broader composite of unplanned care, inclusive of both inpatient and observation stays, which have little distinction in patients' eyes, and both represent potentially unnecessary utilization of acute‐care resources.[50] Such a measure would require development, validation, and appropriate vetting before it is implemented.
The first step is for researchers and policy makers to agree on how a measure of preventable or potentially preventable readmissions could be defined. A common element of preventability assessment is to identify the degree to which the reasons for readmission are related to the diagnoses of the index hospitalization. To be reliable and scalable, this measure will need to be based on algorithms that relate the index and readmission diagnoses, most likely using claims data. Choosing common medical and surgical conditions and developing a consensus‐based list of related readmission diagnoses is an important first step. It would also be important to include some less common conditions, because they may reflect very different aspects of hospital care.
An approach based on a list of related diagnoses would represent potentially preventable rehospitalizations. Generally, clinical review is required to determine actual preventability, taking into account patient factors such as a high level of illness or functional impairment that leads to clinical decompensation in spite of excellent management.[51, 52] Clinical review, like a root cause analysis, also provides greater insight into hospital processes that may warrant improvement. Therefore, even if an administrative measure of potentially preventable readmissions is implemented, hospitals may wish to continue performing detailed clinical review of some readmissions for quality improvement purposes. When clinical review becomes more standardized,[53] a combined approach that uses administrative data plus clinical verification and arbitration may be feasible, as with hospital‐acquired infections.
Similar work to develop related sets of admission and readmission diagnoses has already been undertaken in development of the 3M PPR and SQLape measures.[41, 46] However, the 3M PPR is a proprietary system that has low specificity and a high false‐positive rate for identifying preventable readmissions when compared to clinical review.[42] Moreover, neither measure has yet achieved the consensus required for widespread adoption in the United States. What is needed is a nonproprietary listing of related admission and readmission diagnoses, developed with the engagement of relevant stakeholders, that goes through a period of public comment and vetting by a body such as the NQF.
Until a validated measure of potentially preventable readmission can be developed, how could the current approach evolve toward preventability? The most feasible, rapidly implementable change would be to alter the readmission time horizon from 30 days to 7 or 15 days. A 30‐day period holds hospitals accountable for complications of outpatient care or new problems that may develop weeks after discharge. Even though this may foster shared accountability and collaboration among hospitals and outpatient or community settings, research has demonstrated that early readmissions (eg, within 715 days of discharge) are more likely preventable.[54] Second, consideration of the socioeconomic status of hospital patients, as recommended by MedPAC,[34] would improve on the current model by comparing hospitals to like facilities when determining penalties for excess readmission rates. Finally, adjustment for community factors, such as practice patterns and access to care, would enable readmission metrics to better reflect factors under the hospital's control.[32]
CONCLUSION
Holding hospitals accountable for the quality of acute and transitional care is an important policy initiative that has accelerated many improvements in discharge planning and care coordination. Optimally, the policies, public reporting, and penalties should target preventable readmissions, which may represent as little as one‐quarter of all readmissions. By summarizing some of the issues in defining preventability, we hope to foster continued refinement of quality metrics used in this arena.
Acknowledgements
We thank Eduard Vasilevskis, MD, MPH, for feedback on an earlier draft of this article. This manuscript was informed by a special report titled Preventable Readmissions, written by Julia Lavenberg, Joel Betesh, David Goldmann, Craig Kean, and Kendal Williams of the Penn Medicine Center for Evidence‐based Practice. The review was performed at the request of the Penn Medicine Chief Medical Officer Patrick J. Brennan to inform the development of local readmission prevention metrics, and is available at
Disclosures
Dr. Umscheid's contribution to this project was supported in part by the National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health, through grant UL1TR000003. Dr. Kripalani receives support from the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number R01HL109388, and from the Centers for Medicare and Medicaid Services under awards 1C1CMS331006‐01 and 1C1CMS330979‐01. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or Centers for Medicare and Medicaid Services.
Hospital readmissions cost Medicare $15 to $17 billion per year.[1, 2] In 2010, the Hospital Readmission Reduction Program (HRRP), created by the Patient Protection and Affordable Care Act, authorized the Centers for Medicare and Medicaid Services (CMS) to penalize hospitals with higher‐than‐expected readmission rates for certain index conditions.[3] Other payers may follow suit, so hospitals and health systems nationwide are devoting significant resources to reducing readmissions.[4, 5, 6]
Implicit in these efforts are the assumptions that a significant proportion of readmissions are preventable, and that preventable readmissions can be identified. Unfortunately, estimates of preventability vary widely.[7, 8] In this article, we examine how preventable readmissions have been defined, measured, and calculated, and explore the associated implications for readmission reduction efforts.
THE MEDICARE READMISSION METRIC
The medical literature reveals substantial heterogeneity in how readmissions are assessed. Time periods range from 14 days to 4 years, and readmissions may be counted differently depending on whether they are to the same hospital or to any hospital, whether they are for the same (or a related) condition or for any condition, whether a patient is allowed to count only once during the follow‐up period, how mortality is treated, and whether observation stays are considered.[9]
Despite a lack of consensus in the literature, the approach adopted by CMS is endorsed by the National Quality Forum (NQF)[10] and has become the de facto standard for calculating readmission rates. CMS derives risk‐standardized readmission rates for acute myocardial infarction (AMI), heart failure (HF), and pneumonia (PN), using administrative claims data for each Medicare fee‐for‐service beneficiary 65 years or older.[11, 12, 13, 14] CMS counts the first readmission (but not subsequent ones) for any cause within 30 days of the index discharge, including readmissions to other facilities. Certain planned readmissions for revascularization are excluded, as are patients who left against medical advice, transferred to another acute‐care hospital, or died during the index admission. Admissions to psychiatric, rehabilitation, cancer specialty, and children's hospitals[12] are also excluded, as well as patients classified as observation status for either hospital stay.[15] Only administrative data are used in readmission calculations (ie, there are no chart reviews or interviews with healthcare personnel or patients). Details are published online and updated at least annually.[15]
EFFECTS AND LIMITATIONS OF THE HRRP AND THE CMS READMISSION METRIC
Penalizing hospitals for higher‐than‐expected readmission rates based on the CMS metric has been successful in the sense that hospitals now feel more accountable for patient outcomes after discharge; they are implementing transitional care programs, improving communication, and building relationships with community programs.[4, 5, 16] Early data suggest a small decline in readmission rates of Medicare beneficiaries nationally.[17] Previously, such readmission rates were constant.[18]
Nevertheless, significant concerns with the current approach have surfaced.[19, 20, 21] First, why choose 30 days? This time horizon was believed to be long enough to identify readmissions attributable to an index admission and short enough to reflect hospital‐delivered care and transitions to the outpatient setting, and it allows for collaboration between hospitals and their communities to reduce readmissions.[3] However, some have argued that this time horizon has little scientific basis,[22] and that hospitals are unfairly held accountable for a timeframe when outcomes may largely be influenced by the quality of outpatient care or the development of new problems.[23, 24] Approximately one‐third of 30‐day readmissions occur within the first 7 days, and more than half (55.7%) occur within the first 14 days[22, 25]; such time frames may be more appropriate for hospital accountability.[26]
Second, spurred by the focus of CMS penalties, efforts to reduce readmissions have largely concerned patients admitted for HF, AMI, or PN, although these 3 medical conditions account for only 10% of Medicare hospitalizations.[18] Programs focused on a narrow patient population may not benefit other patients with high readmission rates, such as those with gastrointestinal or psychiatric problems,[2] or lead to improvements in the underlying processes of care that could benefit patients in additional ways. Indeed, research suggests that low readmission rates may not be related to other measures of hospital quality.[27, 28]
Third, public reporting and hospital penalties are based on 3‐year historical performance, in part to accumulate a large enough sample size for each diagnosis. Hospitals that seek real‐time performance monitoring are limited to tracking surrogate outcomes, such as readmissions back to their own facility.[29, 30] Moreover, because of the long performance time frame, hospitals that achieve rapid improvement may endure penalties precisely when they are attempting to sustain their achievements.
Fourth, the CMS approach utilizes a complex risk‐standardization methodology, which has only modest ability to predict readmissions and allow hospital comparisons.[9] There is no adjustment for community characteristics, even though practice patterns are significantly associated with readmission rates,[9, 31] and more than half of the variation in readmission rates across hospitals can be explained by characteristics of the community such as access to care.[32] Moreover, patient factors, such as race and socioeconomic status, are currently not included in an attempt to hold hospitals to similar standards regardless of their patient population. This is hotly contested, however, and critics note this policy penalizes hospitals for factors outside of their control, such as patients' ability to afford medications.[33] Indeed, the June 2013 Medicare Payment Advisory Committee (MedPAC) report to Congress recommended evaluating hospital performance against facilities with a like percentage of low‐income patients as a way to take into account socioeconomic status.[34]
Fifth, observation stays are excluded, so patients who remain in observation status during their index or subsequent hospitalization cannot be counted as a readmission. Prevalence of observation care has increased, raising concerns that inpatient admissions are being shifted to observation status, producing an artificial decline in readmissions.[35] Fortunately, recent population‐level data provide some reassuring evidence to the contrary.[36]
Finally, and perhaps most significantly, the current readmission metric does not consider preventability. Recent reviews have demonstrated that estimates of preventability vary widely in individual studies, ranging from 5% to 79%, depending on study methodology and setting.[7, 8] Across these studies, on average, only 23% of 30‐day readmissions appear to be avoidable.[8] Another way to consider the preventability of hospital readmissions is by noting that the most effective multimodal care‐transition interventions reduce readmission rates by only about 30%, and most interventions are much less effective.[26] The likely fact that only 23% to 30% of readmissions are preventable has profound implications for the anticipated results of hospital readmission reduction efforts. Interventions that are 75% effective in reducing preventable readmissions should be expected to produce only an 18% to 22% reduction in overall readmission rates.[37]
FOCUSING ON PREVENTABLE READMISSIONS
A greater focus on identifying and targeting preventable readmissions would offer a number of advantages over the present approach. First, it is more meaningful to compare hospitals based on their percentage of discharges resulting in a preventable readmission, than on the basis of highly complex risk standardization procedures for selected conditions. Second, a focus on preventable readmissions more clearly identifies and permits hospitals to target opportunities for improvement. Third, if the focus were on preventable readmissions for a large number of conditions, the necessary sample size could be obtained over a shorter period of time. Overall, such a preventable readmissions metric could serve as a more agile and undiluted performance indicator, as opposed to the present 3‐year rolling average rate of all‐cause readmissions for certain conditions, the majority of which are probably not preventable.
DEFINING PREVENTABILITY
Defining a preventable readmission is critically important. However, neither a consensus definition nor a validated standard for assessing preventable hospital readmissions exists. Different conceptual frameworks and terms (eg, avoidable, potentially preventable, or urgent readmission) complicate the issue.[38, 39, 40]
Although the CMS measure does not address preventability, it is helpful to consider whether other readmission metrics incorporate this concept. The United Health Group's (UHG, formerly Pacificare) All‐Cause Readmission Index, University HealthSystem Consortium's 30‐Day Readmission Rate (all cause), and 3M Health Information Systems' (3M) Potentially Preventable Readmissions (PPR) are 3 commonly used measures.
Of these, only the 3M PPR metric includes the concept of preventability. 3M created a proprietary matrix of 98,000 readmission‐index admission All Patient Refined Diagnosis Related Group pairs based on the review of several physicians and the logical assumption that a readmission for a clinically related diagnosis is potentially preventable.[24, 41] Readmission and index admissions are considered clinically related if any of the following occur: (1) medical readmission for continuation or recurrence of an initial, or closely related, condition; (2) medical readmission for acute decompensation of a chronic condition that was not the reason for the index admission but was plausibly related to care during or immediately afterward (eg, readmission for diabetes in a patient whose index admission was AMI); (3) medical readmission for acute complication plausibly related to care during index admission; (4) readmission for surgical procedure for continuation or recurrence of initial problem (eg, readmission for appendectomy following admission for abdominal pain and fever); or (5) readmission for surgical procedure to address complication resulting from care during index admission.[24, 41] The readmission time frame is not standardized and may be set by the user. Though conceptually appealing in some ways, CMS and the NQF have expressed concern about this specific approach because of the uncertain reliability of the relatedness of the admission‐readmission diagnosis dyads.[3]
In the research literature, only a few studies have examined the 3M PPR or other preventability assessments that rely on the relatedness of diagnostic codes.[8] Using the 3M PPR, a study showed that 78% of readmissions were classified as potentially preventable,[42] which explains why the 3M PPR and all‐cause readmission metric may correlate highly.[43] Others have demonstrated that ratings of hospital performance on readmission rates vary by a moderate to large amount, depending on whether the 3M PPR, CMS, or UHG methodology is used.[43, 44] An algorithm called SQLape[45, 46] is used in Switzerland to benchmark hospitals and defines potentially avoidable readmissions as being related to index diagnoses or complications of those conditions. It has recently been tested in the United States in a single‐center study,[47] and a multihospital study is underway.
Aside from these algorithms using related diagnosis codes, most ratings of preventability have relied on subjective assessments made primarily through a review of hospital records, and approximately one‐third also included data from clinic visits or interviews with the treating medical team or patients/families.[8] Unfortunately, these reports provide insufficient detail on how to apply their preventability criteria to subsequent readmission reviews. Studies did, however, provide categories of preventability into which readmissions could be organized (see Supporting Information, Appendix Table 1, in the online version of this article for details from a subset of studies cited in van Walraven's reviews that illustrate this point).
Assessment of preventability by clinician review can be challenging. In general, such assessments have considered readmissions resulting from factors within the hospital's control to be avoidable (eg, providing appropriate discharge instructions, reconciling medications, arranging timely postdischarge follow‐up appointments), whereas readmissions resulting from factors not within the hospital's control are unavoidable (eg, patient socioeconomic status, social support, disease progression). However, readmissions resulting from patient behaviors or social reasons could potentially be classified as avoidable or unavoidable depending on the circumstances. For example, if a patient decides not to take a prescribed antibiotic and is readmitted with worsening infection, this could be classified as an unavoidable readmission from the hospital's perspective. Alternatively, if the physician prescribing the antibiotic was inattentive to the cost of the medication and the patient would have taken a less expensive medication had it been prescribed, this could be classified as an avoidable readmission. Differing interpretations of contextual factors may partially account for the variability in clinical assessments of preventability.
Indeed, despite the lack of consensus around a standard method of defining preventability, hospitals and health systems are moving forward to address the issue and reduce readmissions. A recent survey by America's Essential Hospitals (previously the National Association of Public Hospitals and Health Systems), indicated that: (1) reducing readmissions was a high priority for the majority (86%) of members, (2) most had established interdisciplinary teams to address the issue, and (3) over half had a formal process for determining which readmissions were potentially preventable. Of the survey respondents, just over one‐third rely on staff review of individual patient charts or patient and family interviews, and slightly less than one‐third rely on other mechanisms such as external consultants, criteria developed by other entities, or the Institute for Clinical Systems Improvement methodology.[48] Approximately one‐fifth make use of 3M's PPR product, and slightly fewer use the list of the Agency for Healthcare Research and Quality's ambulatory care sensitive conditions (ACSCs). These are medical conditions for which it is believed that good outpatient care could prevent the need for hospitalization (eg, asthma, congestive heart failure, diabetes) or for which early intervention minimizes complications.[49] Hospitalization rates for ACSCs may represent a good measure of excess hospitalization, with a focus on the quality of outpatient care.
RECOMMENDATIONS
We recommend that reporting of hospital readmission rates be based on preventable or potentially preventable readmissions. Although we acknowledge the challenges in doing so, the advantages are notable. At minimum, a preventable readmission rate would more accurately reflect the true gap in care and therefore hospitals' real opportunity for improvement, without being obscured by readmissions that are not preventable.
Because readmission rates are used for public reporting and financial penalties for hospitals, we favor a measure of preventability that reflects the readmissions that the hospital or hospital system has the ability to prevent. This would not penalize hospitals for factors that are under the control of others, namely patients and caregivers, community supports, or society at large. We further recommend that this measure apply to a broader composite of unplanned care, inclusive of both inpatient and observation stays, which have little distinction in patients' eyes, and both represent potentially unnecessary utilization of acute‐care resources.[50] Such a measure would require development, validation, and appropriate vetting before it is implemented.
The first step is for researchers and policy makers to agree on how a measure of preventable or potentially preventable readmissions could be defined. A common element of preventability assessment is to identify the degree to which the reasons for readmission are related to the diagnoses of the index hospitalization. To be reliable and scalable, this measure will need to be based on algorithms that relate the index and readmission diagnoses, most likely using claims data. Choosing common medical and surgical conditions and developing a consensus‐based list of related readmission diagnoses is an important first step. It would also be important to include some less common conditions, because they may reflect very different aspects of hospital care.
An approach based on a list of related diagnoses would represent potentially preventable rehospitalizations. Generally, clinical review is required to determine actual preventability, taking into account patient factors such as a high level of illness or functional impairment that leads to clinical decompensation in spite of excellent management.[51, 52] Clinical review, like a root cause analysis, also provides greater insight into hospital processes that may warrant improvement. Therefore, even if an administrative measure of potentially preventable readmissions is implemented, hospitals may wish to continue performing detailed clinical review of some readmissions for quality improvement purposes. When clinical review becomes more standardized,[53] a combined approach that uses administrative data plus clinical verification and arbitration may be feasible, as with hospital‐acquired infections.
Similar work to develop related sets of admission and readmission diagnoses has already been undertaken in development of the 3M PPR and SQLape measures.[41, 46] However, the 3M PPR is a proprietary system that has low specificity and a high false‐positive rate for identifying preventable readmissions when compared to clinical review.[42] Moreover, neither measure has yet achieved the consensus required for widespread adoption in the United States. What is needed is a nonproprietary listing of related admission and readmission diagnoses, developed with the engagement of relevant stakeholders, that goes through a period of public comment and vetting by a body such as the NQF.
Until a validated measure of potentially preventable readmission can be developed, how could the current approach evolve toward preventability? The most feasible, rapidly implementable change would be to alter the readmission time horizon from 30 days to 7 or 15 days. A 30‐day period holds hospitals accountable for complications of outpatient care or new problems that may develop weeks after discharge. Even though this may foster shared accountability and collaboration among hospitals and outpatient or community settings, research has demonstrated that early readmissions (eg, within 715 days of discharge) are more likely preventable.[54] Second, consideration of the socioeconomic status of hospital patients, as recommended by MedPAC,[34] would improve on the current model by comparing hospitals to like facilities when determining penalties for excess readmission rates. Finally, adjustment for community factors, such as practice patterns and access to care, would enable readmission metrics to better reflect factors under the hospital's control.[32]
CONCLUSION
Holding hospitals accountable for the quality of acute and transitional care is an important policy initiative that has accelerated many improvements in discharge planning and care coordination. Optimally, the policies, public reporting, and penalties should target preventable readmissions, which may represent as little as one‐quarter of all readmissions. By summarizing some of the issues in defining preventability, we hope to foster continued refinement of quality metrics used in this arena.
Acknowledgements
We thank Eduard Vasilevskis, MD, MPH, for feedback on an earlier draft of this article. This manuscript was informed by a special report titled Preventable Readmissions, written by Julia Lavenberg, Joel Betesh, David Goldmann, Craig Kean, and Kendal Williams of the Penn Medicine Center for Evidence‐based Practice. The review was performed at the request of the Penn Medicine Chief Medical Officer Patrick J. Brennan to inform the development of local readmission prevention metrics, and is available at
Disclosures
Dr. Umscheid's contribution to this project was supported in part by the National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health, through grant UL1TR000003. Dr. Kripalani receives support from the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number R01HL109388, and from the Centers for Medicare and Medicaid Services under awards 1C1CMS331006‐01 and 1C1CMS330979‐01. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or Centers for Medicare and Medicaid Services.
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- American Hospital Association. TrendWatch: examining the drivers of readmissions and reducing unnecessary readmissions for better patient care. Washington, DC: American Hospital Association; 2011.
- , , , et al. Diagnoses and timing of 30‐day readmissions after hospitalization for heart failure, acute myocardial infarction, or pneumonia. JAMA. 2013;309(4):355–363.
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- , , , et al. Use of hospital‐based acute care among patients recently discharged from the hospital. JAMA. 2013;309(4):364–371.
- , , , . Reducing hospital readmission rates: current strategies and future directions. Annu Rev Med. 2014;65:471–485.
- , , , et al. Relationship between hospital readmission and mortality rates for patients hospitalized with acute myocardial infarction, heart failure, or pneumonia. JAMA. 2013;309(6):587–593.
- , , , et al. Hospital performance measures and 30‐day readmission rates. J Gen Intern Med. 2013;28(3):377–385.
- , , , . Limitations of using same‐hospital readmission metrics. Int J Qual Health Care. 2013;25(6):633–639.
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- , , . The relationship between hospital admission rates and rehospitalizations. N Engl J Med. 2011;365(24):2287–2295.
- . Community factors and hospital readmission rates [published online April 9, 2014]. Health Serv Res. doi: 10.1111/1475–6773.12177.
- American Hospital Association. Hospital readmissions reduction program: factsheet. American Hospital Association. Available at: http://www.aha.org/content/13/fs‐readmissions.pdf. Published April 14, 2014. Accessed May 5, 2014.
- Medicare Payment Advisory Commission. Report to the congress: Medicare and the health care delivery system. Available at: http://www.medpac.gov/documents/Jun13_EntireReport.pdf. Published June 14, 2013. Accessed May 5, 2014.
- , , . Sharp rise in Medicare enrollees being held in hospitals for observation raises concerns about causes and consequences. Health Aff (Millwood). 2012;31(6):1251–1259.
- , , . Quality improvement of care transitions and the trend of composite hospital care. JAMA. 2014;311(10):1013–1014.
- , . When projecting required effectiveness of interventions for hospital readmission reduction, the percentage that is potentially avoidable must be considered. J Clin Epidemiol. 2013;66(6):688–690.
- , , . Urgent readmission rates can be used to infer differences in avoidable readmission rates between hospitals. J Clin Epidemiol. 2012;65(10):1124–1130.
- , , , , . Proportion of hospital readmissions deemed avoidable: a systematic review. CMAJ. 2011;183(7):E391–E402.
- , , , , , . Measuring and preventing potentially avoidable hospital readmissions: a review of the literature. Hong Kong Med J. 2010;16(5):383–389.
- 3M Health Information Systems. Potentially preventable readmissions classification system methodology: overview. 3M Health Information Systems; May 2008. Report No.: GRP‐139. Available at: http://multimedia.3m.com/mws/mediawebserver?66666UuZjcFSLXTtNXMtmxMEEVuQEcuZgVs6EVs6E666666‐‐. Accessed June 8, 2014.
- , , , , , . Manual and automated methods for identifying potentially preventable readmissions: a comparison in a large healthcare system. BMC Med Inform Decis Mak. 2014;14:28.
- , , , , , , et al. Comparing 2 methods of assessing 30‐day readmissions: what is the impact on hospital profiling in the Veterans Health Administration? Med Care. 2013;51(7):589–596.
- , . It's not six of one, half‐dozen the other: a comparative analysis of 3 rehospitalization measurement systems for Massachusetts. Academy Health Annual Research Meeting. Seattle, WA. 2011. Available at: http://www.academyhealth.org/files/2011/tuesday/boutwell.pdf. Accessed May 9, 2014.
- , , , , , . Validation of the potentially avoidable hospital readmission rate as a routine indicator of the quality of hospital care. Med Care. 2006;44(11):972–981.
- , , , , , . Measuring potentially avoidable hospital readmissions. J Clin Epidemiol. 2002;55:573–587.
- , , , . Potentially avoidable 30‐day hospital readmissions in medical patients: derivation and validation of a prediction model. JAMA Intern Med. 2013;173(8):632–638.
- National Association of Public Hospitals and Health Systems. NAPH members focus on reducing readmissions. Available at: www.naph.org. Published June 2011. Accessed October 19, 2011.
- Agency for Healthcare Research and Quality. AHRQ quality indicators: prevention quality indicators. Available at: http://www.qualityindicators.ahrq.gov/Modules/pqi_resources.aspx. Accessed February 11, 2014.
- , , , , , . Shifting the dialogue from hospital readmissions to unplanned care. Am J Manag Care. 2013;19(6):450–453.
- . Post‐hospital syndrome—an acquired, transient condition of generalized risk. N Engl J Med. 2013;368(2):100–102.
- , . The hospital‐dependent patient. N Engl J Med. 2014;370(8):694–697.
- , , , et al. The hospital medicine reengineering network (HOMERuN): a learning organization focused on improving hospital care. Acad Med. 2014;89(3):415–420.
- , , , et al. Incidence of potentially avoidable urgent readmissions and their relation to all‐cause urgent readmissions. CMAJ. 2011;183(14):E1067–E1072.
- , . Physician Visits After Hospital Discharge: Implications for Reducing Readmissions. Washington, DC: National Institute for Health Care Reform; 2011. Report no. 6.
- , , . Rehospitalizations among patients in the Medicare fee‐for‐service program. N Engl J Med. 2009;360(14):1418–1428.
- Centers for Medicare and Medicaid Services, US Department of Health and Human Services. Medicare program: hospital inpatient prospective payment systems for acute care hospitals and the long‐term care hospital prospective payment system and FY 2012 rates. Fed Regist. 2011;76(160):51476–51846.
- , , , , , . Quality collaboratives and campaigns to reduce readmissions: what strategies are hospitals using? J Hosp Med. 2013;8:601–608.
- , , , , . Contemporary data about hospital strategies to reduce unplanned readmissions: what has changed [research letter]? JAMA Intern Med. 2014;174(1):154–156.
- , , , , . Interventions to reduce 30‐day rehospitalization: a systematic review. Ann Intern Med. 2011;155(8):520–528.
- , , , . Comparing methods to calculate hospital‐specific rates of early death or urgent readmission. CMAJ. 2012;184(15):E810–E817.
- , , , , . Proportion of hospital readmissions deemed avoidable: a systematic review. CMAJ. 2011;183(7):E391–E402.
- , , , et al. Risk prediction models for hospital readmission: a systematic review. JAMA. 2011;306(15):1688–1698.
- National Quality Forum. Patient outcomes: all‐cause readmissions expedited review 2011. Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id60(7):607–614.
- , , , , , . Data shows reduction in Medicare hospital readmission rates during 2012. Medicare Medicaid Res Rev. 2013;3(2):E1–E11.
- , . Thirty‐day readmissions—truth and consequences. N Engl J Med. 2012;366(15):1366–1369.
- , , , . Moving beyond readmission penalties: creating an ideal process to improve transitional care. J Hosp Med. 2013;8(2):102–109.
- , . A path forward on Medicare readmissions. N Engl J Med. 2013;368(13):1175–1177.
- American Hospital Association. TrendWatch: examining the drivers of readmissions and reducing unnecessary readmissions for better patient care. Washington, DC: American Hospital Association; 2011.
- , , , et al. Diagnoses and timing of 30‐day readmissions after hospitalization for heart failure, acute myocardial infarction, or pneumonia. JAMA. 2013;309(4):355–363.
- , . Characteristics of hospitals receiving penalties under the hospital readmissions reduction program. JAMA. 2013;309(4):342–343.
- , , , , , , et al. Identifying potentially preventable readmissions. Health Care Financ Rev. 2008;30(1):75–91.
- , , , et al. Use of hospital‐based acute care among patients recently discharged from the hospital. JAMA. 2013;309(4):364–371.
- , , , . Reducing hospital readmission rates: current strategies and future directions. Annu Rev Med. 2014;65:471–485.
- , , , et al. Relationship between hospital readmission and mortality rates for patients hospitalized with acute myocardial infarction, heart failure, or pneumonia. JAMA. 2013;309(6):587–593.
- , , , et al. Hospital performance measures and 30‐day readmission rates. J Gen Intern Med. 2013;28(3):377–385.
- , , , . Limitations of using same‐hospital readmission metrics. Int J Qual Health Care. 2013;25(6):633–639.
- , , , et al. Is same‐hospital readmission rate a good surrogate for all‐hospital readmission rate? Med Care. 2010;48(5):477–481.
- , , . The relationship between hospital admission rates and rehospitalizations. N Engl J Med. 2011;365(24):2287–2295.
- . Community factors and hospital readmission rates [published online April 9, 2014]. Health Serv Res. doi: 10.1111/1475–6773.12177.
- American Hospital Association. Hospital readmissions reduction program: factsheet. American Hospital Association. Available at: http://www.aha.org/content/13/fs‐readmissions.pdf. Published April 14, 2014. Accessed May 5, 2014.
- Medicare Payment Advisory Commission. Report to the congress: Medicare and the health care delivery system. Available at: http://www.medpac.gov/documents/Jun13_EntireReport.pdf. Published June 14, 2013. Accessed May 5, 2014.
- , , . Sharp rise in Medicare enrollees being held in hospitals for observation raises concerns about causes and consequences. Health Aff (Millwood). 2012;31(6):1251–1259.
- , , . Quality improvement of care transitions and the trend of composite hospital care. JAMA. 2014;311(10):1013–1014.
- , . When projecting required effectiveness of interventions for hospital readmission reduction, the percentage that is potentially avoidable must be considered. J Clin Epidemiol. 2013;66(6):688–690.
- , , . Urgent readmission rates can be used to infer differences in avoidable readmission rates between hospitals. J Clin Epidemiol. 2012;65(10):1124–1130.
- , , , , . Proportion of hospital readmissions deemed avoidable: a systematic review. CMAJ. 2011;183(7):E391–E402.
- , , , , , . Measuring and preventing potentially avoidable hospital readmissions: a review of the literature. Hong Kong Med J. 2010;16(5):383–389.
- 3M Health Information Systems. Potentially preventable readmissions classification system methodology: overview. 3M Health Information Systems; May 2008. Report No.: GRP‐139. Available at: http://multimedia.3m.com/mws/mediawebserver?66666UuZjcFSLXTtNXMtmxMEEVuQEcuZgVs6EVs6E666666‐‐. Accessed June 8, 2014.
- , , , , , . Manual and automated methods for identifying potentially preventable readmissions: a comparison in a large healthcare system. BMC Med Inform Decis Mak. 2014;14:28.
- , , , , , , et al. Comparing 2 methods of assessing 30‐day readmissions: what is the impact on hospital profiling in the Veterans Health Administration? Med Care. 2013;51(7):589–596.
- , . It's not six of one, half‐dozen the other: a comparative analysis of 3 rehospitalization measurement systems for Massachusetts. Academy Health Annual Research Meeting. Seattle, WA. 2011. Available at: http://www.academyhealth.org/files/2011/tuesday/boutwell.pdf. Accessed May 9, 2014.
- , , , , , . Validation of the potentially avoidable hospital readmission rate as a routine indicator of the quality of hospital care. Med Care. 2006;44(11):972–981.
- , , , , , . Measuring potentially avoidable hospital readmissions. J Clin Epidemiol. 2002;55:573–587.
- , , , . Potentially avoidable 30‐day hospital readmissions in medical patients: derivation and validation of a prediction model. JAMA Intern Med. 2013;173(8):632–638.
- National Association of Public Hospitals and Health Systems. NAPH members focus on reducing readmissions. Available at: www.naph.org. Published June 2011. Accessed October 19, 2011.
- Agency for Healthcare Research and Quality. AHRQ quality indicators: prevention quality indicators. Available at: http://www.qualityindicators.ahrq.gov/Modules/pqi_resources.aspx. Accessed February 11, 2014.
- , , , , , . Shifting the dialogue from hospital readmissions to unplanned care. Am J Manag Care. 2013;19(6):450–453.
- . Post‐hospital syndrome—an acquired, transient condition of generalized risk. N Engl J Med. 2013;368(2):100–102.
- , . The hospital‐dependent patient. N Engl J Med. 2014;370(8):694–697.
- , , , et al. The hospital medicine reengineering network (HOMERuN): a learning organization focused on improving hospital care. Acad Med. 2014;89(3):415–420.
- , , , et al. Incidence of potentially avoidable urgent readmissions and their relation to all‐cause urgent readmissions. CMAJ. 2011;183(14):E1067–E1072.
Ramelteon Reduces Risk of Delirium Among Hospitalized Patients
Clinical question
Does ramelteon, a melatonin agonist, prevent delirium in hospitalized patients?
Bottom line
In this small, single-blinded study, ramelteon was shown to be effective in preventing delirium in elderly patients who required hospitalization for acute illness. You would have to treat 3 patients with ramelteon to prevent one episode of delirium. (LOE = 1b)
Reference
Hatta K, Kishi Y, Wada K, et al, for the DELIRIA-J Group. Preventive effects of ramelteon on delirium. JAMA Psychiatry 2014;71(4):397-403.
Study design
Randomized controlled trial (single-blinded)
Funding source
Government
Allocation
Concealed
Setting
Inpatient (any location)
Synopsis
Using concealed allocation, these investigators randomized 67 hospitalized patients (24 admitted to intensive care units, 43 admitted to general wards) to receive either ramelteon 8 mg or placebo nightly up to 7 days or until the onset of delirium. Eligible patients were 65 years to 89 years old, were admitted to the hospital via the emergency department, were able to take oral medications, and had an expected length of stay of greater than 48 hours. Patients with psychiatric disorders, severe liver disease, Lewy body disease, or alcohol dependency were excluded. Nurses provided similar delirium prevention care to all patients, including frequent reorientation, adequate lighting, and noise reduction. If patients required treatment for insomnia, hydroxyzine was used with a dose limit of 25 mg per night. Baseline characteristics were similar in the 2 groups, with a mean age of 78 years. For the primary outcome of onset of delirium, experienced psychiatrists, masked to study group, assessed patients in the mornings and afternoons for up to 7 days using a delirium rating scale. Only 1 patient in the ramelteon group was diagnosed with delirium as compared with 11 patients in the placebo group (3% vs 32%; number needed to treat = 3; P = .003). Interestingly, there were no significant differences between the groups in sleep metrics such as difficulty falling asleep and poor sleep quality, although the sample was likely too small to detect such differences. Note that the patients were not masked in this study, which could have potentially affected the overall outcomes. No adverse effects attributed to the study drug were reported.
Dr. Kulkarni is an assistant professor of hospital medicine at Northwestern University in Chicago.
Clinical question
Does ramelteon, a melatonin agonist, prevent delirium in hospitalized patients?
Bottom line
In this small, single-blinded study, ramelteon was shown to be effective in preventing delirium in elderly patients who required hospitalization for acute illness. You would have to treat 3 patients with ramelteon to prevent one episode of delirium. (LOE = 1b)
Reference
Hatta K, Kishi Y, Wada K, et al, for the DELIRIA-J Group. Preventive effects of ramelteon on delirium. JAMA Psychiatry 2014;71(4):397-403.
Study design
Randomized controlled trial (single-blinded)
Funding source
Government
Allocation
Concealed
Setting
Inpatient (any location)
Synopsis
Using concealed allocation, these investigators randomized 67 hospitalized patients (24 admitted to intensive care units, 43 admitted to general wards) to receive either ramelteon 8 mg or placebo nightly up to 7 days or until the onset of delirium. Eligible patients were 65 years to 89 years old, were admitted to the hospital via the emergency department, were able to take oral medications, and had an expected length of stay of greater than 48 hours. Patients with psychiatric disorders, severe liver disease, Lewy body disease, or alcohol dependency were excluded. Nurses provided similar delirium prevention care to all patients, including frequent reorientation, adequate lighting, and noise reduction. If patients required treatment for insomnia, hydroxyzine was used with a dose limit of 25 mg per night. Baseline characteristics were similar in the 2 groups, with a mean age of 78 years. For the primary outcome of onset of delirium, experienced psychiatrists, masked to study group, assessed patients in the mornings and afternoons for up to 7 days using a delirium rating scale. Only 1 patient in the ramelteon group was diagnosed with delirium as compared with 11 patients in the placebo group (3% vs 32%; number needed to treat = 3; P = .003). Interestingly, there were no significant differences between the groups in sleep metrics such as difficulty falling asleep and poor sleep quality, although the sample was likely too small to detect such differences. Note that the patients were not masked in this study, which could have potentially affected the overall outcomes. No adverse effects attributed to the study drug were reported.
Dr. Kulkarni is an assistant professor of hospital medicine at Northwestern University in Chicago.
Clinical question
Does ramelteon, a melatonin agonist, prevent delirium in hospitalized patients?
Bottom line
In this small, single-blinded study, ramelteon was shown to be effective in preventing delirium in elderly patients who required hospitalization for acute illness. You would have to treat 3 patients with ramelteon to prevent one episode of delirium. (LOE = 1b)
Reference
Hatta K, Kishi Y, Wada K, et al, for the DELIRIA-J Group. Preventive effects of ramelteon on delirium. JAMA Psychiatry 2014;71(4):397-403.
Study design
Randomized controlled trial (single-blinded)
Funding source
Government
Allocation
Concealed
Setting
Inpatient (any location)
Synopsis
Using concealed allocation, these investigators randomized 67 hospitalized patients (24 admitted to intensive care units, 43 admitted to general wards) to receive either ramelteon 8 mg or placebo nightly up to 7 days or until the onset of delirium. Eligible patients were 65 years to 89 years old, were admitted to the hospital via the emergency department, were able to take oral medications, and had an expected length of stay of greater than 48 hours. Patients with psychiatric disorders, severe liver disease, Lewy body disease, or alcohol dependency were excluded. Nurses provided similar delirium prevention care to all patients, including frequent reorientation, adequate lighting, and noise reduction. If patients required treatment for insomnia, hydroxyzine was used with a dose limit of 25 mg per night. Baseline characteristics were similar in the 2 groups, with a mean age of 78 years. For the primary outcome of onset of delirium, experienced psychiatrists, masked to study group, assessed patients in the mornings and afternoons for up to 7 days using a delirium rating scale. Only 1 patient in the ramelteon group was diagnosed with delirium as compared with 11 patients in the placebo group (3% vs 32%; number needed to treat = 3; P = .003). Interestingly, there were no significant differences between the groups in sleep metrics such as difficulty falling asleep and poor sleep quality, although the sample was likely too small to detect such differences. Note that the patients were not masked in this study, which could have potentially affected the overall outcomes. No adverse effects attributed to the study drug were reported.
Dr. Kulkarni is an assistant professor of hospital medicine at Northwestern University in Chicago.
Fibrinolysis for Intermediate-Risk PE: Increased Bleeding, No Mortality Effect
Clinical question
Does the use of fibrinolytic therapy improve mortality and morbidity in normotensive patients with acute pulmonary embolism who are at intermediate risk for adverse outcomes?
Bottom line
For patients with acute pulmonary embolism (PE) at intermediate risk for adverse outcomes, fibrinolytic therapy (tenecteplase plus standard anticoagulation) decreases the incidence of hemodynamic decompensation but does not decrease mortality as compared with anticoagulation alone. Not surprisingly, fibrinolysis also increases bleeding and strokes. You would need to treat 20 people with tenecteplase to cause one episode of bleeding, and 45 people to cause one additional stroke. Given the significant bleeding risk with this therapy, fibrinolysis in patients who are at higher risk of adverse outcomes but are hemodynamically stable cannot be recommended until further research shows a greater clinical benefit. (LOE = 1b)
Reference
Study design
Randomized controlled trial (nonblinded)
Funding source
Industry + govt
Allocation
Concealed
Setting
Inpatient (any location)
Synopsis
These authors enrolled adult patients with acute PE who were hemodynamically stable and were considered to have an intermediate risk for adverse outcomes as indicated by right ventricular dysfunction or myocardial injury. Right ventricular dysfunction was confirmed by either echocardiography or chest computed tomography, and myocardial injury was confirmed by a positive troponin test result. Using concealed allocation, investigators randomized these patients (N = 1006) to receive either fibrinolysis with tenecteplase at a weight-based dose or matching placebo. Both groups also received full anticoagulation with unfractionated heparin. Baseline characteristics were similar in the 2 groups and analysis was by intention to treat. Fewer patients in the tenecteplase group experienced the primary outcome of death or hemodynamic decompensation at 7 days (2.6% vs 5.6%; odds ratio = 0.44; 95% CI, 0.23 - 0.87). Looking at the individual components of the composite outcome, there was no significant difference in mortality between the 2 groups (1.2% vs 1.8%), but the tenecteplase group had a decreased incidence of hemodynamic decompensation (1.6% vs 5%; P = .002). The significance of this is unclear, as one of the definitions of hemodynamic decompensation was an isolated drop in systolic blood pressure to below 90 mmHg for at least 15 minutes. Major bleeding and hemorrhagic strokes were more common in the tenecteplase group (bleeding: 11.5% vs 2.4%; strokes: 2% vs 0.2%).
Dr. Kulkarni is an assistant professor of hospital medicine at Northwestern University in Chicago.
Clinical question
Does the use of fibrinolytic therapy improve mortality and morbidity in normotensive patients with acute pulmonary embolism who are at intermediate risk for adverse outcomes?
Bottom line
For patients with acute pulmonary embolism (PE) at intermediate risk for adverse outcomes, fibrinolytic therapy (tenecteplase plus standard anticoagulation) decreases the incidence of hemodynamic decompensation but does not decrease mortality as compared with anticoagulation alone. Not surprisingly, fibrinolysis also increases bleeding and strokes. You would need to treat 20 people with tenecteplase to cause one episode of bleeding, and 45 people to cause one additional stroke. Given the significant bleeding risk with this therapy, fibrinolysis in patients who are at higher risk of adverse outcomes but are hemodynamically stable cannot be recommended until further research shows a greater clinical benefit. (LOE = 1b)
Reference
Study design
Randomized controlled trial (nonblinded)
Funding source
Industry + govt
Allocation
Concealed
Setting
Inpatient (any location)
Synopsis
These authors enrolled adult patients with acute PE who were hemodynamically stable and were considered to have an intermediate risk for adverse outcomes as indicated by right ventricular dysfunction or myocardial injury. Right ventricular dysfunction was confirmed by either echocardiography or chest computed tomography, and myocardial injury was confirmed by a positive troponin test result. Using concealed allocation, investigators randomized these patients (N = 1006) to receive either fibrinolysis with tenecteplase at a weight-based dose or matching placebo. Both groups also received full anticoagulation with unfractionated heparin. Baseline characteristics were similar in the 2 groups and analysis was by intention to treat. Fewer patients in the tenecteplase group experienced the primary outcome of death or hemodynamic decompensation at 7 days (2.6% vs 5.6%; odds ratio = 0.44; 95% CI, 0.23 - 0.87). Looking at the individual components of the composite outcome, there was no significant difference in mortality between the 2 groups (1.2% vs 1.8%), but the tenecteplase group had a decreased incidence of hemodynamic decompensation (1.6% vs 5%; P = .002). The significance of this is unclear, as one of the definitions of hemodynamic decompensation was an isolated drop in systolic blood pressure to below 90 mmHg for at least 15 minutes. Major bleeding and hemorrhagic strokes were more common in the tenecteplase group (bleeding: 11.5% vs 2.4%; strokes: 2% vs 0.2%).
Dr. Kulkarni is an assistant professor of hospital medicine at Northwestern University in Chicago.
Clinical question
Does the use of fibrinolytic therapy improve mortality and morbidity in normotensive patients with acute pulmonary embolism who are at intermediate risk for adverse outcomes?
Bottom line
For patients with acute pulmonary embolism (PE) at intermediate risk for adverse outcomes, fibrinolytic therapy (tenecteplase plus standard anticoagulation) decreases the incidence of hemodynamic decompensation but does not decrease mortality as compared with anticoagulation alone. Not surprisingly, fibrinolysis also increases bleeding and strokes. You would need to treat 20 people with tenecteplase to cause one episode of bleeding, and 45 people to cause one additional stroke. Given the significant bleeding risk with this therapy, fibrinolysis in patients who are at higher risk of adverse outcomes but are hemodynamically stable cannot be recommended until further research shows a greater clinical benefit. (LOE = 1b)
Reference
Study design
Randomized controlled trial (nonblinded)
Funding source
Industry + govt
Allocation
Concealed
Setting
Inpatient (any location)
Synopsis
These authors enrolled adult patients with acute PE who were hemodynamically stable and were considered to have an intermediate risk for adverse outcomes as indicated by right ventricular dysfunction or myocardial injury. Right ventricular dysfunction was confirmed by either echocardiography or chest computed tomography, and myocardial injury was confirmed by a positive troponin test result. Using concealed allocation, investigators randomized these patients (N = 1006) to receive either fibrinolysis with tenecteplase at a weight-based dose or matching placebo. Both groups also received full anticoagulation with unfractionated heparin. Baseline characteristics were similar in the 2 groups and analysis was by intention to treat. Fewer patients in the tenecteplase group experienced the primary outcome of death or hemodynamic decompensation at 7 days (2.6% vs 5.6%; odds ratio = 0.44; 95% CI, 0.23 - 0.87). Looking at the individual components of the composite outcome, there was no significant difference in mortality between the 2 groups (1.2% vs 1.8%), but the tenecteplase group had a decreased incidence of hemodynamic decompensation (1.6% vs 5%; P = .002). The significance of this is unclear, as one of the definitions of hemodynamic decompensation was an isolated drop in systolic blood pressure to below 90 mmHg for at least 15 minutes. Major bleeding and hemorrhagic strokes were more common in the tenecteplase group (bleeding: 11.5% vs 2.4%; strokes: 2% vs 0.2%).
Dr. Kulkarni is an assistant professor of hospital medicine at Northwestern University in Chicago.
Ramelteon Reduces Risk of Delirium in Hospitalized Patients
Clinical question
Does ramelteon, a melatonin agonist, prevent delirium in hospitalized patients?
Bottom line
In this small, single-blinded study, ramelteon was shown to be effective in preventing delirium in elderly patients who required hospitalization for acute illness. You would have to treat 3 patients with ramelteon to prevent one episode of delirium. (LOE = 1b)
Reference
Study design
Randomized controlled trial (single-blinded)
Funding source
Government
Allocation
Concealed
Setting
Inpatient (any location)
Synopsis
Using concealed allocation, these investigators randomized 67 hospitalized patients (24 admitted to intensive care units, 43 admitted to general wards) to receive either ramelteon 8 mg or placebo nightly up to 7 days or until the onset of delirium. Eligible patients were 65 years to 89 years old, were admitted to the hospital via the emergency department, were able to take oral medications, and had an expected length of stay of greater than 48 hours. Patients with psychiatric disorders, severe liver disease, Lewy body disease, or alcohol dependency were excluded. Nurses provided similar delirium prevention care to all patients, including frequent reorientation, adequate lighting, and noise reduction. If patients required treatment for insomnia, hydroxyzine was used with a dose limit of 25 mg per night. Baseline characteristics were similar in the 2 groups, with a mean age of 78 years. For the primary outcome of onset of delirium, experienced psychiatrists, masked to study group, assessed patients in the mornings and afternoons for up to 7 days using a delirium rating scale. Only 1 patient in the ramelteon group was diagnosed with delirium as compared with 11 patients in the placebo group (3% vs 32%; number needed to treat = 3; P = .003). Interestingly, there were no significant differences between the groups in sleep metrics such as difficulty falling asleep and poor sleep quality, although the sample was likely too small to detect such differences. Note that the patients were not masked in this study, which could have potentially affected the overall outcomes. No adverse effects attributed to the study drug were reported.
Dr. Kulkarni is an assistant professor of hospital medicine at Northwestern University in Chicago.
Clinical question
Does ramelteon, a melatonin agonist, prevent delirium in hospitalized patients?
Bottom line
In this small, single-blinded study, ramelteon was shown to be effective in preventing delirium in elderly patients who required hospitalization for acute illness. You would have to treat 3 patients with ramelteon to prevent one episode of delirium. (LOE = 1b)
Reference
Study design
Randomized controlled trial (single-blinded)
Funding source
Government
Allocation
Concealed
Setting
Inpatient (any location)
Synopsis
Using concealed allocation, these investigators randomized 67 hospitalized patients (24 admitted to intensive care units, 43 admitted to general wards) to receive either ramelteon 8 mg or placebo nightly up to 7 days or until the onset of delirium. Eligible patients were 65 years to 89 years old, were admitted to the hospital via the emergency department, were able to take oral medications, and had an expected length of stay of greater than 48 hours. Patients with psychiatric disorders, severe liver disease, Lewy body disease, or alcohol dependency were excluded. Nurses provided similar delirium prevention care to all patients, including frequent reorientation, adequate lighting, and noise reduction. If patients required treatment for insomnia, hydroxyzine was used with a dose limit of 25 mg per night. Baseline characteristics were similar in the 2 groups, with a mean age of 78 years. For the primary outcome of onset of delirium, experienced psychiatrists, masked to study group, assessed patients in the mornings and afternoons for up to 7 days using a delirium rating scale. Only 1 patient in the ramelteon group was diagnosed with delirium as compared with 11 patients in the placebo group (3% vs 32%; number needed to treat = 3; P = .003). Interestingly, there were no significant differences between the groups in sleep metrics such as difficulty falling asleep and poor sleep quality, although the sample was likely too small to detect such differences. Note that the patients were not masked in this study, which could have potentially affected the overall outcomes. No adverse effects attributed to the study drug were reported.
Dr. Kulkarni is an assistant professor of hospital medicine at Northwestern University in Chicago.
Clinical question
Does ramelteon, a melatonin agonist, prevent delirium in hospitalized patients?
Bottom line
In this small, single-blinded study, ramelteon was shown to be effective in preventing delirium in elderly patients who required hospitalization for acute illness. You would have to treat 3 patients with ramelteon to prevent one episode of delirium. (LOE = 1b)
Reference
Study design
Randomized controlled trial (single-blinded)
Funding source
Government
Allocation
Concealed
Setting
Inpatient (any location)
Synopsis
Using concealed allocation, these investigators randomized 67 hospitalized patients (24 admitted to intensive care units, 43 admitted to general wards) to receive either ramelteon 8 mg or placebo nightly up to 7 days or until the onset of delirium. Eligible patients were 65 years to 89 years old, were admitted to the hospital via the emergency department, were able to take oral medications, and had an expected length of stay of greater than 48 hours. Patients with psychiatric disorders, severe liver disease, Lewy body disease, or alcohol dependency were excluded. Nurses provided similar delirium prevention care to all patients, including frequent reorientation, adequate lighting, and noise reduction. If patients required treatment for insomnia, hydroxyzine was used with a dose limit of 25 mg per night. Baseline characteristics were similar in the 2 groups, with a mean age of 78 years. For the primary outcome of onset of delirium, experienced psychiatrists, masked to study group, assessed patients in the mornings and afternoons for up to 7 days using a delirium rating scale. Only 1 patient in the ramelteon group was diagnosed with delirium as compared with 11 patients in the placebo group (3% vs 32%; number needed to treat = 3; P = .003). Interestingly, there were no significant differences between the groups in sleep metrics such as difficulty falling asleep and poor sleep quality, although the sample was likely too small to detect such differences. Note that the patients were not masked in this study, which could have potentially affected the overall outcomes. No adverse effects attributed to the study drug were reported.
Dr. Kulkarni is an assistant professor of hospital medicine at Northwestern University in Chicago.
HACs may not tell the whole story
The Affordable Care Act has essentially overhauled Medicare’s payment system for hospitals in an effort to improve quality while minimizing wasteful spending.
One such change centers on HACs, or hospital-acquired conditions. These conditions were deemed potentially preventable by the Centers for Medicare & Medicaid Services in 2009 and are a major target for Medicare payment penalties and hospital quality initiatives. Hospitalizations that are complicated by one of these conditions, for instance, the development of diabetic ketoacidosis from poor glycemic control, do not qualify for higher paying diagnosis-related group payment, leaving a gaping hole between the cost of care delivered and the amount reimbursed by Medicare.
Yet to come in fiscal year 2015, Medicare payments for all discharges will be cut by 1% for those hospitals that score in the top quartile for the rate of hospital-acquired conditions, compared with national average.
Upon initially hearing about this provision in the ACA, I was shocked and felt it was both unfair and realistic, but as time has passed, it is clear that a variety of innovative hospital-based quality initiatives have made significant headway into minimizing at least some of the HACs.
Help is also available through the government. The Medicare Shared Savings and Pioneer ACO Models offer participating hospitals a share of the savings if they can reduce spending below historical benchmarks. A healthier bottom line for our hospitals has the potential to ultimately translate into improved resources and support systems to enhance our ability to provide excellent care for our patients, while making our days run more smoothly.
However, a recent study shows that HACs do not appear to be the bottom line in hospital savings after all. Identifying hospital-wide harm associated with increased cost, length of stay, and mortality in U.S. hospitals, was recently released by the Premier health care alliance, and was based on peer-reviewed research in the American Journal of Medical Quality.
Premier evaluated more than 5.5 million deidentified ICD-9 discharge records from hospitals and medical centers in 47 states. They identified 86 potential inpatient complications that were associated with higher cost, increased length of stay, and/or higher mortality.
Surprisingly, this study concluded that the current HACs used by the CMS cover only a fraction of the complications and that of the 86 high-impact conditions they evaluated, only 22 are addressed through the CMS’s federal payment policies. Conditions such as acute renal failure, which was associated with close to $490 million in costs, and hypotension, which had $200 million in costs in this study were far more significant than were the HACs such as air embolism and blood incompatibility, seen in 23 and 8 patients, respectively, in more than 5 million records.
While some of the 86 conditions identified may not be easy to prevent, others, such as acute renal failure and hypotension, have the potential to be significantly reduced through vigilant monitoring of parameters such as nephrotoxin use and blood pressure trends.
Dr. A. Maria Hester is a hospitalist with Baltimore-Washington Medical Center, Glen Burnie, Md., who has a passion for empowering patients to partner in their health care. She is the creator of the Patient Whiz, a patient-engagement app for iOS.
The Affordable Care Act has essentially overhauled Medicare’s payment system for hospitals in an effort to improve quality while minimizing wasteful spending.
One such change centers on HACs, or hospital-acquired conditions. These conditions were deemed potentially preventable by the Centers for Medicare & Medicaid Services in 2009 and are a major target for Medicare payment penalties and hospital quality initiatives. Hospitalizations that are complicated by one of these conditions, for instance, the development of diabetic ketoacidosis from poor glycemic control, do not qualify for higher paying diagnosis-related group payment, leaving a gaping hole between the cost of care delivered and the amount reimbursed by Medicare.
Yet to come in fiscal year 2015, Medicare payments for all discharges will be cut by 1% for those hospitals that score in the top quartile for the rate of hospital-acquired conditions, compared with national average.
Upon initially hearing about this provision in the ACA, I was shocked and felt it was both unfair and realistic, but as time has passed, it is clear that a variety of innovative hospital-based quality initiatives have made significant headway into minimizing at least some of the HACs.
Help is also available through the government. The Medicare Shared Savings and Pioneer ACO Models offer participating hospitals a share of the savings if they can reduce spending below historical benchmarks. A healthier bottom line for our hospitals has the potential to ultimately translate into improved resources and support systems to enhance our ability to provide excellent care for our patients, while making our days run more smoothly.
However, a recent study shows that HACs do not appear to be the bottom line in hospital savings after all. Identifying hospital-wide harm associated with increased cost, length of stay, and mortality in U.S. hospitals, was recently released by the Premier health care alliance, and was based on peer-reviewed research in the American Journal of Medical Quality.
Premier evaluated more than 5.5 million deidentified ICD-9 discharge records from hospitals and medical centers in 47 states. They identified 86 potential inpatient complications that were associated with higher cost, increased length of stay, and/or higher mortality.
Surprisingly, this study concluded that the current HACs used by the CMS cover only a fraction of the complications and that of the 86 high-impact conditions they evaluated, only 22 are addressed through the CMS’s federal payment policies. Conditions such as acute renal failure, which was associated with close to $490 million in costs, and hypotension, which had $200 million in costs in this study were far more significant than were the HACs such as air embolism and blood incompatibility, seen in 23 and 8 patients, respectively, in more than 5 million records.
While some of the 86 conditions identified may not be easy to prevent, others, such as acute renal failure and hypotension, have the potential to be significantly reduced through vigilant monitoring of parameters such as nephrotoxin use and blood pressure trends.
Dr. A. Maria Hester is a hospitalist with Baltimore-Washington Medical Center, Glen Burnie, Md., who has a passion for empowering patients to partner in their health care. She is the creator of the Patient Whiz, a patient-engagement app for iOS.
The Affordable Care Act has essentially overhauled Medicare’s payment system for hospitals in an effort to improve quality while minimizing wasteful spending.
One such change centers on HACs, or hospital-acquired conditions. These conditions were deemed potentially preventable by the Centers for Medicare & Medicaid Services in 2009 and are a major target for Medicare payment penalties and hospital quality initiatives. Hospitalizations that are complicated by one of these conditions, for instance, the development of diabetic ketoacidosis from poor glycemic control, do not qualify for higher paying diagnosis-related group payment, leaving a gaping hole between the cost of care delivered and the amount reimbursed by Medicare.
Yet to come in fiscal year 2015, Medicare payments for all discharges will be cut by 1% for those hospitals that score in the top quartile for the rate of hospital-acquired conditions, compared with national average.
Upon initially hearing about this provision in the ACA, I was shocked and felt it was both unfair and realistic, but as time has passed, it is clear that a variety of innovative hospital-based quality initiatives have made significant headway into minimizing at least some of the HACs.
Help is also available through the government. The Medicare Shared Savings and Pioneer ACO Models offer participating hospitals a share of the savings if they can reduce spending below historical benchmarks. A healthier bottom line for our hospitals has the potential to ultimately translate into improved resources and support systems to enhance our ability to provide excellent care for our patients, while making our days run more smoothly.
However, a recent study shows that HACs do not appear to be the bottom line in hospital savings after all. Identifying hospital-wide harm associated with increased cost, length of stay, and mortality in U.S. hospitals, was recently released by the Premier health care alliance, and was based on peer-reviewed research in the American Journal of Medical Quality.
Premier evaluated more than 5.5 million deidentified ICD-9 discharge records from hospitals and medical centers in 47 states. They identified 86 potential inpatient complications that were associated with higher cost, increased length of stay, and/or higher mortality.
Surprisingly, this study concluded that the current HACs used by the CMS cover only a fraction of the complications and that of the 86 high-impact conditions they evaluated, only 22 are addressed through the CMS’s federal payment policies. Conditions such as acute renal failure, which was associated with close to $490 million in costs, and hypotension, which had $200 million in costs in this study were far more significant than were the HACs such as air embolism and blood incompatibility, seen in 23 and 8 patients, respectively, in more than 5 million records.
While some of the 86 conditions identified may not be easy to prevent, others, such as acute renal failure and hypotension, have the potential to be significantly reduced through vigilant monitoring of parameters such as nephrotoxin use and blood pressure trends.
Dr. A. Maria Hester is a hospitalist with Baltimore-Washington Medical Center, Glen Burnie, Md., who has a passion for empowering patients to partner in their health care. She is the creator of the Patient Whiz, a patient-engagement app for iOS.
Factors that lead to gout often differ in men and women
PARIS – Women have different predisposing risk factors for gout than do men, who more often fit the stereotypical profile of patients with gout who consume foods that increase the risk of the disease.
In the study based on data collected from participants in the Consortium of Rheumatology Researchers of North America (CORRONA) gout registry, women with gout were more likely to have taken predisposing medications and to have more gout-associated comorbidities, whereas men were more likely to consume foods linked to the disorder, such as alcohol and red meat, according to Dr. Leslie Harrold, scientific director of the CORRONA gout registry.
"We live in an era of personalized medicine," she said in an interview. "These findings speak to the need to tailor our evaluations and treatments based on the patient. There cannot be a one-size-fits-all approach. We need to approach women with gout differently than men with gout."
Patients in the gout study were enrolled in 2012-2013. Data gathered from patients and their rheumatologists at study enrollment included demographics, predisposing factors (comorbid conditions, medications, diet), gout disease characteristics, current treatments, and physical exam findings.
The 54 participating rheumatologists enrolled 1,167 gout patients (239 women). Women were significantly older than men (71 years vs. 61 years) and had higher body mass index (34 kg/m2 vs. 23 kg/m2). They also were significantly more likely to have hypertension (77% vs. 57%), diabetes (28% vs. 17%), and renal disease (25% vs. 14%).
Women also had a shorter duration of gout when enrolled (6 years vs. 11 years) and were less likely to have a crystal-proven diagnosis (26% vs. 35%).
Medication risk factors for gout, such as diuretics, were more common in women (49% vs. 22%), while dietary risk factors were more frequent in men, who consumed significantly more beer, hard liquor, beef, and pork, Dr. Harrold reported at the annual European Congress of Rheumatology.
Although the clinical features of gout were similar between the genders at the time of initial diagnosis, women reported more frequent disability. Women were more likely to have contraindications to treatment with NSAIDs or colchicine, but women with tophi or active disease – defined as two or more flares per year – used urate-lowering therapy at a rate that was not statistically different from men (78% vs. 84%).
"I think what is most interesting is that the profile of men and women with gout differs," said Dr. Harrold of the division of rheumatology at the University of Massachusetts, Worcester. "Doctors usually have a single concept of the typical patient. But instead, here we have to realize that the typical woman with gout is different than the typical man with gout. That should frame our evaluation of suspected cases."
A number of pharmaceutical companies have financially supported the CORRONA registry. In the last 5 years, Dr. Harrold has received research funding from Takeda and has a pending grant with AstraZeneca.
PARIS – Women have different predisposing risk factors for gout than do men, who more often fit the stereotypical profile of patients with gout who consume foods that increase the risk of the disease.
In the study based on data collected from participants in the Consortium of Rheumatology Researchers of North America (CORRONA) gout registry, women with gout were more likely to have taken predisposing medications and to have more gout-associated comorbidities, whereas men were more likely to consume foods linked to the disorder, such as alcohol and red meat, according to Dr. Leslie Harrold, scientific director of the CORRONA gout registry.
"We live in an era of personalized medicine," she said in an interview. "These findings speak to the need to tailor our evaluations and treatments based on the patient. There cannot be a one-size-fits-all approach. We need to approach women with gout differently than men with gout."
Patients in the gout study were enrolled in 2012-2013. Data gathered from patients and their rheumatologists at study enrollment included demographics, predisposing factors (comorbid conditions, medications, diet), gout disease characteristics, current treatments, and physical exam findings.
The 54 participating rheumatologists enrolled 1,167 gout patients (239 women). Women were significantly older than men (71 years vs. 61 years) and had higher body mass index (34 kg/m2 vs. 23 kg/m2). They also were significantly more likely to have hypertension (77% vs. 57%), diabetes (28% vs. 17%), and renal disease (25% vs. 14%).
Women also had a shorter duration of gout when enrolled (6 years vs. 11 years) and were less likely to have a crystal-proven diagnosis (26% vs. 35%).
Medication risk factors for gout, such as diuretics, were more common in women (49% vs. 22%), while dietary risk factors were more frequent in men, who consumed significantly more beer, hard liquor, beef, and pork, Dr. Harrold reported at the annual European Congress of Rheumatology.
Although the clinical features of gout were similar between the genders at the time of initial diagnosis, women reported more frequent disability. Women were more likely to have contraindications to treatment with NSAIDs or colchicine, but women with tophi or active disease – defined as two or more flares per year – used urate-lowering therapy at a rate that was not statistically different from men (78% vs. 84%).
"I think what is most interesting is that the profile of men and women with gout differs," said Dr. Harrold of the division of rheumatology at the University of Massachusetts, Worcester. "Doctors usually have a single concept of the typical patient. But instead, here we have to realize that the typical woman with gout is different than the typical man with gout. That should frame our evaluation of suspected cases."
A number of pharmaceutical companies have financially supported the CORRONA registry. In the last 5 years, Dr. Harrold has received research funding from Takeda and has a pending grant with AstraZeneca.
PARIS – Women have different predisposing risk factors for gout than do men, who more often fit the stereotypical profile of patients with gout who consume foods that increase the risk of the disease.
In the study based on data collected from participants in the Consortium of Rheumatology Researchers of North America (CORRONA) gout registry, women with gout were more likely to have taken predisposing medications and to have more gout-associated comorbidities, whereas men were more likely to consume foods linked to the disorder, such as alcohol and red meat, according to Dr. Leslie Harrold, scientific director of the CORRONA gout registry.
"We live in an era of personalized medicine," she said in an interview. "These findings speak to the need to tailor our evaluations and treatments based on the patient. There cannot be a one-size-fits-all approach. We need to approach women with gout differently than men with gout."
Patients in the gout study were enrolled in 2012-2013. Data gathered from patients and their rheumatologists at study enrollment included demographics, predisposing factors (comorbid conditions, medications, diet), gout disease characteristics, current treatments, and physical exam findings.
The 54 participating rheumatologists enrolled 1,167 gout patients (239 women). Women were significantly older than men (71 years vs. 61 years) and had higher body mass index (34 kg/m2 vs. 23 kg/m2). They also were significantly more likely to have hypertension (77% vs. 57%), diabetes (28% vs. 17%), and renal disease (25% vs. 14%).
Women also had a shorter duration of gout when enrolled (6 years vs. 11 years) and were less likely to have a crystal-proven diagnosis (26% vs. 35%).
Medication risk factors for gout, such as diuretics, were more common in women (49% vs. 22%), while dietary risk factors were more frequent in men, who consumed significantly more beer, hard liquor, beef, and pork, Dr. Harrold reported at the annual European Congress of Rheumatology.
Although the clinical features of gout were similar between the genders at the time of initial diagnosis, women reported more frequent disability. Women were more likely to have contraindications to treatment with NSAIDs or colchicine, but women with tophi or active disease – defined as two or more flares per year – used urate-lowering therapy at a rate that was not statistically different from men (78% vs. 84%).
"I think what is most interesting is that the profile of men and women with gout differs," said Dr. Harrold of the division of rheumatology at the University of Massachusetts, Worcester. "Doctors usually have a single concept of the typical patient. But instead, here we have to realize that the typical woman with gout is different than the typical man with gout. That should frame our evaluation of suspected cases."
A number of pharmaceutical companies have financially supported the CORRONA registry. In the last 5 years, Dr. Harrold has received research funding from Takeda and has a pending grant with AstraZeneca.
AT THE EULAR CONGRESS 2014
Key clinical point: Clinicians should consider the differences in the presentation of gout between women and men and tailor their evaluation and treatment accordingly.
Major finding: Medication risk factors for gout, such as diuretics, were more common in women (49% vs. 22%), while dietary risk factors were more frequent in men, who consumed significantly more beer, hard liquor, beef, and pork.
Data source: A retrospective cohort study of 1,167 patients in the CORRONA gout registry.
Disclosures: A number of pharmaceutical companies have financially supported the CORRONA registry. In the last 5 years, Dr. Harrold has received research funding from Takeda and has a pending grant with AstraZeneca.
AG-221 sparked durable responses in hematologic cancers
MILAN – The investigational drug AG-221 induced responses in more than half of patients with advanced IDH2 mutation–positive hematologic cancers, updated phase I data showed.
Among 25 evaluable patients, 14 responded to treatment with AG-221: 6 had complete responses, 2 had complete responses with incomplete platelet count recovery, 1 had a complete response with incomplete hematologic recovery, and 5 had partial responses.
Twelve of 14 responses are ongoing, and five patients with stable disease remain on study.
Responses are seen in acute myelogenous leukemia, myelodysplastic syndromes, and chronic myelomonocytic leukemia, Dr. Stéphane de Botton said during a late-breaking abstract session at the annual congress of the European Hematology Association.
"Very interestingly, at least in five patients, the duration of the responses has reached greater than 2.5 months," he said.
AG-221 is a first-in-class inhibitor of the isocitrate dehydrogenase–2 (IDH2) protein and was just granted orphan drug status by the Food and Drug Administration for the treatment of acute myelogenous leukemia (AML).
About 15% of patients with AML carry an IDH2 mutation, as do 5% with myelodysplastic syndromes.
An initial report from this phase I, multicenter study showed five of seven patients evaluable at that time had a complete response or platelet count recovery after treatment with AG-221.
Of the 35 patients now enrolled, 27 had relapsed or refractory AML, 4 had myelodysplastic syndromes, 2 had untreated AML, 1 had chronic myelomonocytic leukemia, and 1 had granulocytic sarcoma. Patients’ mean age was 66 years, 31 had IDH2 R140Q mutations, and 4 had IDH2 R172K mutations.
Up to 100% plasma 2-hydroxyglutarate inhibition was seen after multiple doses in R140Q patients and up to 60% plasma 2-HG inhibition, in R172K patients, said Dr. de Botton, head of hematology, Institut Gustave Roussy, Villejuif, France.
Dose escalation has continued with single-agent oral dosing ranging from 30 mg twice daily to 150 mg once daily in 28-day cycles. The results were very similar with 50 mg b.i.d. and 100 mg every day.
AG-221 was also "remarkably well tolerated," with the maximum tolerated dose yet to be reached, he said.
The majority of adverse events are grade 1 and 2, notably edema, leukocytosis, nausea, sepsis, and thrombocytopenia.
Grade 3 or higher events in 18 evaluable patients included 3 cases each of thrombocytopenia and febrile neutropenia, 2 of leukocytosis, and 1 case each of diarrhea and rash, he said.
There have been four possible treatment-related serious adverse events: grade 3 confusion and grade 5 respiratory failure in a patient with severe sepsis, one case of grade 3 leukocytosis along with grade 3 anorexia and grade 1 nausea, one case of grade 3 diarrhea, and one case of grade 3 leukocytosis.
There have been seven deaths within 30 days of study drug termination: five stemming from complications of disease-related sepsis, one from complications of a humeral fracture not related to the study drug, and one from stroke, also unrelated to treatment, Dr. de Botton said.
"AG-221 is safe and well tolerated to date with durable clinical activity," he concluded.
Dr. de Botton reported research funding from Agios Pharmaceuticals, the study sponsor.
MILAN – The investigational drug AG-221 induced responses in more than half of patients with advanced IDH2 mutation–positive hematologic cancers, updated phase I data showed.
Among 25 evaluable patients, 14 responded to treatment with AG-221: 6 had complete responses, 2 had complete responses with incomplete platelet count recovery, 1 had a complete response with incomplete hematologic recovery, and 5 had partial responses.
Twelve of 14 responses are ongoing, and five patients with stable disease remain on study.
Responses are seen in acute myelogenous leukemia, myelodysplastic syndromes, and chronic myelomonocytic leukemia, Dr. Stéphane de Botton said during a late-breaking abstract session at the annual congress of the European Hematology Association.
"Very interestingly, at least in five patients, the duration of the responses has reached greater than 2.5 months," he said.
AG-221 is a first-in-class inhibitor of the isocitrate dehydrogenase–2 (IDH2) protein and was just granted orphan drug status by the Food and Drug Administration for the treatment of acute myelogenous leukemia (AML).
About 15% of patients with AML carry an IDH2 mutation, as do 5% with myelodysplastic syndromes.
An initial report from this phase I, multicenter study showed five of seven patients evaluable at that time had a complete response or platelet count recovery after treatment with AG-221.
Of the 35 patients now enrolled, 27 had relapsed or refractory AML, 4 had myelodysplastic syndromes, 2 had untreated AML, 1 had chronic myelomonocytic leukemia, and 1 had granulocytic sarcoma. Patients’ mean age was 66 years, 31 had IDH2 R140Q mutations, and 4 had IDH2 R172K mutations.
Up to 100% plasma 2-hydroxyglutarate inhibition was seen after multiple doses in R140Q patients and up to 60% plasma 2-HG inhibition, in R172K patients, said Dr. de Botton, head of hematology, Institut Gustave Roussy, Villejuif, France.
Dose escalation has continued with single-agent oral dosing ranging from 30 mg twice daily to 150 mg once daily in 28-day cycles. The results were very similar with 50 mg b.i.d. and 100 mg every day.
AG-221 was also "remarkably well tolerated," with the maximum tolerated dose yet to be reached, he said.
The majority of adverse events are grade 1 and 2, notably edema, leukocytosis, nausea, sepsis, and thrombocytopenia.
Grade 3 or higher events in 18 evaluable patients included 3 cases each of thrombocytopenia and febrile neutropenia, 2 of leukocytosis, and 1 case each of diarrhea and rash, he said.
There have been four possible treatment-related serious adverse events: grade 3 confusion and grade 5 respiratory failure in a patient with severe sepsis, one case of grade 3 leukocytosis along with grade 3 anorexia and grade 1 nausea, one case of grade 3 diarrhea, and one case of grade 3 leukocytosis.
There have been seven deaths within 30 days of study drug termination: five stemming from complications of disease-related sepsis, one from complications of a humeral fracture not related to the study drug, and one from stroke, also unrelated to treatment, Dr. de Botton said.
"AG-221 is safe and well tolerated to date with durable clinical activity," he concluded.
Dr. de Botton reported research funding from Agios Pharmaceuticals, the study sponsor.
MILAN – The investigational drug AG-221 induced responses in more than half of patients with advanced IDH2 mutation–positive hematologic cancers, updated phase I data showed.
Among 25 evaluable patients, 14 responded to treatment with AG-221: 6 had complete responses, 2 had complete responses with incomplete platelet count recovery, 1 had a complete response with incomplete hematologic recovery, and 5 had partial responses.
Twelve of 14 responses are ongoing, and five patients with stable disease remain on study.
Responses are seen in acute myelogenous leukemia, myelodysplastic syndromes, and chronic myelomonocytic leukemia, Dr. Stéphane de Botton said during a late-breaking abstract session at the annual congress of the European Hematology Association.
"Very interestingly, at least in five patients, the duration of the responses has reached greater than 2.5 months," he said.
AG-221 is a first-in-class inhibitor of the isocitrate dehydrogenase–2 (IDH2) protein and was just granted orphan drug status by the Food and Drug Administration for the treatment of acute myelogenous leukemia (AML).
About 15% of patients with AML carry an IDH2 mutation, as do 5% with myelodysplastic syndromes.
An initial report from this phase I, multicenter study showed five of seven patients evaluable at that time had a complete response or platelet count recovery after treatment with AG-221.
Of the 35 patients now enrolled, 27 had relapsed or refractory AML, 4 had myelodysplastic syndromes, 2 had untreated AML, 1 had chronic myelomonocytic leukemia, and 1 had granulocytic sarcoma. Patients’ mean age was 66 years, 31 had IDH2 R140Q mutations, and 4 had IDH2 R172K mutations.
Up to 100% plasma 2-hydroxyglutarate inhibition was seen after multiple doses in R140Q patients and up to 60% plasma 2-HG inhibition, in R172K patients, said Dr. de Botton, head of hematology, Institut Gustave Roussy, Villejuif, France.
Dose escalation has continued with single-agent oral dosing ranging from 30 mg twice daily to 150 mg once daily in 28-day cycles. The results were very similar with 50 mg b.i.d. and 100 mg every day.
AG-221 was also "remarkably well tolerated," with the maximum tolerated dose yet to be reached, he said.
The majority of adverse events are grade 1 and 2, notably edema, leukocytosis, nausea, sepsis, and thrombocytopenia.
Grade 3 or higher events in 18 evaluable patients included 3 cases each of thrombocytopenia and febrile neutropenia, 2 of leukocytosis, and 1 case each of diarrhea and rash, he said.
There have been four possible treatment-related serious adverse events: grade 3 confusion and grade 5 respiratory failure in a patient with severe sepsis, one case of grade 3 leukocytosis along with grade 3 anorexia and grade 1 nausea, one case of grade 3 diarrhea, and one case of grade 3 leukocytosis.
There have been seven deaths within 30 days of study drug termination: five stemming from complications of disease-related sepsis, one from complications of a humeral fracture not related to the study drug, and one from stroke, also unrelated to treatment, Dr. de Botton said.
"AG-221 is safe and well tolerated to date with durable clinical activity," he concluded.
Dr. de Botton reported research funding from Agios Pharmaceuticals, the study sponsor.
AT THE EHA CONGRESS
Key clinical point: AG-221 could shift the treatment for IDH2 mutation-positive hematologic cancers.
Major finding: Fourteen of 25 patients responded to treatment with AG-221.
Data source: A prospective phase I dose-escalation study in 35 patients with hematologic cancers.
Disclosures: Dr. de Botton reported research funding from Agios Pharmaceuticals, the study sponsor.
Post-World War II psychiatry: 70 years of momentous change
A large percentage of psychiatrists practicing today are Boomers, and have experienced the tumultuous change in their profession since the end of World War II. At a recent Grand Rounds presentation in the Department of Neurology & Psychiatry at Saint Louis University, participants examined major changes and paradigm shifts that have reshaped psychiatry since 1946. The audience, which included me, contributed historical observations to the list of those changes and shifts, which I’ve classified here for your benefit, whether or not you are a Boomer.
Medical advances
Consider these discoveries and developments:
• Penicillin in 1947, which led to a reduction in cases of psychosis caused by tertiary syphilis, a disease that accounted for 10% to 15% of state hospital admissions.
• Lithium in 1948, the first pharmaceutical treatment for mania.
• Chlorpromazine, the first antipsychotic drug, in 1952, launching the psychopharmacology era and ending lifetime institutional sequestration as the only “treatment” for serious mental disorders.
• Monoamine oxidase inhibitors in 1959, from observations that iproniazid, a drug used in tuberculosis sanitariums, improved the mood of tuberculosis patients. This was the first pharmacotherapy for depression, which had been treated with electroconvulsive therapy (ECT), developed in the 1930s.
• Tricyclic antidepressants, starting with imipramine in the late 1950s, during attempts to synthesize additional phenothiazine antipsychotics.
• Diazepam, introduced in 1963 for its anti-anxiety effects, became the most widely used drug in the world over the next 2 decades.
• Pre-frontal lobotomy to treat severe psychiatric disorders. The neurosurgeon-inventor of this so-called medical advance won the 1949 Nobel Prize for Medicine or Physiology. The procedure was rapidly discredited after the development of antipsychotic drugs.
• Fluoxetine, the first selective serotonin reuptake inhibitor, in 1987, revolutionized the treatment of depression, especially in primary care settings.
• Clozapine, as an effective treatment for refractory and suicidal schizophrenia, and the spawning of second-generation antipsychotics. These newer agents shifted focus from neurologic adverse effects (extrapyramidal symptoms, tardive dyskinesia) to cardio-metabolic side effects (obesity, diabetes, dyslipidemia, and hypertension).
Changes to the landscape of health care
Three noteworthy developments made the list:
• The Community Mental Health Act of 1963, signed into law by President John F. Kennedy, revolutionized psychiatric care by shifting delivery of care from inpatient, hospital-based facilities to outpatient, clinic-based centers. There are now close to 800 community mental health centers in the United States, where care is dominated by non-physician mental health providers—in contrast to the era of state hospitals, during which physicians and nurses provided care for mentally ill patients.
• Deinstitutionalization. This move-ment gathered momentum in the 1970s and 1980s, leading to closing of the majority of state hospitals, with tragic consequences for the seriously mentally ill—including early demise, homelessness, substance abuse, and incarceration. In fact, the large percentage of mentally ill people in U.S. jails and prisons, instead of in a hospital, represents what has been labeled trans-institutionalization (see my March 2008 editorial, “Bring back the asylums?,” available at CurrentPsychiatry.com).
• Managed care, emerging in the late 1980s and early 1990s, caused a seismic disturbance in the delivery of, and reimbursement for, psychiatric care. The result was a significant decline in access to, and quality of, care—especially the so-called carve-out model that reduced payment for psychiatric care even more drastically than for general medical care. Under managed care, the priority became saving money, rather than saving lives. Average hospital stay for patients who had a psychiatric disorder, which was years in the pre-pharmacotherapy era, and weeks or months after that, shrunk to a few days under managed care.
Changes in professional direction
Two major shifts in the complexion of the specialty were identified:
• The decline of psychoanalysis, which had dominated psychiatry for decades (the 1940s through the 1970s), was a major shift in the conceptualization, training, and delivery of care in psychiatry. The rise of biological psychiatry and the medical model of psychiatric brain disorders, as well as the emergence of evidence-based (and briefer) psychotherapies (eg, cognitive-behavioral therapy, dialectical behavior therapy, and interpersonal therapy), gradually replaced the Freudian model of mental illness.
As a result, it became no longer necessary to be a certified psychoanalyst to be named chair of a department of psychiatry. The impact of this change on psychiatric training has been profound, because medical management by psychiatrists superseded psychotherapy— given the brief hospitalization that is required and the diminishing coverage for psychotherapy by insurers.
• Delegation of psychosocial treatments to non-psychiatrists. The unintended consequences of psychiatrists’ change of focus to 1) consultation on medical/surgical patients and 2) the medical evaluation, diagnosis, and pharmacotherapy of mental disorders led to the so-called “dual treatment model” for the most seriously mentally ill patients: The physician provides medical management and non-physician mental health professionals provide counseling, psychosocial therapy, and rehabilitation.
Disruptive breakthroughs
Several are notable:
• National Institute of Mental Health (NIMH). Establishment of NIMH in April 1949 was a major step toward funding research into psychiatric disorders. Billions of dollars have been invested to generate knowledge about the causes, treatment, course, and prevention of mental illness. No other country has spent as much on psychiatric research. It would have been nearly impossible to discover what we know today without the work of NIMH.
• Neuroscience. The meteoric rise of neuroscience from the 1960s to the present has had a dramatic effect, transforming old psychiatry and the study and therapy of the mind to a focus on the brain-mind continuum and the prospects of brain repair and neuroplasticity. Psychiatry is now regarded as a clinical neuroscience specialty of brain disorders that manifest as changes in thought, affect, mood, cognition, and behavior.
• Brain imaging. Techniques developed since the 1970s—the veritable alphabet soup of CT, PET, SPECT, MRI, MRS, fMRI, and DTI— has revolutionized understanding of brain structure and function in all psychiatric disorders but especially in psychotic and mood disorders.
• Molecular genetics. Advances over the past 2 decades have shed unprecedented light on the complex genetics of psychiatric disorders. It is becoming apparent that most psychiatric disorders are caused via gene-by-environment interaction; etiology is therefore a consequence of genetic and non-genetic variables. Risk genes, copy number variants, and de novo mutations are being discovered almost weekly, and progress in epigenetics holds promise for preventing medical disorders, including psychiatric illness.
• Neuromodulation. Advances represent an important paradigm shift, from pharmacotherapy to brain stimulation. Several techniques have been approved by the FDA, including transcranial magnetic stimulation, vagus nerve stimulation, and deep brain stimulation, to supplement, and perhaps eventually supplant, ECT.
Legal intrusiveness
No other medical specialty has been subject to laws governing clinical practice as psychiatry has been. Progressive intrusion of laws (ostensibly, enacted to protect the civil rights of “the disabled”) ends up hurting patients who refuse admission and then often harm themselves or others or decline urgent treatment, which can be associated with loss of brain tissue in acute psychotic, manic, and depressed states. No legal shackles apply to treating unconscious stroke patients, delirious geriatric patients, or semiconscious myocardial infarction patients when they are admitted to a hospital.
Distortions of the anti-psychiatry movement
The antipsychiatry movement preceded the Baby Boomer era by a century but has continued unabated. The movement gained momentum and became more defamatory after release of the movie One Flew Over the Cuckoo’s Nest in 1975, which portrayed psychiatry in a purely negative light. Despite progress in public understanding of psychiatry, and tangible improvements in practice, the stigma of mental illness persists. Media portrayals, including motion pictures, continue to distort the good that psychiatrists do for their patients.
Gender and sexuality
• Gender distribution of psychiatrists. A major shift occurred over the past 7 decades, reflecting the same pattern that has been documented in other medical specialties. At least one-half of psychiatry residents are now women—a welcome change from the pre-1946 era, when nearly all psychiatrists were men. This demographic transformation has had an impact on the dynamics of psychiatric practice.
• Acceptance and depathologization of homosexuality. Until 1974, homosexuality was considered a psychiatric disorder, and many homosexual persons sought treatment. That year, membership of the American Psychiatric Association voted to remove homosexuality from DSM-II and to no longer regard it as a behavioral abnormality. This was a huge step toward de-pathologizing same-sex orientation and love, and might have been the major impetus for the progressive social acceptance of gay, lesbian, and transgendered people over the past 4 decades.
The DSM paradigm shift in psychiatric diagnosis
• DSM-III. Perhaps the most radical change in the diagnostic criteria of psychiatric disorders occurred in 1980, with introduction of DSM-III to replace DSM-I and DSM-II, which were absurdly vague, unreliable, and with poor validity.
The move toward more operational and reliable diagnostic requirements began with the Research Diagnostic Criteria, developed by the Department of Psychiatry at Washington University in St. Louis. DSM-III represented a complete paradigm shift in psychiatric diagnosis. Subsequent editions maintained the same methodology, with relatively modest changes. The field expects continued evolution in DSM diagnostic criteria, including the future inclusion of biomarkers, based on sound, controlled studies.
• Recognizing PTSD. Develop-ment of posttraumatic stress disorder (PTSD) as a diagnostic entity, and its inclusion in DSM-III, were major changes in psychiatric nosology. At last, the old terms—shell shock, battle fatigue, neurasthenia—were legitimized as a recognizable syndrome secondary to major life trauma, including war and rape. That legitimacy has instigated substantial clinical and research interest in identifying how serious psychopathology can be triggered by life events.
Pharmaceutical industry debacle
Few industries have fallen so far from grace in the eyes of psychiatric professionals and the public as the manufacturers of psychotropic drugs.
At the dawn of the psychopharmacology era (the 1950s, 1960s, and 1970s) pharmaceutical companies were respected and regarded by physicians and patients as a vital partner in health care for their discovery and development of medications to treat psychiatric disorders. That image was tarnished in the 1990s, however, with the approval and release of several atypical antipsychotics. Cutthroat competition, questionable publication methods, concealment of negative findings, and excessive spending on marketing, including FDA-approved educational programs for clinicians on efficacy, safety, and dosing, all contributed to escalating cynicism about the industry. Academic faculty who received research grants to conduct FDA-required clinical trials of new agents were painted with the same brush.
Disclosure of potential conflict of interest became a mandatory procedure at universities and for NIMH grant applicants and journal publishers. Class-action lawsuits against companies that manufacture second-generation antipsychotics—filed for lack of transparency about metabolic side effects—exacerbated the intensity of criticism and condemnation.
Although new drug development has become measurably more rigorous and ethical because of self-regulation, combined with vigorous government scrutiny and regulation, demonization of the pharmaceutical industry remains unabated. That might be the reason why several major pharmaceutical companies have abandoned research and development of psychotropic drugs. That is likely to impede progress in psychopharmacotherapeutics; after all, no other private or government entity develops drugs for patients who have a psychiatric illness. The need for such agents is great: There is no FDA-indicated drug for the majority of DSM-5 diagnoses.
We entrust the future to next generations
Momentous events have transformed psychiatry during the lifespan of Baby Boomers like me and many of you. Because the cohort of 80 million Baby Boomers has comprised a significant percentage of the nation’s scientists, media representatives, members of the American Psychiatric Association, academicians, and community leaders over the past few decades, it is conceivable that the Baby Boomer generation helped trigger most of the transformative changes in psychiatry we have seen over the past 70 years.
I can only wonder: What direction will psychiatry take in the age of Generation X, Generation Y, and the Millennials? Only this is certain: Psychiatry will continue to evolve— long after Baby Boomers are gone.
A large percentage of psychiatrists practicing today are Boomers, and have experienced the tumultuous change in their profession since the end of World War II. At a recent Grand Rounds presentation in the Department of Neurology & Psychiatry at Saint Louis University, participants examined major changes and paradigm shifts that have reshaped psychiatry since 1946. The audience, which included me, contributed historical observations to the list of those changes and shifts, which I’ve classified here for your benefit, whether or not you are a Boomer.
Medical advances
Consider these discoveries and developments:
• Penicillin in 1947, which led to a reduction in cases of psychosis caused by tertiary syphilis, a disease that accounted for 10% to 15% of state hospital admissions.
• Lithium in 1948, the first pharmaceutical treatment for mania.
• Chlorpromazine, the first antipsychotic drug, in 1952, launching the psychopharmacology era and ending lifetime institutional sequestration as the only “treatment” for serious mental disorders.
• Monoamine oxidase inhibitors in 1959, from observations that iproniazid, a drug used in tuberculosis sanitariums, improved the mood of tuberculosis patients. This was the first pharmacotherapy for depression, which had been treated with electroconvulsive therapy (ECT), developed in the 1930s.
• Tricyclic antidepressants, starting with imipramine in the late 1950s, during attempts to synthesize additional phenothiazine antipsychotics.
• Diazepam, introduced in 1963 for its anti-anxiety effects, became the most widely used drug in the world over the next 2 decades.
• Pre-frontal lobotomy to treat severe psychiatric disorders. The neurosurgeon-inventor of this so-called medical advance won the 1949 Nobel Prize for Medicine or Physiology. The procedure was rapidly discredited after the development of antipsychotic drugs.
• Fluoxetine, the first selective serotonin reuptake inhibitor, in 1987, revolutionized the treatment of depression, especially in primary care settings.
• Clozapine, as an effective treatment for refractory and suicidal schizophrenia, and the spawning of second-generation antipsychotics. These newer agents shifted focus from neurologic adverse effects (extrapyramidal symptoms, tardive dyskinesia) to cardio-metabolic side effects (obesity, diabetes, dyslipidemia, and hypertension).
Changes to the landscape of health care
Three noteworthy developments made the list:
• The Community Mental Health Act of 1963, signed into law by President John F. Kennedy, revolutionized psychiatric care by shifting delivery of care from inpatient, hospital-based facilities to outpatient, clinic-based centers. There are now close to 800 community mental health centers in the United States, where care is dominated by non-physician mental health providers—in contrast to the era of state hospitals, during which physicians and nurses provided care for mentally ill patients.
• Deinstitutionalization. This move-ment gathered momentum in the 1970s and 1980s, leading to closing of the majority of state hospitals, with tragic consequences for the seriously mentally ill—including early demise, homelessness, substance abuse, and incarceration. In fact, the large percentage of mentally ill people in U.S. jails and prisons, instead of in a hospital, represents what has been labeled trans-institutionalization (see my March 2008 editorial, “Bring back the asylums?,” available at CurrentPsychiatry.com).
• Managed care, emerging in the late 1980s and early 1990s, caused a seismic disturbance in the delivery of, and reimbursement for, psychiatric care. The result was a significant decline in access to, and quality of, care—especially the so-called carve-out model that reduced payment for psychiatric care even more drastically than for general medical care. Under managed care, the priority became saving money, rather than saving lives. Average hospital stay for patients who had a psychiatric disorder, which was years in the pre-pharmacotherapy era, and weeks or months after that, shrunk to a few days under managed care.
Changes in professional direction
Two major shifts in the complexion of the specialty were identified:
• The decline of psychoanalysis, which had dominated psychiatry for decades (the 1940s through the 1970s), was a major shift in the conceptualization, training, and delivery of care in psychiatry. The rise of biological psychiatry and the medical model of psychiatric brain disorders, as well as the emergence of evidence-based (and briefer) psychotherapies (eg, cognitive-behavioral therapy, dialectical behavior therapy, and interpersonal therapy), gradually replaced the Freudian model of mental illness.
As a result, it became no longer necessary to be a certified psychoanalyst to be named chair of a department of psychiatry. The impact of this change on psychiatric training has been profound, because medical management by psychiatrists superseded psychotherapy— given the brief hospitalization that is required and the diminishing coverage for psychotherapy by insurers.
• Delegation of psychosocial treatments to non-psychiatrists. The unintended consequences of psychiatrists’ change of focus to 1) consultation on medical/surgical patients and 2) the medical evaluation, diagnosis, and pharmacotherapy of mental disorders led to the so-called “dual treatment model” for the most seriously mentally ill patients: The physician provides medical management and non-physician mental health professionals provide counseling, psychosocial therapy, and rehabilitation.
Disruptive breakthroughs
Several are notable:
• National Institute of Mental Health (NIMH). Establishment of NIMH in April 1949 was a major step toward funding research into psychiatric disorders. Billions of dollars have been invested to generate knowledge about the causes, treatment, course, and prevention of mental illness. No other country has spent as much on psychiatric research. It would have been nearly impossible to discover what we know today without the work of NIMH.
• Neuroscience. The meteoric rise of neuroscience from the 1960s to the present has had a dramatic effect, transforming old psychiatry and the study and therapy of the mind to a focus on the brain-mind continuum and the prospects of brain repair and neuroplasticity. Psychiatry is now regarded as a clinical neuroscience specialty of brain disorders that manifest as changes in thought, affect, mood, cognition, and behavior.
• Brain imaging. Techniques developed since the 1970s—the veritable alphabet soup of CT, PET, SPECT, MRI, MRS, fMRI, and DTI— has revolutionized understanding of brain structure and function in all psychiatric disorders but especially in psychotic and mood disorders.
• Molecular genetics. Advances over the past 2 decades have shed unprecedented light on the complex genetics of psychiatric disorders. It is becoming apparent that most psychiatric disorders are caused via gene-by-environment interaction; etiology is therefore a consequence of genetic and non-genetic variables. Risk genes, copy number variants, and de novo mutations are being discovered almost weekly, and progress in epigenetics holds promise for preventing medical disorders, including psychiatric illness.
• Neuromodulation. Advances represent an important paradigm shift, from pharmacotherapy to brain stimulation. Several techniques have been approved by the FDA, including transcranial magnetic stimulation, vagus nerve stimulation, and deep brain stimulation, to supplement, and perhaps eventually supplant, ECT.
Legal intrusiveness
No other medical specialty has been subject to laws governing clinical practice as psychiatry has been. Progressive intrusion of laws (ostensibly, enacted to protect the civil rights of “the disabled”) ends up hurting patients who refuse admission and then often harm themselves or others or decline urgent treatment, which can be associated with loss of brain tissue in acute psychotic, manic, and depressed states. No legal shackles apply to treating unconscious stroke patients, delirious geriatric patients, or semiconscious myocardial infarction patients when they are admitted to a hospital.
Distortions of the anti-psychiatry movement
The antipsychiatry movement preceded the Baby Boomer era by a century but has continued unabated. The movement gained momentum and became more defamatory after release of the movie One Flew Over the Cuckoo’s Nest in 1975, which portrayed psychiatry in a purely negative light. Despite progress in public understanding of psychiatry, and tangible improvements in practice, the stigma of mental illness persists. Media portrayals, including motion pictures, continue to distort the good that psychiatrists do for their patients.
Gender and sexuality
• Gender distribution of psychiatrists. A major shift occurred over the past 7 decades, reflecting the same pattern that has been documented in other medical specialties. At least one-half of psychiatry residents are now women—a welcome change from the pre-1946 era, when nearly all psychiatrists were men. This demographic transformation has had an impact on the dynamics of psychiatric practice.
• Acceptance and depathologization of homosexuality. Until 1974, homosexuality was considered a psychiatric disorder, and many homosexual persons sought treatment. That year, membership of the American Psychiatric Association voted to remove homosexuality from DSM-II and to no longer regard it as a behavioral abnormality. This was a huge step toward de-pathologizing same-sex orientation and love, and might have been the major impetus for the progressive social acceptance of gay, lesbian, and transgendered people over the past 4 decades.
The DSM paradigm shift in psychiatric diagnosis
• DSM-III. Perhaps the most radical change in the diagnostic criteria of psychiatric disorders occurred in 1980, with introduction of DSM-III to replace DSM-I and DSM-II, which were absurdly vague, unreliable, and with poor validity.
The move toward more operational and reliable diagnostic requirements began with the Research Diagnostic Criteria, developed by the Department of Psychiatry at Washington University in St. Louis. DSM-III represented a complete paradigm shift in psychiatric diagnosis. Subsequent editions maintained the same methodology, with relatively modest changes. The field expects continued evolution in DSM diagnostic criteria, including the future inclusion of biomarkers, based on sound, controlled studies.
• Recognizing PTSD. Develop-ment of posttraumatic stress disorder (PTSD) as a diagnostic entity, and its inclusion in DSM-III, were major changes in psychiatric nosology. At last, the old terms—shell shock, battle fatigue, neurasthenia—were legitimized as a recognizable syndrome secondary to major life trauma, including war and rape. That legitimacy has instigated substantial clinical and research interest in identifying how serious psychopathology can be triggered by life events.
Pharmaceutical industry debacle
Few industries have fallen so far from grace in the eyes of psychiatric professionals and the public as the manufacturers of psychotropic drugs.
At the dawn of the psychopharmacology era (the 1950s, 1960s, and 1970s) pharmaceutical companies were respected and regarded by physicians and patients as a vital partner in health care for their discovery and development of medications to treat psychiatric disorders. That image was tarnished in the 1990s, however, with the approval and release of several atypical antipsychotics. Cutthroat competition, questionable publication methods, concealment of negative findings, and excessive spending on marketing, including FDA-approved educational programs for clinicians on efficacy, safety, and dosing, all contributed to escalating cynicism about the industry. Academic faculty who received research grants to conduct FDA-required clinical trials of new agents were painted with the same brush.
Disclosure of potential conflict of interest became a mandatory procedure at universities and for NIMH grant applicants and journal publishers. Class-action lawsuits against companies that manufacture second-generation antipsychotics—filed for lack of transparency about metabolic side effects—exacerbated the intensity of criticism and condemnation.
Although new drug development has become measurably more rigorous and ethical because of self-regulation, combined with vigorous government scrutiny and regulation, demonization of the pharmaceutical industry remains unabated. That might be the reason why several major pharmaceutical companies have abandoned research and development of psychotropic drugs. That is likely to impede progress in psychopharmacotherapeutics; after all, no other private or government entity develops drugs for patients who have a psychiatric illness. The need for such agents is great: There is no FDA-indicated drug for the majority of DSM-5 diagnoses.
We entrust the future to next generations
Momentous events have transformed psychiatry during the lifespan of Baby Boomers like me and many of you. Because the cohort of 80 million Baby Boomers has comprised a significant percentage of the nation’s scientists, media representatives, members of the American Psychiatric Association, academicians, and community leaders over the past few decades, it is conceivable that the Baby Boomer generation helped trigger most of the transformative changes in psychiatry we have seen over the past 70 years.
I can only wonder: What direction will psychiatry take in the age of Generation X, Generation Y, and the Millennials? Only this is certain: Psychiatry will continue to evolve— long after Baby Boomers are gone.
A large percentage of psychiatrists practicing today are Boomers, and have experienced the tumultuous change in their profession since the end of World War II. At a recent Grand Rounds presentation in the Department of Neurology & Psychiatry at Saint Louis University, participants examined major changes and paradigm shifts that have reshaped psychiatry since 1946. The audience, which included me, contributed historical observations to the list of those changes and shifts, which I’ve classified here for your benefit, whether or not you are a Boomer.
Medical advances
Consider these discoveries and developments:
• Penicillin in 1947, which led to a reduction in cases of psychosis caused by tertiary syphilis, a disease that accounted for 10% to 15% of state hospital admissions.
• Lithium in 1948, the first pharmaceutical treatment for mania.
• Chlorpromazine, the first antipsychotic drug, in 1952, launching the psychopharmacology era and ending lifetime institutional sequestration as the only “treatment” for serious mental disorders.
• Monoamine oxidase inhibitors in 1959, from observations that iproniazid, a drug used in tuberculosis sanitariums, improved the mood of tuberculosis patients. This was the first pharmacotherapy for depression, which had been treated with electroconvulsive therapy (ECT), developed in the 1930s.
• Tricyclic antidepressants, starting with imipramine in the late 1950s, during attempts to synthesize additional phenothiazine antipsychotics.
• Diazepam, introduced in 1963 for its anti-anxiety effects, became the most widely used drug in the world over the next 2 decades.
• Pre-frontal lobotomy to treat severe psychiatric disorders. The neurosurgeon-inventor of this so-called medical advance won the 1949 Nobel Prize for Medicine or Physiology. The procedure was rapidly discredited after the development of antipsychotic drugs.
• Fluoxetine, the first selective serotonin reuptake inhibitor, in 1987, revolutionized the treatment of depression, especially in primary care settings.
• Clozapine, as an effective treatment for refractory and suicidal schizophrenia, and the spawning of second-generation antipsychotics. These newer agents shifted focus from neurologic adverse effects (extrapyramidal symptoms, tardive dyskinesia) to cardio-metabolic side effects (obesity, diabetes, dyslipidemia, and hypertension).
Changes to the landscape of health care
Three noteworthy developments made the list:
• The Community Mental Health Act of 1963, signed into law by President John F. Kennedy, revolutionized psychiatric care by shifting delivery of care from inpatient, hospital-based facilities to outpatient, clinic-based centers. There are now close to 800 community mental health centers in the United States, where care is dominated by non-physician mental health providers—in contrast to the era of state hospitals, during which physicians and nurses provided care for mentally ill patients.
• Deinstitutionalization. This move-ment gathered momentum in the 1970s and 1980s, leading to closing of the majority of state hospitals, with tragic consequences for the seriously mentally ill—including early demise, homelessness, substance abuse, and incarceration. In fact, the large percentage of mentally ill people in U.S. jails and prisons, instead of in a hospital, represents what has been labeled trans-institutionalization (see my March 2008 editorial, “Bring back the asylums?,” available at CurrentPsychiatry.com).
• Managed care, emerging in the late 1980s and early 1990s, caused a seismic disturbance in the delivery of, and reimbursement for, psychiatric care. The result was a significant decline in access to, and quality of, care—especially the so-called carve-out model that reduced payment for psychiatric care even more drastically than for general medical care. Under managed care, the priority became saving money, rather than saving lives. Average hospital stay for patients who had a psychiatric disorder, which was years in the pre-pharmacotherapy era, and weeks or months after that, shrunk to a few days under managed care.
Changes in professional direction
Two major shifts in the complexion of the specialty were identified:
• The decline of psychoanalysis, which had dominated psychiatry for decades (the 1940s through the 1970s), was a major shift in the conceptualization, training, and delivery of care in psychiatry. The rise of biological psychiatry and the medical model of psychiatric brain disorders, as well as the emergence of evidence-based (and briefer) psychotherapies (eg, cognitive-behavioral therapy, dialectical behavior therapy, and interpersonal therapy), gradually replaced the Freudian model of mental illness.
As a result, it became no longer necessary to be a certified psychoanalyst to be named chair of a department of psychiatry. The impact of this change on psychiatric training has been profound, because medical management by psychiatrists superseded psychotherapy— given the brief hospitalization that is required and the diminishing coverage for psychotherapy by insurers.
• Delegation of psychosocial treatments to non-psychiatrists. The unintended consequences of psychiatrists’ change of focus to 1) consultation on medical/surgical patients and 2) the medical evaluation, diagnosis, and pharmacotherapy of mental disorders led to the so-called “dual treatment model” for the most seriously mentally ill patients: The physician provides medical management and non-physician mental health professionals provide counseling, psychosocial therapy, and rehabilitation.
Disruptive breakthroughs
Several are notable:
• National Institute of Mental Health (NIMH). Establishment of NIMH in April 1949 was a major step toward funding research into psychiatric disorders. Billions of dollars have been invested to generate knowledge about the causes, treatment, course, and prevention of mental illness. No other country has spent as much on psychiatric research. It would have been nearly impossible to discover what we know today without the work of NIMH.
• Neuroscience. The meteoric rise of neuroscience from the 1960s to the present has had a dramatic effect, transforming old psychiatry and the study and therapy of the mind to a focus on the brain-mind continuum and the prospects of brain repair and neuroplasticity. Psychiatry is now regarded as a clinical neuroscience specialty of brain disorders that manifest as changes in thought, affect, mood, cognition, and behavior.
• Brain imaging. Techniques developed since the 1970s—the veritable alphabet soup of CT, PET, SPECT, MRI, MRS, fMRI, and DTI— has revolutionized understanding of brain structure and function in all psychiatric disorders but especially in psychotic and mood disorders.
• Molecular genetics. Advances over the past 2 decades have shed unprecedented light on the complex genetics of psychiatric disorders. It is becoming apparent that most psychiatric disorders are caused via gene-by-environment interaction; etiology is therefore a consequence of genetic and non-genetic variables. Risk genes, copy number variants, and de novo mutations are being discovered almost weekly, and progress in epigenetics holds promise for preventing medical disorders, including psychiatric illness.
• Neuromodulation. Advances represent an important paradigm shift, from pharmacotherapy to brain stimulation. Several techniques have been approved by the FDA, including transcranial magnetic stimulation, vagus nerve stimulation, and deep brain stimulation, to supplement, and perhaps eventually supplant, ECT.
Legal intrusiveness
No other medical specialty has been subject to laws governing clinical practice as psychiatry has been. Progressive intrusion of laws (ostensibly, enacted to protect the civil rights of “the disabled”) ends up hurting patients who refuse admission and then often harm themselves or others or decline urgent treatment, which can be associated with loss of brain tissue in acute psychotic, manic, and depressed states. No legal shackles apply to treating unconscious stroke patients, delirious geriatric patients, or semiconscious myocardial infarction patients when they are admitted to a hospital.
Distortions of the anti-psychiatry movement
The antipsychiatry movement preceded the Baby Boomer era by a century but has continued unabated. The movement gained momentum and became more defamatory after release of the movie One Flew Over the Cuckoo’s Nest in 1975, which portrayed psychiatry in a purely negative light. Despite progress in public understanding of psychiatry, and tangible improvements in practice, the stigma of mental illness persists. Media portrayals, including motion pictures, continue to distort the good that psychiatrists do for their patients.
Gender and sexuality
• Gender distribution of psychiatrists. A major shift occurred over the past 7 decades, reflecting the same pattern that has been documented in other medical specialties. At least one-half of psychiatry residents are now women—a welcome change from the pre-1946 era, when nearly all psychiatrists were men. This demographic transformation has had an impact on the dynamics of psychiatric practice.
• Acceptance and depathologization of homosexuality. Until 1974, homosexuality was considered a psychiatric disorder, and many homosexual persons sought treatment. That year, membership of the American Psychiatric Association voted to remove homosexuality from DSM-II and to no longer regard it as a behavioral abnormality. This was a huge step toward de-pathologizing same-sex orientation and love, and might have been the major impetus for the progressive social acceptance of gay, lesbian, and transgendered people over the past 4 decades.
The DSM paradigm shift in psychiatric diagnosis
• DSM-III. Perhaps the most radical change in the diagnostic criteria of psychiatric disorders occurred in 1980, with introduction of DSM-III to replace DSM-I and DSM-II, which were absurdly vague, unreliable, and with poor validity.
The move toward more operational and reliable diagnostic requirements began with the Research Diagnostic Criteria, developed by the Department of Psychiatry at Washington University in St. Louis. DSM-III represented a complete paradigm shift in psychiatric diagnosis. Subsequent editions maintained the same methodology, with relatively modest changes. The field expects continued evolution in DSM diagnostic criteria, including the future inclusion of biomarkers, based on sound, controlled studies.
• Recognizing PTSD. Develop-ment of posttraumatic stress disorder (PTSD) as a diagnostic entity, and its inclusion in DSM-III, were major changes in psychiatric nosology. At last, the old terms—shell shock, battle fatigue, neurasthenia—were legitimized as a recognizable syndrome secondary to major life trauma, including war and rape. That legitimacy has instigated substantial clinical and research interest in identifying how serious psychopathology can be triggered by life events.
Pharmaceutical industry debacle
Few industries have fallen so far from grace in the eyes of psychiatric professionals and the public as the manufacturers of psychotropic drugs.
At the dawn of the psychopharmacology era (the 1950s, 1960s, and 1970s) pharmaceutical companies were respected and regarded by physicians and patients as a vital partner in health care for their discovery and development of medications to treat psychiatric disorders. That image was tarnished in the 1990s, however, with the approval and release of several atypical antipsychotics. Cutthroat competition, questionable publication methods, concealment of negative findings, and excessive spending on marketing, including FDA-approved educational programs for clinicians on efficacy, safety, and dosing, all contributed to escalating cynicism about the industry. Academic faculty who received research grants to conduct FDA-required clinical trials of new agents were painted with the same brush.
Disclosure of potential conflict of interest became a mandatory procedure at universities and for NIMH grant applicants and journal publishers. Class-action lawsuits against companies that manufacture second-generation antipsychotics—filed for lack of transparency about metabolic side effects—exacerbated the intensity of criticism and condemnation.
Although new drug development has become measurably more rigorous and ethical because of self-regulation, combined with vigorous government scrutiny and regulation, demonization of the pharmaceutical industry remains unabated. That might be the reason why several major pharmaceutical companies have abandoned research and development of psychotropic drugs. That is likely to impede progress in psychopharmacotherapeutics; after all, no other private or government entity develops drugs for patients who have a psychiatric illness. The need for such agents is great: There is no FDA-indicated drug for the majority of DSM-5 diagnoses.
We entrust the future to next generations
Momentous events have transformed psychiatry during the lifespan of Baby Boomers like me and many of you. Because the cohort of 80 million Baby Boomers has comprised a significant percentage of the nation’s scientists, media representatives, members of the American Psychiatric Association, academicians, and community leaders over the past few decades, it is conceivable that the Baby Boomer generation helped trigger most of the transformative changes in psychiatry we have seen over the past 70 years.
I can only wonder: What direction will psychiatry take in the age of Generation X, Generation Y, and the Millennials? Only this is certain: Psychiatry will continue to evolve— long after Baby Boomers are gone.
Inhibitor shows promise for hematologic disorders
Photo courtesy of EHA
MILAN—The IDH2 inhibitor AG-221 is well-tolerated and exhibits durable clinical activity in patients with hematologic disorders, results of a phase 1 study suggest.
The drug prompted responses in patients with myelodysplastic syndromes (MDS), acute myeloid leukemia (AML), or chronic myelomonocytic leukemia (CMML).
Fourteen of 25 patients achieved a response, and 12 of those responses are ongoing.
Most adverse events (AEs) were grade 1 or 2 in nature. However, 4 patients did have serious AEs that were possibly related to treatment.
Stéphane de Botton, MD, PhD, of Institut Gustave Roussy in Villejuif, France, presented these results at the 19th Annual Congress of the European Hematology Association (EHA) as abstract LB2434.
Dr de Botton and his colleagues enrolled 35 patients who had a median age of 68 years (range, 48-81).
Twenty-seven patients had relapsed/refractory AML, 4 had relapsed/refractory MDS, 2 had untreated AML, 1 had CMML, and 1 had granulocytic sarcoma. Thirty-one patients had R140Q IDH2 mutations, and 4 had R172K IDH2 mutations.
The patients received AG-221 at 30 mg BID (n=7), 50 mg BID (n=7), 75 mg BID (n=6), 100 mg QD (n=5), 100 mg BID (n=5), or 150 mg QD (n=5). Patients completed a median of 1 cycle of treatment (range, <1-5+) and a mean of 2 cycles.
Safety data
“AG-221 was remarkable well-tolerated, and the [maximum tolerated dose] has not been reached,” Dr de Botton said. “The majority of adverse events were grade 1 and 2.”
Eighteen patients were evaluable for safety. AEs of all grades included nausea (n=4), pyrexia (n=4), thrombocytopenia (n=4), anemia (n=3), dizziness (n=3), febrile neutropenia (n=3), peripheral edema (n=3), sepsis (n=3), cough (n=2), diarrhea (n=2), fatigue (n=2), leukocytosis (n=2), neutropenia (n=2), petechiae (n=2), and rash (n=2).
Grade 3 or higher AEs included thrombocytopenia (n=3), anemia (n=1), febrile neutropenia (n=3), sepsis (n=3), diarrhea (n=1), fatigue (n=1), leukocytosis (n=2), neutropenia (n=1), and rash (n=1). Dr de Botton noted that diarrhea and rash were not expected events.
Four patients had serious AEs possibly related to treatment. One patient had grade 3 confusion and grade 5 respiratory failure. One patient had grade 3 leukocytosis, grade 3 anorexia, and grade 1 nausea. One patient had grade 3 diarrhea. And 1 patient had grade 3 leukocytosis.
Seven patients died within 30 days of study drug termination: 4 in the 30-mg cohort, 2 in the 50-mg cohort, and 1 in the 100-mg-BID cohort.
Five deaths were due to complications of disease-related sepsis (all in cycle 1), 1 complication of a humeral fracture, and 1 complication of a stroke.
Activity and response data
The researchers observed high AG-221 accumulation after multiple doses. And results were “really very similar” between the 30-mg-BID cohort and the 100-mg-QD cohort, Dr de Botton noted.
He also said AG-221 was “very efficient” at inhibiting 2-HG in the plasma. 2-HG was inhibited up to 100% in subjects with R140Q mutations and up to 60% in subjects with R172K mutations.
Twenty-five patients were evaluable for response. The remaining 10 patients did not have day-28 marrow assessments, either due to early termination (n=7) or receiving less than 28 days of treatment although they were still on the study (n=3).
In all, there were 6 complete responses (CRs), 2 CRs with incomplete platelet recovery (CRps), 1 CR with incomplete hematologic recovery (CRi), and 5 partial responses (PRs). Five patients had stable disease (SD), and 6 had progressive disease (PD).
The most responses occurred in the 50-mg group, which had 3 CRs, 1 CRi, and 1 PR. This was followed by the 30-mg group, which had 2 CRs, 1 CRp, and 1 PR.
“The majority of responses occurred in cycle 1,” Dr de Botton noted, “except in the first cohort [30 mg], where responses occurred late, at the end of cycle 3 and cycle 4.”
Twelve of the 14 responses are ongoing. Of the 8 patients who achieved a CR or CRp, 5 have lasted more than 2.5 months (range, 1-4+ months). And the 5 patients with SD remain on study.
This study is sponsored by Celgene Corporation and Agios Pharmaceuticals Inc., the companies developing AG-221. 
Photo courtesy of EHA
MILAN—The IDH2 inhibitor AG-221 is well-tolerated and exhibits durable clinical activity in patients with hematologic disorders, results of a phase 1 study suggest.
The drug prompted responses in patients with myelodysplastic syndromes (MDS), acute myeloid leukemia (AML), or chronic myelomonocytic leukemia (CMML).
Fourteen of 25 patients achieved a response, and 12 of those responses are ongoing.
Most adverse events (AEs) were grade 1 or 2 in nature. However, 4 patients did have serious AEs that were possibly related to treatment.
Stéphane de Botton, MD, PhD, of Institut Gustave Roussy in Villejuif, France, presented these results at the 19th Annual Congress of the European Hematology Association (EHA) as abstract LB2434.
Dr de Botton and his colleagues enrolled 35 patients who had a median age of 68 years (range, 48-81).
Twenty-seven patients had relapsed/refractory AML, 4 had relapsed/refractory MDS, 2 had untreated AML, 1 had CMML, and 1 had granulocytic sarcoma. Thirty-one patients had R140Q IDH2 mutations, and 4 had R172K IDH2 mutations.
The patients received AG-221 at 30 mg BID (n=7), 50 mg BID (n=7), 75 mg BID (n=6), 100 mg QD (n=5), 100 mg BID (n=5), or 150 mg QD (n=5). Patients completed a median of 1 cycle of treatment (range, <1-5+) and a mean of 2 cycles.
Safety data
“AG-221 was remarkable well-tolerated, and the [maximum tolerated dose] has not been reached,” Dr de Botton said. “The majority of adverse events were grade 1 and 2.”
Eighteen patients were evaluable for safety. AEs of all grades included nausea (n=4), pyrexia (n=4), thrombocytopenia (n=4), anemia (n=3), dizziness (n=3), febrile neutropenia (n=3), peripheral edema (n=3), sepsis (n=3), cough (n=2), diarrhea (n=2), fatigue (n=2), leukocytosis (n=2), neutropenia (n=2), petechiae (n=2), and rash (n=2).
Grade 3 or higher AEs included thrombocytopenia (n=3), anemia (n=1), febrile neutropenia (n=3), sepsis (n=3), diarrhea (n=1), fatigue (n=1), leukocytosis (n=2), neutropenia (n=1), and rash (n=1). Dr de Botton noted that diarrhea and rash were not expected events.
Four patients had serious AEs possibly related to treatment. One patient had grade 3 confusion and grade 5 respiratory failure. One patient had grade 3 leukocytosis, grade 3 anorexia, and grade 1 nausea. One patient had grade 3 diarrhea. And 1 patient had grade 3 leukocytosis.
Seven patients died within 30 days of study drug termination: 4 in the 30-mg cohort, 2 in the 50-mg cohort, and 1 in the 100-mg-BID cohort.
Five deaths were due to complications of disease-related sepsis (all in cycle 1), 1 complication of a humeral fracture, and 1 complication of a stroke.
Activity and response data
The researchers observed high AG-221 accumulation after multiple doses. And results were “really very similar” between the 30-mg-BID cohort and the 100-mg-QD cohort, Dr de Botton noted.
He also said AG-221 was “very efficient” at inhibiting 2-HG in the plasma. 2-HG was inhibited up to 100% in subjects with R140Q mutations and up to 60% in subjects with R172K mutations.
Twenty-five patients were evaluable for response. The remaining 10 patients did not have day-28 marrow assessments, either due to early termination (n=7) or receiving less than 28 days of treatment although they were still on the study (n=3).
In all, there were 6 complete responses (CRs), 2 CRs with incomplete platelet recovery (CRps), 1 CR with incomplete hematologic recovery (CRi), and 5 partial responses (PRs). Five patients had stable disease (SD), and 6 had progressive disease (PD).
The most responses occurred in the 50-mg group, which had 3 CRs, 1 CRi, and 1 PR. This was followed by the 30-mg group, which had 2 CRs, 1 CRp, and 1 PR.
“The majority of responses occurred in cycle 1,” Dr de Botton noted, “except in the first cohort [30 mg], where responses occurred late, at the end of cycle 3 and cycle 4.”
Twelve of the 14 responses are ongoing. Of the 8 patients who achieved a CR or CRp, 5 have lasted more than 2.5 months (range, 1-4+ months). And the 5 patients with SD remain on study.
This study is sponsored by Celgene Corporation and Agios Pharmaceuticals Inc., the companies developing AG-221.
Photo courtesy of EHA
MILAN—The IDH2 inhibitor AG-221 is well-tolerated and exhibits durable clinical activity in patients with hematologic disorders, results of a phase 1 study suggest.
The drug prompted responses in patients with myelodysplastic syndromes (MDS), acute myeloid leukemia (AML), or chronic myelomonocytic leukemia (CMML).
Fourteen of 25 patients achieved a response, and 12 of those responses are ongoing.
Most adverse events (AEs) were grade 1 or 2 in nature. However, 4 patients did have serious AEs that were possibly related to treatment.
Stéphane de Botton, MD, PhD, of Institut Gustave Roussy in Villejuif, France, presented these results at the 19th Annual Congress of the European Hematology Association (EHA) as abstract LB2434.
Dr de Botton and his colleagues enrolled 35 patients who had a median age of 68 years (range, 48-81).
Twenty-seven patients had relapsed/refractory AML, 4 had relapsed/refractory MDS, 2 had untreated AML, 1 had CMML, and 1 had granulocytic sarcoma. Thirty-one patients had R140Q IDH2 mutations, and 4 had R172K IDH2 mutations.
The patients received AG-221 at 30 mg BID (n=7), 50 mg BID (n=7), 75 mg BID (n=6), 100 mg QD (n=5), 100 mg BID (n=5), or 150 mg QD (n=5). Patients completed a median of 1 cycle of treatment (range, <1-5+) and a mean of 2 cycles.
Safety data
“AG-221 was remarkable well-tolerated, and the [maximum tolerated dose] has not been reached,” Dr de Botton said. “The majority of adverse events were grade 1 and 2.”
Eighteen patients were evaluable for safety. AEs of all grades included nausea (n=4), pyrexia (n=4), thrombocytopenia (n=4), anemia (n=3), dizziness (n=3), febrile neutropenia (n=3), peripheral edema (n=3), sepsis (n=3), cough (n=2), diarrhea (n=2), fatigue (n=2), leukocytosis (n=2), neutropenia (n=2), petechiae (n=2), and rash (n=2).
Grade 3 or higher AEs included thrombocytopenia (n=3), anemia (n=1), febrile neutropenia (n=3), sepsis (n=3), diarrhea (n=1), fatigue (n=1), leukocytosis (n=2), neutropenia (n=1), and rash (n=1). Dr de Botton noted that diarrhea and rash were not expected events.
Four patients had serious AEs possibly related to treatment. One patient had grade 3 confusion and grade 5 respiratory failure. One patient had grade 3 leukocytosis, grade 3 anorexia, and grade 1 nausea. One patient had grade 3 diarrhea. And 1 patient had grade 3 leukocytosis.
Seven patients died within 30 days of study drug termination: 4 in the 30-mg cohort, 2 in the 50-mg cohort, and 1 in the 100-mg-BID cohort.
Five deaths were due to complications of disease-related sepsis (all in cycle 1), 1 complication of a humeral fracture, and 1 complication of a stroke.
Activity and response data
The researchers observed high AG-221 accumulation after multiple doses. And results were “really very similar” between the 30-mg-BID cohort and the 100-mg-QD cohort, Dr de Botton noted.
He also said AG-221 was “very efficient” at inhibiting 2-HG in the plasma. 2-HG was inhibited up to 100% in subjects with R140Q mutations and up to 60% in subjects with R172K mutations.
Twenty-five patients were evaluable for response. The remaining 10 patients did not have day-28 marrow assessments, either due to early termination (n=7) or receiving less than 28 days of treatment although they were still on the study (n=3).
In all, there were 6 complete responses (CRs), 2 CRs with incomplete platelet recovery (CRps), 1 CR with incomplete hematologic recovery (CRi), and 5 partial responses (PRs). Five patients had stable disease (SD), and 6 had progressive disease (PD).
The most responses occurred in the 50-mg group, which had 3 CRs, 1 CRi, and 1 PR. This was followed by the 30-mg group, which had 2 CRs, 1 CRp, and 1 PR.
“The majority of responses occurred in cycle 1,” Dr de Botton noted, “except in the first cohort [30 mg], where responses occurred late, at the end of cycle 3 and cycle 4.”
Twelve of the 14 responses are ongoing. Of the 8 patients who achieved a CR or CRp, 5 have lasted more than 2.5 months (range, 1-4+ months). And the 5 patients with SD remain on study.
This study is sponsored by Celgene Corporation and Agios Pharmaceuticals Inc., the companies developing AG-221.
Engineered protein targets EBV lymphoma
Credit: Ed Uthman
Preclinical research suggests a newly engineered protein can suppress tumor growth and extend survival in a mouse model of lymphoma.
The molecule, called BINDI (BHRF1-inhibiting design acting intracellularly), was designed to trigger the self-destruction of cancer cells infected with the Epstein-Barr virus (EBV).
EBV can disrupt the body’s clearance of old, abnormal, infected, and damaged cells. And BINDI works by overriding this interference.
Erik Procko, PhD, of the University of Washington in Seattle, and his colleagues described results observed with BINDI in Cell.
The researchers used computational design and experimental optimization to generate BINDI. The protein was designed to recognize and attach itself to an EBV protein called BHRF1 and to ignore similar proteins. BHRF1 keeps cancer cells alive, but, when bound to BINDI, it can no longer fend off cell death.
By examining the crystal structure of BINDI, the researchers saw that it nearly matched their computationally designed architecture for the protein molecule.
Furthermore, experiments showed that BINDI could prompt EBV-infected cancer cell lines to shrivel, disassemble their components, and burst into small pieces.
The researchers also tested BINDI in a mouse model of EBV-positive lymphoma. They delivered BINDI into cancer cells via an antibody-targeted nanocarrier designed to deliver protein cargo to intracellular cancer targets.
And BINDI behaved as ordered. It suppressed tumor growth and enabled the mice to live longer than control mice.
The researchers said this work demonstrates the potential to develop new classes of more effective, intracellular protein drugs, as current protein therapeutics are limited to extracellular targets. 
Credit: Ed Uthman
Preclinical research suggests a newly engineered protein can suppress tumor growth and extend survival in a mouse model of lymphoma.
The molecule, called BINDI (BHRF1-inhibiting design acting intracellularly), was designed to trigger the self-destruction of cancer cells infected with the Epstein-Barr virus (EBV).
EBV can disrupt the body’s clearance of old, abnormal, infected, and damaged cells. And BINDI works by overriding this interference.
Erik Procko, PhD, of the University of Washington in Seattle, and his colleagues described results observed with BINDI in Cell.
The researchers used computational design and experimental optimization to generate BINDI. The protein was designed to recognize and attach itself to an EBV protein called BHRF1 and to ignore similar proteins. BHRF1 keeps cancer cells alive, but, when bound to BINDI, it can no longer fend off cell death.
By examining the crystal structure of BINDI, the researchers saw that it nearly matched their computationally designed architecture for the protein molecule.
Furthermore, experiments showed that BINDI could prompt EBV-infected cancer cell lines to shrivel, disassemble their components, and burst into small pieces.
The researchers also tested BINDI in a mouse model of EBV-positive lymphoma. They delivered BINDI into cancer cells via an antibody-targeted nanocarrier designed to deliver protein cargo to intracellular cancer targets.
And BINDI behaved as ordered. It suppressed tumor growth and enabled the mice to live longer than control mice.
The researchers said this work demonstrates the potential to develop new classes of more effective, intracellular protein drugs, as current protein therapeutics are limited to extracellular targets.
Credit: Ed Uthman
Preclinical research suggests a newly engineered protein can suppress tumor growth and extend survival in a mouse model of lymphoma.
The molecule, called BINDI (BHRF1-inhibiting design acting intracellularly), was designed to trigger the self-destruction of cancer cells infected with the Epstein-Barr virus (EBV).
EBV can disrupt the body’s clearance of old, abnormal, infected, and damaged cells. And BINDI works by overriding this interference.
Erik Procko, PhD, of the University of Washington in Seattle, and his colleagues described results observed with BINDI in Cell.
The researchers used computational design and experimental optimization to generate BINDI. The protein was designed to recognize and attach itself to an EBV protein called BHRF1 and to ignore similar proteins. BHRF1 keeps cancer cells alive, but, when bound to BINDI, it can no longer fend off cell death.
By examining the crystal structure of BINDI, the researchers saw that it nearly matched their computationally designed architecture for the protein molecule.
Furthermore, experiments showed that BINDI could prompt EBV-infected cancer cell lines to shrivel, disassemble their components, and burst into small pieces.
The researchers also tested BINDI in a mouse model of EBV-positive lymphoma. They delivered BINDI into cancer cells via an antibody-targeted nanocarrier designed to deliver protein cargo to intracellular cancer targets.
And BINDI behaved as ordered. It suppressed tumor growth and enabled the mice to live longer than control mice.
The researchers said this work demonstrates the potential to develop new classes of more effective, intracellular protein drugs, as current protein therapeutics are limited to extracellular targets.