Valerie G. Press, MD, MPH

Health literacy (HL), defined as patients’ ability to understand health information and make health decisions,¹ is a prevalent problem in the outpatient and inpatient settings.^2,3 In both settings, low HL has adverse implications for self-care including interpreting health labels⁴ and taking medications correctly.⁵ Among outpatient cohorts, HL has been associated with worse outcomes and acute care utilization.⁶ Associations with low HL include increased hospitalizations,⁷ rehospitalizations,^8,9 emergency department visits,¹⁰ and decreased preventative care use.¹¹ Among the elderly, low HL is associated with increased mortality¹² and decreased self-perception of health.¹³

A systematic review revealed that most high-quality HL outcome studies were conducted in the outpatient setting.⁶ There have been very few studies assessing effects of low HL in an acute-care setting.^7,14 These studies have evaluated postdischarge outcomes, including admissions or readmissions,^7-9 and medication knowledge.¹⁴ To the best of our knowledge, there are no studies evaluating associations between HL and hospital length of stay (LOS).

LOS has received much attention as providers and payers focus more on resource utilization and eliminating adverse effects of prolonged hospitalization.¹⁵ LOS is multifactorial, depending on clinical characteristics like disease severity, as well as on sociocultural, demographic, and geographic factors.¹⁶ Despite evidence that LOS reductions translate into improved resource allocation and potentially fewer complications, there remains a tension between the appropriate LOS and one that is too short for a given condition.¹⁷

Because low HL is associated with inefficient resource utilization, we hypothesized that low HL would be associated with increased LOS after controlling for illness severity. Our objectives were to evaluate the association between low HL and LOS and whether such an association was modified by illness severity and sociodemographics.

METHODS

Study Design, Setting, Participants

An in-hospital, cohort study design of patients who were admitted or transferred to the general medicine service at the University of Chicago between October 2012 and November 2015 and screened for inclusion as part of a large, ongoing study of inpatient care quality was conducted.¹⁸ Exclusion criteria included observation status, age under 18 years, non-English speaking, and repeat participants. Those who died during hospitalization or whose discharge status was missing were excluded because the primary goal was to examine the association of HL and time to discharge, which could not be evaluated among those who died. We excluded participants with LOS >30 days to limit overly influential effects of extreme outliers (1% of the population).

Variables

HL was screened using the Brief Health Literacy Screen (BHLS), a validated, 3-question verbal survey not requiring adequate visual acuity to assess HL.^19,20 The 3 questions are as follows: (1) “How confident are you filling out medical forms by yourself?”, (2) “How often do you have someone help you read hospital materials?”, and (3) “How often do you have problems learning about your medical condition because of difficulty understanding written information?” Responses to the questions were scored on a 5-point Likert scale in which higher scores corresponded to higher HL.^21,22 The scores for each of the 3 questions were summed to yield a range between 3 and 15. On the individual questions, prior work has demonstrated improved test performance with a cutoff of ≤3, which corresponds to a response of “some of the time” or “somewhat”; therefore, when the 3 questions were summed together, scores of ≤9 were considered indicative of low HL.^21,23

For severity of illness adjustment, we used relative weights derived from the 3M (3M, Maplewood, MN) All Patient Refined Diagnosis Related Groups (APR-DRG) classification system, which uses administrative data to classify the severity. The APR-DRG system assigns each admission to a DRG based on principal diagnosis; for each DRG, patients are then subdivided into 4 severity classes based on age, comorbidity, and interactions between these variables and the admitting diagnosis.²⁴ Using the base DRG and severity score, the system assigns relative weights that reflect differences in expected hospital resource utilization.

LOS was derived from hospital administrative data and counted from the date of admission to the hospital. Participants who were discharged on the day of admission were counted as having an LOS of 1. Insurance status (Medicare, Medicaid, no payer, private) also was obtained from administrative data. Age, sex (male or female), education (junior high or less, some high school, high school graduate, some college, college graduate, postgraduate), and race (black/African American, white, Asian or Pacific Islander [including Asian Indian, Chinese, Filipino, Japanese, Korean, Vietnamese, other Asian, Native Hawaiian, Guam/Chamorro, Samoan, other Pacific], American Indian or Alaskan Native, multiple race) were obtained from administrative data based on information provided by the patient. Participants with missing data on any of the sociodemographic variables or on the APR-DRG score were excluded from the analysis.

 

Statistical Analysis

χ² and 2-tailed t tests were used to compare categorical and continuous variables, respectively. Multivariate linear regressions were employed to measure associations between the independent variables (HL, illness severity, race, gender, education, and insurance status) and the dependent variable, LOS. Independent variables were chosen for clinical significance and retained in the model regardless of statistical significance. The adjusted R² values of models with and without the HL variable included were reported to provide information on the contribution of HL to the overall model.

Because LOS was observed to be right skewed and residuals of the untransformed regression were observed to be non-normally distributed, the decision was made to natural log transform LOS, which is consistent with previous hospital LOS studies.¹⁶ Regression coefficients and confidence intervals were then transformed into percentage estimates using the following equation: 100(e^β–1). Adjusted R² was reported for the transformed regression.

The APR-DRG relative weight was treated as a continuous variable. Sociodemographic variables were dichotomized as follows: female vs male; high school graduates vs not; African American vs not; Medicaid/no payer vs Medicare/private payer. Age was not included in the multivariate model because it has been incorporated into the weighted APR-DRG illness severity scores.

Each of the sociodemographic variables and the APR-DRG score were examined for effect modification via the same multivariate linear equation described above, with the addition of an interaction term. A separate regression was performed with an interaction term between age (dichotomized at ≥65) and HL to investigate whether age modified the association between HL and LOS. Finally, we explored whether effects were isolated to long vs short LOS by dividing the sample based on the mean LOS (≥6 days) and performing separate multivariate comparisons.

Sensitivity analyses were performed to exclude those with LOS greater than the 90th percentile and those with APR-DRG score greater than the 90th percentile; age was added to the model as a continuous variable to evaluate whether the illness severity score fully adjusted for the effects of age on LOS. Furthermore, we compared the participants with missing data to those with complete data across both dependent and independent variables. Alpha was set at 0.05; analyses were performed using Stata Version 14 (Stata, College Station, TX).

RESULTS

A total of 5983 participants met inclusion criteria and completed the HL assessment; of these participants, 75 (1%) died during hospitalization, 9 (0.2%) had missing discharge status, and 79 (1%) had LOS >30 days. Two hundred eighty (5%) were missing data on sociodemographic variables or APR-DRG score. Of the remaining (n = 5540), the mean age was 57 years (standard deviation [SD] = 19 years), over half of participants were female (57%), and the majority were African American (73%) and had graduated from high school (81%). The sample was divided into those with private insurance (25%), those with Medicare (46%), and those with Medicaid (26%); 2% had no payer. The mean APR-DRG score was 1.3 (SD = 1.2), and the scores ranged from 0.3 to 15.8.

On the BHLS screen for HL, 20% (1104/5540) had inadequate HL. Participants with low HL had higher weighted illness severity scores (average 1.4 vs 1.3; P = 0.003). Participants with low HL were also more likely to be 65 or older (55% vs 33%; P < 0.001), non-high school graduates (35% vs 15%; P < 0.001), and African American (78% vs 72%; P < 0.001), and to have Medicare or private insurance (75% vs 71%; P = 0.02). There was no significant difference with respect to gender (54% male vs 57% female; P = 0.1)

The mean and median LOS were 6 ± 5 days and 4 days (interquartile range 2-7 days), respectively. Those with low HL had a longer average LOS (6.0 vs 5.4 days; P < 0.001). In multivariate analysis controlling for APR-DRG score, gender, education, race, and insurance status, low HL was associated with an 11.1% longer LOS (95% CI, 6.1-16.1; P < 0.001; Table 1). The adjusted R² value for the regression was 25.0% including HL and 24.7% with HL excluded. Additionally, being African American (P < 0.001) and having Medicaid or no insurance (P < 0.001) were associated with a shorter LOS in multivariate analysis (Table 1). The association of HL and LOS in multivariate modeling remained significant among participants with LOS <6 days (10.2%; 95% CI, 5.6%-14.9%; P < 0.001), but not among participants with LOS ≥6 days (0.4%; 95% CI, −3.6% to 4.4%; P = 0.8).

Neither age ≥65 (P = 0.4) nor illness severity score (P = 0.5) significantly modified the effect of HL on LOS. However, the effect of HL on hospital LOS was significantly modified by gender (P = 0.02). Among men, low HL was associated with a 17.8% longer LOS (95% CI, 10.0%-25.7%; P < 0.001), but among women, low HL was associated with only a 7.7% longer LOS (95% CI, 1.9%-13.5%; P = 0.009). Among the remaining demographics, high school graduation status (P = 0.4), being African American (P = 0.6), and insurance status (P = 0.2) did not significantly modify the effect of HL on LOS. In sensitivity analysis, excluding participants with LOS above the 90th percentile of 12 days and excluding participants with illness severity scores above the 90th percentile, low HL was still associated with longer LOS (P < 0.001 and P = 0.001, respectively; Table 2). In the final sensitivity analysis, although age remained a significant predictor of longer LOS after controlling for illness severity (0.2% increase per year, 95% CI, 0.1%-0.3%; P < 0.001), low HL nevertheless remained significantly associated with longer LOS (P < 0.001; Table 2).

Finally, we compared the group with missing data (n = 280) to the group with complete data (n = 5540). The participants with missing data were more likely to have low HL (31% [86/280] vs 20%; P < 0.001) and to have Medicare or private insurance (82% [177/217] vs 72%; P = 0.002); however, they were not more likely to be 65 or older (40% [112/280] vs 37%; P = 0.3), high school graduates (88% [113/129] vs 81%; P = 0.06), African American (69% [177/256] vs 73%; P = 0.1), or female (57% [158/279] vs 57%; P = 1), nor were they more likely to have longer LOS (5.7 [n = 280] vs 5.5 days; P = 0.6) or higher illness severity scores (1.3 [n = 231] vs 1.3; P = 0.7).

 

DISCUSSION

To our knowledge, this study is the first to evaluate the association between low HL and an important in-hospital outcome measure, hospital LOS. We found that low HL was associated with a longer hospital LOS, a result which remained significant when controlling for severity of illness and sociodemographic variables and when testing the model for sensitivity to the highest values of LOS and illness severity. Additionally, the association of HL with LOS appeared concentrated among participants with shorter LOS. Relative to other predictors, the contribution of HL to the overall LOS model was small, as evidenced by the change in adjusted R² values with HL excluded.

Among the covariates, only gender modified the association between HL and LOS; the findings suggested that men were more susceptible to the effect of low HL on increased LOS. Illness severity and other sociodemographics, including age ≥65, did not appear to modify the association. We also found that being African American and having Medicaid or no insurance were associated with a significantly shorter LOS in multivariate analysis.

Previous work suggested that the adverse health effects of low HL may be mediated through several pathways, including health knowledge, self-efficacy, health skills, and illness stigma.^25-27 The finding of a small but significant relationship between HL and LOS was not surprising given these known associations; nevertheless, there may be an additional patient-dependent effect of low HL on LOS not discovered here. For instance, patients with poor health knowledge and self-efficacy might stay in the hospital longer if they or their providers do not feel comfortable with their self-care ability.

This finding may be useful in developing hospital-based interventions. HL-specific interventions, several of which have been tested in the inpatient setting,^14,28,29 have shown promise toward improving health knowledge,³⁰ disease severity,³¹ and health resource utilization.³²

Those with low HL may lack the self-efficacy to participate in discharge planning; in fact, previous work has related low HL to posthospital readmissions.^8,9 Conversely, patients with low HL might struggle to engage in the inpatient milieu, advocating for shorter LOS if they feel alienated by the inpatient experience.

These possibilities show that LOS is a complex measure shown to depend on patient-level characteristics and on provider-based, geographical, and sociocultural factors.^16,33 With these forces at play, additional effects of lower levels of HL may be lost without phenotyping patients by both level of HL and related characteristics, such as self-efficacy, health skills, and stigma. By gathering these additional data, future work should explore whether subpopulations of patients with low HL may be at risk for too-short vs too-long hospital admissions.

For instance, in this study, both race and Medicaid insurance were associated with shorter LOS. Being African American was associated with shorter LOS in our study but has been found to be associated with longer LOS in another study specifically focused on diabetes.³⁴ Prior findings found uninsured patients have shorter LOS.³⁵ Therefore, these findings in our study are difficult to explain without further work to understand whether there are health disparities in the way patients are cared for during hospitalization that may shorten or lengthen their LOS because of factors outside of their clinical need.

The finding that gender modified the effect of low HL on LOS was unexpected. There were similar proportions of men and women with low HL. There is evidence to support that women make the majority of health decisions for themselves and their familes³⁶; therefore, there may be unmeasured aspects of HL that provide an advantage for female vs male inpatients. Furthermore, omitted confounders, such as social support, may not fully capture potential gender-related differences. Future work is needed to understand the role of gender in relationship to HL and LOS.

Limitations of this study include its observational, single-centered design with information derived from administrative data; positive and negative confounding cannot be ruled out. For instance, we did not control for complex aspects affecting LOS, such as discharge disposition and goals of care (eg, aggressive care after discharge vs hospice). To address this limitation, multivariate analyses were performed, which were adjusted for illness severity scores and took into account both comorbidity and severity of the current illness. Additionally, although it is important to study such populations, our largely urban, minority sample is not representative of the U.S. population, and within our large sample, there were participants with missing data who had lower HL on average, although this group represented only 5% of the sample. Finally, different HL tools have noncomplete concordance, which has been seen when comparing the BHLS with more objective tools.^20,37 Furthermore, certain in-hospital clinical scenarios (eg, recent stroke or prolonged intensive care unit stay) may present unique challenges in establishing a baseline HL level. However, the BHLS was used in this study because of its greater feasibility.

In conclusion, this study is the first to evaluate the relationship between low HL and LOS. The findings suggest that HL may play a role in shaping outcomes in the inpatient setting and that targeting interventions toward screened patients may be a pathway toward mitigating adverse effects. Our findings need to be replicated in larger, more representative samples, and further work understanding subpopulations within the low HL population is needed. Future work should measure this association in diverse inpatient settings (eg, psychiatric, surgical, and specialty), in addition to assessing associations between HL and other important in-hospital outcome measures, including mortality and discharge disposition.

 

Acknowledgments

The authors thank the Hospitalist Project team for their assistance with data collection. The authors especially thank Chuanhong Liao and Ashley Snyder for assistance with statistical analyses; Andrea Flores, Ainoa Coltri, and Tom Best for their assistance with data management. The authors would also like to thank Nicole Twu for her help with preparing and editing the manuscript.

Disclosures

Dr. Jaffee was supported by a Calvin Fentress Research Fellowship and NIH R25MH094612. Dr. Press was supported by a career development award (NHLBI K23HL118151). This work was also supported by a seed grant from the Center for Health Administration Studies. All other authors declare no conflicts of interest.

Health literacy (HL), defined as patients’ ability to understand health information and make health decisions,¹ is a prevalent problem in the outpatient and inpatient settings.^2,3 In both settings, low HL has adverse implications for self-care including interpreting health labels⁴ and taking medications correctly.⁵ Among outpatient cohorts, HL has been associated with worse outcomes and acute care utilization.⁶ Associations with low HL include increased hospitalizations,⁷ rehospitalizations,^8,9 emergency department visits,¹⁰ and decreased preventative care use.¹¹ Among the elderly, low HL is associated with increased mortality¹² and decreased self-perception of health.¹³

A systematic review revealed that most high-quality HL outcome studies were conducted in the outpatient setting.⁶ There have been very few studies assessing effects of low HL in an acute-care setting.^7,14 These studies have evaluated postdischarge outcomes, including admissions or readmissions,^7-9 and medication knowledge.¹⁴ To the best of our knowledge, there are no studies evaluating associations between HL and hospital length of stay (LOS).

LOS has received much attention as providers and payers focus more on resource utilization and eliminating adverse effects of prolonged hospitalization.¹⁵ LOS is multifactorial, depending on clinical characteristics like disease severity, as well as on sociocultural, demographic, and geographic factors.¹⁶ Despite evidence that LOS reductions translate into improved resource allocation and potentially fewer complications, there remains a tension between the appropriate LOS and one that is too short for a given condition.¹⁷

Because low HL is associated with inefficient resource utilization, we hypothesized that low HL would be associated with increased LOS after controlling for illness severity. Our objectives were to evaluate the association between low HL and LOS and whether such an association was modified by illness severity and sociodemographics.

METHODS

Study Design, Setting, Participants

An in-hospital, cohort study design of patients who were admitted or transferred to the general medicine service at the University of Chicago between October 2012 and November 2015 and screened for inclusion as part of a large, ongoing study of inpatient care quality was conducted.¹⁸ Exclusion criteria included observation status, age under 18 years, non-English speaking, and repeat participants. Those who died during hospitalization or whose discharge status was missing were excluded because the primary goal was to examine the association of HL and time to discharge, which could not be evaluated among those who died. We excluded participants with LOS >30 days to limit overly influential effects of extreme outliers (1% of the population).

Variables

HL was screened using the Brief Health Literacy Screen (BHLS), a validated, 3-question verbal survey not requiring adequate visual acuity to assess HL.^19,20 The 3 questions are as follows: (1) “How confident are you filling out medical forms by yourself?”, (2) “How often do you have someone help you read hospital materials?”, and (3) “How often do you have problems learning about your medical condition because of difficulty understanding written information?” Responses to the questions were scored on a 5-point Likert scale in which higher scores corresponded to higher HL.^21,22 The scores for each of the 3 questions were summed to yield a range between 3 and 15. On the individual questions, prior work has demonstrated improved test performance with a cutoff of ≤3, which corresponds to a response of “some of the time” or “somewhat”; therefore, when the 3 questions were summed together, scores of ≤9 were considered indicative of low HL.^21,23

For severity of illness adjustment, we used relative weights derived from the 3M (3M, Maplewood, MN) All Patient Refined Diagnosis Related Groups (APR-DRG) classification system, which uses administrative data to classify the severity. The APR-DRG system assigns each admission to a DRG based on principal diagnosis; for each DRG, patients are then subdivided into 4 severity classes based on age, comorbidity, and interactions between these variables and the admitting diagnosis.²⁴ Using the base DRG and severity score, the system assigns relative weights that reflect differences in expected hospital resource utilization.

LOS was derived from hospital administrative data and counted from the date of admission to the hospital. Participants who were discharged on the day of admission were counted as having an LOS of 1. Insurance status (Medicare, Medicaid, no payer, private) also was obtained from administrative data. Age, sex (male or female), education (junior high or less, some high school, high school graduate, some college, college graduate, postgraduate), and race (black/African American, white, Asian or Pacific Islander [including Asian Indian, Chinese, Filipino, Japanese, Korean, Vietnamese, other Asian, Native Hawaiian, Guam/Chamorro, Samoan, other Pacific], American Indian or Alaskan Native, multiple race) were obtained from administrative data based on information provided by the patient. Participants with missing data on any of the sociodemographic variables or on the APR-DRG score were excluded from the analysis.

 

Statistical Analysis

χ² and 2-tailed t tests were used to compare categorical and continuous variables, respectively. Multivariate linear regressions were employed to measure associations between the independent variables (HL, illness severity, race, gender, education, and insurance status) and the dependent variable, LOS. Independent variables were chosen for clinical significance and retained in the model regardless of statistical significance. The adjusted R² values of models with and without the HL variable included were reported to provide information on the contribution of HL to the overall model.

Because LOS was observed to be right skewed and residuals of the untransformed regression were observed to be non-normally distributed, the decision was made to natural log transform LOS, which is consistent with previous hospital LOS studies.¹⁶ Regression coefficients and confidence intervals were then transformed into percentage estimates using the following equation: 100(e^β–1). Adjusted R² was reported for the transformed regression.

The APR-DRG relative weight was treated as a continuous variable. Sociodemographic variables were dichotomized as follows: female vs male; high school graduates vs not; African American vs not; Medicaid/no payer vs Medicare/private payer. Age was not included in the multivariate model because it has been incorporated into the weighted APR-DRG illness severity scores.

Each of the sociodemographic variables and the APR-DRG score were examined for effect modification via the same multivariate linear equation described above, with the addition of an interaction term. A separate regression was performed with an interaction term between age (dichotomized at ≥65) and HL to investigate whether age modified the association between HL and LOS. Finally, we explored whether effects were isolated to long vs short LOS by dividing the sample based on the mean LOS (≥6 days) and performing separate multivariate comparisons.

Sensitivity analyses were performed to exclude those with LOS greater than the 90th percentile and those with APR-DRG score greater than the 90th percentile; age was added to the model as a continuous variable to evaluate whether the illness severity score fully adjusted for the effects of age on LOS. Furthermore, we compared the participants with missing data to those with complete data across both dependent and independent variables. Alpha was set at 0.05; analyses were performed using Stata Version 14 (Stata, College Station, TX).

RESULTS

A total of 5983 participants met inclusion criteria and completed the HL assessment; of these participants, 75 (1%) died during hospitalization, 9 (0.2%) had missing discharge status, and 79 (1%) had LOS >30 days. Two hundred eighty (5%) were missing data on sociodemographic variables or APR-DRG score. Of the remaining (n = 5540), the mean age was 57 years (standard deviation [SD] = 19 years), over half of participants were female (57%), and the majority were African American (73%) and had graduated from high school (81%). The sample was divided into those with private insurance (25%), those with Medicare (46%), and those with Medicaid (26%); 2% had no payer. The mean APR-DRG score was 1.3 (SD = 1.2), and the scores ranged from 0.3 to 15.8.

On the BHLS screen for HL, 20% (1104/5540) had inadequate HL. Participants with low HL had higher weighted illness severity scores (average 1.4 vs 1.3; P = 0.003). Participants with low HL were also more likely to be 65 or older (55% vs 33%; P < 0.001), non-high school graduates (35% vs 15%; P < 0.001), and African American (78% vs 72%; P < 0.001), and to have Medicare or private insurance (75% vs 71%; P = 0.02). There was no significant difference with respect to gender (54% male vs 57% female; P = 0.1)

The mean and median LOS were 6 ± 5 days and 4 days (interquartile range 2-7 days), respectively. Those with low HL had a longer average LOS (6.0 vs 5.4 days; P < 0.001). In multivariate analysis controlling for APR-DRG score, gender, education, race, and insurance status, low HL was associated with an 11.1% longer LOS (95% CI, 6.1-16.1; P < 0.001; Table 1). The adjusted R² value for the regression was 25.0% including HL and 24.7% with HL excluded. Additionally, being African American (P < 0.001) and having Medicaid or no insurance (P < 0.001) were associated with a shorter LOS in multivariate analysis (Table 1). The association of HL and LOS in multivariate modeling remained significant among participants with LOS <6 days (10.2%; 95% CI, 5.6%-14.9%; P < 0.001), but not among participants with LOS ≥6 days (0.4%; 95% CI, −3.6% to 4.4%; P = 0.8).

Neither age ≥65 (P = 0.4) nor illness severity score (P = 0.5) significantly modified the effect of HL on LOS. However, the effect of HL on hospital LOS was significantly modified by gender (P = 0.02). Among men, low HL was associated with a 17.8% longer LOS (95% CI, 10.0%-25.7%; P < 0.001), but among women, low HL was associated with only a 7.7% longer LOS (95% CI, 1.9%-13.5%; P = 0.009). Among the remaining demographics, high school graduation status (P = 0.4), being African American (P = 0.6), and insurance status (P = 0.2) did not significantly modify the effect of HL on LOS. In sensitivity analysis, excluding participants with LOS above the 90th percentile of 12 days and excluding participants with illness severity scores above the 90th percentile, low HL was still associated with longer LOS (P < 0.001 and P = 0.001, respectively; Table 2). In the final sensitivity analysis, although age remained a significant predictor of longer LOS after controlling for illness severity (0.2% increase per year, 95% CI, 0.1%-0.3%; P < 0.001), low HL nevertheless remained significantly associated with longer LOS (P < 0.001; Table 2).

Finally, we compared the group with missing data (n = 280) to the group with complete data (n = 5540). The participants with missing data were more likely to have low HL (31% [86/280] vs 20%; P < 0.001) and to have Medicare or private insurance (82% [177/217] vs 72%; P = 0.002); however, they were not more likely to be 65 or older (40% [112/280] vs 37%; P = 0.3), high school graduates (88% [113/129] vs 81%; P = 0.06), African American (69% [177/256] vs 73%; P = 0.1), or female (57% [158/279] vs 57%; P = 1), nor were they more likely to have longer LOS (5.7 [n = 280] vs 5.5 days; P = 0.6) or higher illness severity scores (1.3 [n = 231] vs 1.3; P = 0.7).

 

DISCUSSION

To our knowledge, this study is the first to evaluate the association between low HL and an important in-hospital outcome measure, hospital LOS. We found that low HL was associated with a longer hospital LOS, a result which remained significant when controlling for severity of illness and sociodemographic variables and when testing the model for sensitivity to the highest values of LOS and illness severity. Additionally, the association of HL with LOS appeared concentrated among participants with shorter LOS. Relative to other predictors, the contribution of HL to the overall LOS model was small, as evidenced by the change in adjusted R² values with HL excluded.

Among the covariates, only gender modified the association between HL and LOS; the findings suggested that men were more susceptible to the effect of low HL on increased LOS. Illness severity and other sociodemographics, including age ≥65, did not appear to modify the association. We also found that being African American and having Medicaid or no insurance were associated with a significantly shorter LOS in multivariate analysis.

Previous work suggested that the adverse health effects of low HL may be mediated through several pathways, including health knowledge, self-efficacy, health skills, and illness stigma.^25-27 The finding of a small but significant relationship between HL and LOS was not surprising given these known associations; nevertheless, there may be an additional patient-dependent effect of low HL on LOS not discovered here. For instance, patients with poor health knowledge and self-efficacy might stay in the hospital longer if they or their providers do not feel comfortable with their self-care ability.

This finding may be useful in developing hospital-based interventions. HL-specific interventions, several of which have been tested in the inpatient setting,^14,28,29 have shown promise toward improving health knowledge,³⁰ disease severity,³¹ and health resource utilization.³²

Those with low HL may lack the self-efficacy to participate in discharge planning; in fact, previous work has related low HL to posthospital readmissions.^8,9 Conversely, patients with low HL might struggle to engage in the inpatient milieu, advocating for shorter LOS if they feel alienated by the inpatient experience.

These possibilities show that LOS is a complex measure shown to depend on patient-level characteristics and on provider-based, geographical, and sociocultural factors.^16,33 With these forces at play, additional effects of lower levels of HL may be lost without phenotyping patients by both level of HL and related characteristics, such as self-efficacy, health skills, and stigma. By gathering these additional data, future work should explore whether subpopulations of patients with low HL may be at risk for too-short vs too-long hospital admissions.

For instance, in this study, both race and Medicaid insurance were associated with shorter LOS. Being African American was associated with shorter LOS in our study but has been found to be associated with longer LOS in another study specifically focused on diabetes.³⁴ Prior findings found uninsured patients have shorter LOS.³⁵ Therefore, these findings in our study are difficult to explain without further work to understand whether there are health disparities in the way patients are cared for during hospitalization that may shorten or lengthen their LOS because of factors outside of their clinical need.

The finding that gender modified the effect of low HL on LOS was unexpected. There were similar proportions of men and women with low HL. There is evidence to support that women make the majority of health decisions for themselves and their familes³⁶; therefore, there may be unmeasured aspects of HL that provide an advantage for female vs male inpatients. Furthermore, omitted confounders, such as social support, may not fully capture potential gender-related differences. Future work is needed to understand the role of gender in relationship to HL and LOS.

Limitations of this study include its observational, single-centered design with information derived from administrative data; positive and negative confounding cannot be ruled out. For instance, we did not control for complex aspects affecting LOS, such as discharge disposition and goals of care (eg, aggressive care after discharge vs hospice). To address this limitation, multivariate analyses were performed, which were adjusted for illness severity scores and took into account both comorbidity and severity of the current illness. Additionally, although it is important to study such populations, our largely urban, minority sample is not representative of the U.S. population, and within our large sample, there were participants with missing data who had lower HL on average, although this group represented only 5% of the sample. Finally, different HL tools have noncomplete concordance, which has been seen when comparing the BHLS with more objective tools.^20,37 Furthermore, certain in-hospital clinical scenarios (eg, recent stroke or prolonged intensive care unit stay) may present unique challenges in establishing a baseline HL level. However, the BHLS was used in this study because of its greater feasibility.

In conclusion, this study is the first to evaluate the relationship between low HL and LOS. The findings suggest that HL may play a role in shaping outcomes in the inpatient setting and that targeting interventions toward screened patients may be a pathway toward mitigating adverse effects. Our findings need to be replicated in larger, more representative samples, and further work understanding subpopulations within the low HL population is needed. Future work should measure this association in diverse inpatient settings (eg, psychiatric, surgical, and specialty), in addition to assessing associations between HL and other important in-hospital outcome measures, including mortality and discharge disposition.

 

Acknowledgments

The authors thank the Hospitalist Project team for their assistance with data collection. The authors especially thank Chuanhong Liao and Ashley Snyder for assistance with statistical analyses; Andrea Flores, Ainoa Coltri, and Tom Best for their assistance with data management. The authors would also like to thank Nicole Twu for her help with preparing and editing the manuscript.

Disclosures

Dr. Jaffee was supported by a Calvin Fentress Research Fellowship and NIH R25MH094612. Dr. Press was supported by a career development award (NHLBI K23HL118151). This work was also supported by a seed grant from the Center for Health Administration Studies. All other authors declare no conflicts of interest.

Health literacy (HL), defined as patients’ ability to understand health information and make health decisions,¹ is a prevalent problem in the outpatient and inpatient settings.^2,3 In both settings, low HL has adverse implications for self-care including interpreting health labels⁴ and taking medications correctly.⁵ Among outpatient cohorts, HL has been associated with worse outcomes and acute care utilization.⁶ Associations with low HL include increased hospitalizations,⁷ rehospitalizations,^8,9 emergency department visits,¹⁰ and decreased preventative care use.¹¹ Among the elderly, low HL is associated with increased mortality¹² and decreased self-perception of health.¹³

A systematic review revealed that most high-quality HL outcome studies were conducted in the outpatient setting.⁶ There have been very few studies assessing effects of low HL in an acute-care setting.^7,14 These studies have evaluated postdischarge outcomes, including admissions or readmissions,^7-9 and medication knowledge.¹⁴ To the best of our knowledge, there are no studies evaluating associations between HL and hospital length of stay (LOS).

LOS has received much attention as providers and payers focus more on resource utilization and eliminating adverse effects of prolonged hospitalization.¹⁵ LOS is multifactorial, depending on clinical characteristics like disease severity, as well as on sociocultural, demographic, and geographic factors.¹⁶ Despite evidence that LOS reductions translate into improved resource allocation and potentially fewer complications, there remains a tension between the appropriate LOS and one that is too short for a given condition.¹⁷

Because low HL is associated with inefficient resource utilization, we hypothesized that low HL would be associated with increased LOS after controlling for illness severity. Our objectives were to evaluate the association between low HL and LOS and whether such an association was modified by illness severity and sociodemographics.

METHODS

Study Design, Setting, Participants

An in-hospital, cohort study design of patients who were admitted or transferred to the general medicine service at the University of Chicago between October 2012 and November 2015 and screened for inclusion as part of a large, ongoing study of inpatient care quality was conducted.¹⁸ Exclusion criteria included observation status, age under 18 years, non-English speaking, and repeat participants. Those who died during hospitalization or whose discharge status was missing were excluded because the primary goal was to examine the association of HL and time to discharge, which could not be evaluated among those who died. We excluded participants with LOS >30 days to limit overly influential effects of extreme outliers (1% of the population).

Variables

HL was screened using the Brief Health Literacy Screen (BHLS), a validated, 3-question verbal survey not requiring adequate visual acuity to assess HL.^19,20 The 3 questions are as follows: (1) “How confident are you filling out medical forms by yourself?”, (2) “How often do you have someone help you read hospital materials?”, and (3) “How often do you have problems learning about your medical condition because of difficulty understanding written information?” Responses to the questions were scored on a 5-point Likert scale in which higher scores corresponded to higher HL.^21,22 The scores for each of the 3 questions were summed to yield a range between 3 and 15. On the individual questions, prior work has demonstrated improved test performance with a cutoff of ≤3, which corresponds to a response of “some of the time” or “somewhat”; therefore, when the 3 questions were summed together, scores of ≤9 were considered indicative of low HL.^21,23

For severity of illness adjustment, we used relative weights derived from the 3M (3M, Maplewood, MN) All Patient Refined Diagnosis Related Groups (APR-DRG) classification system, which uses administrative data to classify the severity. The APR-DRG system assigns each admission to a DRG based on principal diagnosis; for each DRG, patients are then subdivided into 4 severity classes based on age, comorbidity, and interactions between these variables and the admitting diagnosis.²⁴ Using the base DRG and severity score, the system assigns relative weights that reflect differences in expected hospital resource utilization.

LOS was derived from hospital administrative data and counted from the date of admission to the hospital. Participants who were discharged on the day of admission were counted as having an LOS of 1. Insurance status (Medicare, Medicaid, no payer, private) also was obtained from administrative data. Age, sex (male or female), education (junior high or less, some high school, high school graduate, some college, college graduate, postgraduate), and race (black/African American, white, Asian or Pacific Islander [including Asian Indian, Chinese, Filipino, Japanese, Korean, Vietnamese, other Asian, Native Hawaiian, Guam/Chamorro, Samoan, other Pacific], American Indian or Alaskan Native, multiple race) were obtained from administrative data based on information provided by the patient. Participants with missing data on any of the sociodemographic variables or on the APR-DRG score were excluded from the analysis.

 

Statistical Analysis

χ² and 2-tailed t tests were used to compare categorical and continuous variables, respectively. Multivariate linear regressions were employed to measure associations between the independent variables (HL, illness severity, race, gender, education, and insurance status) and the dependent variable, LOS. Independent variables were chosen for clinical significance and retained in the model regardless of statistical significance. The adjusted R² values of models with and without the HL variable included were reported to provide information on the contribution of HL to the overall model.

Because LOS was observed to be right skewed and residuals of the untransformed regression were observed to be non-normally distributed, the decision was made to natural log transform LOS, which is consistent with previous hospital LOS studies.¹⁶ Regression coefficients and confidence intervals were then transformed into percentage estimates using the following equation: 100(e^β–1). Adjusted R² was reported for the transformed regression.

The APR-DRG relative weight was treated as a continuous variable. Sociodemographic variables were dichotomized as follows: female vs male; high school graduates vs not; African American vs not; Medicaid/no payer vs Medicare/private payer. Age was not included in the multivariate model because it has been incorporated into the weighted APR-DRG illness severity scores.

Each of the sociodemographic variables and the APR-DRG score were examined for effect modification via the same multivariate linear equation described above, with the addition of an interaction term. A separate regression was performed with an interaction term between age (dichotomized at ≥65) and HL to investigate whether age modified the association between HL and LOS. Finally, we explored whether effects were isolated to long vs short LOS by dividing the sample based on the mean LOS (≥6 days) and performing separate multivariate comparisons.

Sensitivity analyses were performed to exclude those with LOS greater than the 90th percentile and those with APR-DRG score greater than the 90th percentile; age was added to the model as a continuous variable to evaluate whether the illness severity score fully adjusted for the effects of age on LOS. Furthermore, we compared the participants with missing data to those with complete data across both dependent and independent variables. Alpha was set at 0.05; analyses were performed using Stata Version 14 (Stata, College Station, TX).

RESULTS

A total of 5983 participants met inclusion criteria and completed the HL assessment; of these participants, 75 (1%) died during hospitalization, 9 (0.2%) had missing discharge status, and 79 (1%) had LOS >30 days. Two hundred eighty (5%) were missing data on sociodemographic variables or APR-DRG score. Of the remaining (n = 5540), the mean age was 57 years (standard deviation [SD] = 19 years), over half of participants were female (57%), and the majority were African American (73%) and had graduated from high school (81%). The sample was divided into those with private insurance (25%), those with Medicare (46%), and those with Medicaid (26%); 2% had no payer. The mean APR-DRG score was 1.3 (SD = 1.2), and the scores ranged from 0.3 to 15.8.

On the BHLS screen for HL, 20% (1104/5540) had inadequate HL. Participants with low HL had higher weighted illness severity scores (average 1.4 vs 1.3; P = 0.003). Participants with low HL were also more likely to be 65 or older (55% vs 33%; P < 0.001), non-high school graduates (35% vs 15%; P < 0.001), and African American (78% vs 72%; P < 0.001), and to have Medicare or private insurance (75% vs 71%; P = 0.02). There was no significant difference with respect to gender (54% male vs 57% female; P = 0.1)

The mean and median LOS were 6 ± 5 days and 4 days (interquartile range 2-7 days), respectively. Those with low HL had a longer average LOS (6.0 vs 5.4 days; P < 0.001). In multivariate analysis controlling for APR-DRG score, gender, education, race, and insurance status, low HL was associated with an 11.1% longer LOS (95% CI, 6.1-16.1; P < 0.001; Table 1). The adjusted R² value for the regression was 25.0% including HL and 24.7% with HL excluded. Additionally, being African American (P < 0.001) and having Medicaid or no insurance (P < 0.001) were associated with a shorter LOS in multivariate analysis (Table 1). The association of HL and LOS in multivariate modeling remained significant among participants with LOS <6 days (10.2%; 95% CI, 5.6%-14.9%; P < 0.001), but not among participants with LOS ≥6 days (0.4%; 95% CI, −3.6% to 4.4%; P = 0.8).

Neither age ≥65 (P = 0.4) nor illness severity score (P = 0.5) significantly modified the effect of HL on LOS. However, the effect of HL on hospital LOS was significantly modified by gender (P = 0.02). Among men, low HL was associated with a 17.8% longer LOS (95% CI, 10.0%-25.7%; P < 0.001), but among women, low HL was associated with only a 7.7% longer LOS (95% CI, 1.9%-13.5%; P = 0.009). Among the remaining demographics, high school graduation status (P = 0.4), being African American (P = 0.6), and insurance status (P = 0.2) did not significantly modify the effect of HL on LOS. In sensitivity analysis, excluding participants with LOS above the 90th percentile of 12 days and excluding participants with illness severity scores above the 90th percentile, low HL was still associated with longer LOS (P < 0.001 and P = 0.001, respectively; Table 2). In the final sensitivity analysis, although age remained a significant predictor of longer LOS after controlling for illness severity (0.2% increase per year, 95% CI, 0.1%-0.3%; P < 0.001), low HL nevertheless remained significantly associated with longer LOS (P < 0.001; Table 2).

Finally, we compared the group with missing data (n = 280) to the group with complete data (n = 5540). The participants with missing data were more likely to have low HL (31% [86/280] vs 20%; P < 0.001) and to have Medicare or private insurance (82% [177/217] vs 72%; P = 0.002); however, they were not more likely to be 65 or older (40% [112/280] vs 37%; P = 0.3), high school graduates (88% [113/129] vs 81%; P = 0.06), African American (69% [177/256] vs 73%; P = 0.1), or female (57% [158/279] vs 57%; P = 1), nor were they more likely to have longer LOS (5.7 [n = 280] vs 5.5 days; P = 0.6) or higher illness severity scores (1.3 [n = 231] vs 1.3; P = 0.7).

 

DISCUSSION

To our knowledge, this study is the first to evaluate the association between low HL and an important in-hospital outcome measure, hospital LOS. We found that low HL was associated with a longer hospital LOS, a result which remained significant when controlling for severity of illness and sociodemographic variables and when testing the model for sensitivity to the highest values of LOS and illness severity. Additionally, the association of HL with LOS appeared concentrated among participants with shorter LOS. Relative to other predictors, the contribution of HL to the overall LOS model was small, as evidenced by the change in adjusted R² values with HL excluded.

Among the covariates, only gender modified the association between HL and LOS; the findings suggested that men were more susceptible to the effect of low HL on increased LOS. Illness severity and other sociodemographics, including age ≥65, did not appear to modify the association. We also found that being African American and having Medicaid or no insurance were associated with a significantly shorter LOS in multivariate analysis.

Previous work suggested that the adverse health effects of low HL may be mediated through several pathways, including health knowledge, self-efficacy, health skills, and illness stigma.^25-27 The finding of a small but significant relationship between HL and LOS was not surprising given these known associations; nevertheless, there may be an additional patient-dependent effect of low HL on LOS not discovered here. For instance, patients with poor health knowledge and self-efficacy might stay in the hospital longer if they or their providers do not feel comfortable with their self-care ability.

This finding may be useful in developing hospital-based interventions. HL-specific interventions, several of which have been tested in the inpatient setting,^14,28,29 have shown promise toward improving health knowledge,³⁰ disease severity,³¹ and health resource utilization.³²

Those with low HL may lack the self-efficacy to participate in discharge planning; in fact, previous work has related low HL to posthospital readmissions.^8,9 Conversely, patients with low HL might struggle to engage in the inpatient milieu, advocating for shorter LOS if they feel alienated by the inpatient experience.

These possibilities show that LOS is a complex measure shown to depend on patient-level characteristics and on provider-based, geographical, and sociocultural factors.^16,33 With these forces at play, additional effects of lower levels of HL may be lost without phenotyping patients by both level of HL and related characteristics, such as self-efficacy, health skills, and stigma. By gathering these additional data, future work should explore whether subpopulations of patients with low HL may be at risk for too-short vs too-long hospital admissions.

For instance, in this study, both race and Medicaid insurance were associated with shorter LOS. Being African American was associated with shorter LOS in our study but has been found to be associated with longer LOS in another study specifically focused on diabetes.³⁴ Prior findings found uninsured patients have shorter LOS.³⁵ Therefore, these findings in our study are difficult to explain without further work to understand whether there are health disparities in the way patients are cared for during hospitalization that may shorten or lengthen their LOS because of factors outside of their clinical need.

The finding that gender modified the effect of low HL on LOS was unexpected. There were similar proportions of men and women with low HL. There is evidence to support that women make the majority of health decisions for themselves and their familes³⁶; therefore, there may be unmeasured aspects of HL that provide an advantage for female vs male inpatients. Furthermore, omitted confounders, such as social support, may not fully capture potential gender-related differences. Future work is needed to understand the role of gender in relationship to HL and LOS.

Limitations of this study include its observational, single-centered design with information derived from administrative data; positive and negative confounding cannot be ruled out. For instance, we did not control for complex aspects affecting LOS, such as discharge disposition and goals of care (eg, aggressive care after discharge vs hospice). To address this limitation, multivariate analyses were performed, which were adjusted for illness severity scores and took into account both comorbidity and severity of the current illness. Additionally, although it is important to study such populations, our largely urban, minority sample is not representative of the U.S. population, and within our large sample, there were participants with missing data who had lower HL on average, although this group represented only 5% of the sample. Finally, different HL tools have noncomplete concordance, which has been seen when comparing the BHLS with more objective tools.^20,37 Furthermore, certain in-hospital clinical scenarios (eg, recent stroke or prolonged intensive care unit stay) may present unique challenges in establishing a baseline HL level. However, the BHLS was used in this study because of its greater feasibility.

In conclusion, this study is the first to evaluate the relationship between low HL and LOS. The findings suggest that HL may play a role in shaping outcomes in the inpatient setting and that targeting interventions toward screened patients may be a pathway toward mitigating adverse effects. Our findings need to be replicated in larger, more representative samples, and further work understanding subpopulations within the low HL population is needed. Future work should measure this association in diverse inpatient settings (eg, psychiatric, surgical, and specialty), in addition to assessing associations between HL and other important in-hospital outcome measures, including mortality and discharge disposition.

 

Acknowledgments

The authors thank the Hospitalist Project team for their assistance with data collection. The authors especially thank Chuanhong Liao and Ashley Snyder for assistance with statistical analyses; Andrea Flores, Ainoa Coltri, and Tom Best for their assistance with data management. The authors would also like to thank Nicole Twu for her help with preparing and editing the manuscript.

Disclosures

Dr. Jaffee was supported by a Calvin Fentress Research Fellowship and NIH R25MH094612. Dr. Press was supported by a career development award (NHLBI K23HL118151). This work was also supported by a seed grant from the Center for Health Administration Studies. All other authors declare no conflicts of interest.

In This Edition

Literature at a Glance

A guide to this month’s studies

• ICU volume and outcomes
• Bicarbonate and contrast-induced nephropathy
• Rate of incidental findings in chest CT angiography
• Consequences of adverse-event reporting by physicians
• Hip fracture comanagement
• Niacin vs. ezetimibe in atherosclerosis
• Effect of hospital pharmacists on readmission rates
• Antibiotics in acute exacerbations of COPD

 

Higher Patient ICU Inflow Volumes Are Associated with Unplanned Readmissions to ICU

Clinical question: Do higher rates of unplanned ICU readmissions occur on days with high patient inflow volumes?

Background: Patients readmitted to ICUs have longer lengths of stay (LOS) and higher rates of in-hospital mortality. Previous studies suggest many ICU readmissions might be due to premature discharge, but there is little evidence evaluating the impact of patient inflow volumes on the incidence of ICU readmissions.

Study design: Retrospective, cohort study.

Setting: Large, urban, tertiary-care academic medical center in Baltimore.

Synopsis: A retrospective review of 3,233 discharges from a neurosciences critical-care unit revealed 95 unplanned readmissions to the ICU setting within 72 hours of discharge to lower level of care. The odds of one or more discharges becoming an unplanned readmission became significantly higher on days when ≥8 patients were admitted to the ICU (OR, 1.66; 95% CI, 1.03-2.68), and the odds of an unplanned readmission were almost five times higher on days when ≥10 patients were admitted, compared with days when ≤9 patients were admitted (OR, 4.99; 95% CI, 2.45-10.17).

After adjusting for patient complexity, patients discharged on days with ≥10 admissions had higher than twice the odds of becoming an unplanned readmission than patients discharged on days with ≤9 admissions (OR, 2.34; 95% CI, 1.27-4.34).

This study was limited to patients in a neurosciences critical-care unit at a single academic medical center. Further research is needed to better understand how high admission volumes lead to increased unplanned readmission rates.

Bottom line: Days with high patient inflow volumes to the ICU are associated with higher rates of unplanned readmissions to the ICU, and the rate of unplanned readmissions becomes significant once a daily threshold of eight admissions is reached.

Citation: Baker DR, Pronovost PJ, Morlock LL, Geocadin RG, Holzmueller CG. Patient flow variability and unplanned readmissions to an intensive care unit. Crit Care Med. 2009;37(11):2882-2887.

 

Effectiveness of Sodium Bicarbonate in Contrast-Induced Nephropathy Prevention

Clinical question: Is IV sodium bicarbonate effective for prevention of contrast-induced nephropathy (CIN) in high-risk patients?

Background: CIN is a leading cause of acute kidney injury in the hospital setting. Some studies have suggested IV sodium bicarbonate might reduce risk for CIN; other studies challenge this conclusion.

 

Study design: Systematic review.

Setting: Published and unpublished randomized, controlled trials performed worldwide.

Synopsis: The research examined in this study was composed of randomized, controlled trials that investigated CIN prevention and included IV sodium bicarbonate in one of the treatment groups. Nine published and 15 unpublished trials were selected for a total of 3,563 patients studied. The overall pooled relative risk of CIN in patients treated with IV sodium bicarbonate compared with normal saline was 0.62 (95% CI, 0.45-0.86), though the strength of this evidence was questioned.

Significant heterogeneity across studies was found (I²=49.1%; P=0.004), partially related to substantially greater treatment effect in published (RR 0.43, 95% CI, 0.25-0.75) versus unpublished (RR 0.78, 95% CI, 0.52-1.17) studies. Publication bias was confirmed statistically. Among the published studies, greater treatment effect favoring bicarbonate over saline tended to be reported in those published before 2008, had fewer patients (<200) and events (<15), had measured events within 48 hours, and were studies of lower quality.

No effects regarding the risk of heart failure, the need for dialysis, or mortality were found, though the studies were not specifically designed to investigate those clinical outcomes. Larger studies are needed to better assess these questions.

Bottom line: IV sodium bicarbonate for CIN prevention in high-risk patients could be less effective than previous reports have suggested.

Citation: Zoungas S, Ninomiya T, Huxley R, et al. Systematic review: sodium bicarbonate treatment regimens for the prevention of contrast-induced nephropathy. Ann Intern Med. 2009;151(9):631-638.

 

Incidental Findings More Frequent than PE in Chest CT Angiograms

Clinical question: What is the prevalence of incidental findings on chest-computed tomographic angiograms (CTAs) ordered by an ED to evaluate for pulmonary embolism (PE)?

Background: CTAs commonly are ordered by ED physicians to assess for PE. While CTAs might yield findings to support an alternate diagnosis to PE, incidental findings might be found that often require further radiographic or clinical followup. The workup of these incidental findings can be burdensome and low-yield.

Study design: Retrospective chart review.

Setting: Single, academic, tertiary-care hospital in North Carolina.

Synopsis: All patients who underwent CTA evaluation for PE in the ED over two enrollment periods were selected; radiographic findings were compiled and their medical records reviewed. Fifty-five of 589 CTAs (9%) were positive for PE. New incidental findings requiring radiographic or clinical followup were found in 141 cases (24%).

Overall, pulmonary nodules were most common, requiring followup in 73 (13%) cases. Adenopathy requiring followup was seen in 51 cases (9%), and new masses requiring followup were found in 12 cases (2%). Findings to support alternate diagnoses for shortness of breath, hypoxemia, or tachycardia were found in 195 patients (33%), most commonly pleural effusion (19%) and infiltrates (11%). Other incidental findings that required less-urgent clinical attention were common with 615 total findings, most frequently nonmalignant bone findings in 144 cases (24%), mild dependent atelectasis in 137 cases (23%), and emphysema in 69 cases (12%).

 

Bottom line: Incidental findings requiring followup were more than twice as common as PE (24% vs. 9%) in CTAs ordered to evaluate for PE in an ED.

Citation: Hall WB, Truitt SG, Scheunemann LP, et al. The prevalence of clinically relevant incidental findings on chest computed tomographic angiograms ordered to diagnose pulmonary embolism. Arch Intern Med. 2009;169(21):1961-1965.

 

Patients Don’t Penalize for Adverse-Outcome Disclosure

Clinical question: What patient or clinical characteristics affect the likelihood of physician reporting of an adverse outcome, and how does adverse-outcome disclosure affect patient perceptions of quality of care?

Background: Harmful adverse events (AE), injuries caused by medical management rather than by the underlying condition of the patient, are common in the U.S. Previous studies have focused on physician and provider attitudes about disclosure. Little is known about how characteristics of the AE affect disclosure, and how disclosure affects patients’ perceptions of quality of care.

Study design: Retrospective cohort study.

Setting: Acute-care hospitals in Massachusetts.

Synopsis: Of 4,143 eligible patients, 2,582 (62%) agreed to a telephone interview that asked about patient experiences with adverse events during their hospital stay. Respondents reporting an AE were asked about disclosure by medical staff, effects of adverse events on their hospital course, and the quality of their hospital care.

Of the 845 AEs reported by 608 patients, only 40% were disclosed, defined as “anyone from the hospital explaining why the negative effects occurred.” The majority of the AEs were related to newly prescribed medications (40%) and surgical procedures (34%). Researchers determined that 31% of the AEs were preventable and 75% were severe. In multivariate analysis, disclosure was less likely if the AE was preventable or if patients had long-term effects from the AE. Patients with an AE were more likely to rate the quality of their hospitalization higher if there had been disclosure.

Bottom line: Disclosure of adverse events by medical personnel is low (40%) in hospitalized patients, even though disclosure of adverse events increases patients’ ratings of quality of care.

Citation: López L, Weismann JS, Schneider EC, Weingart SN, Cohen AP, Epstein AM. Disclosure of hospital adverse events and its association with patients’ ratings of the quality of care. Arch Intern Med. 2009;169(20):1888-1894.

 

Comanagement of Hip-Fracture Patients by Geriatricians Decreases Time to Surgery, LOS, and Complications

Clinical question: Does comanagement of hip-fracture patients by geriatricians and orthopedic surgeons improve short-term outcomes?

 

Background: Hip fractures in older adults are associated with considerable morbidity and mortality. A model at a single center, where hip fracture patients are comanaged by geriatricians and orthopedic surgeons, demonstrated decreased LOS, readmission rates, and mortality when compared with national data. This study compares results to a usual-care site.

Study design: Retrospective cohort study.

Setting: Community-based teaching hospital and a tertiary-care hospital in Rochester, N.Y.

Synopsis: Researchers enrolled 314 patients with hip fractures. The 193 patients in the intervention group were comanaged by geriatricians and orthopedic surgeons. The 121 patients in the usual-care group were admitted under the care of orthopedic surgeons, and hospitalists were consulted when deemed necessary. Retrospective chart reviews were performed; complications were defined a priori.

When compared with usual care, patients in the intervention group had significantly shorter times to surgery (24.1 hours vs. 37.4 hours), shorter LOS (4.6 days vs. 8.3 days), fewer complications (30.6% vs. 46.3%), including fewer postoperative infections (2.3% vs. 19.8%), cardiac complications (1.0% vs. 7.4%), cases of thromboembolism (0.5% vs. 5.0%), episodes of bleeding (0% vs. 3.3%), and episodes of hypoxia (6.7% vs. 14.1%). There was no difference in inpatient mortality or 30-day readmission rates.

Further assessment comanagement by hospitalists and comanagement by geriatricians is needed.

Bottom line: Perioperative comanagement of hip-fracture patients by geriatricians and orthopedic surgeons significantly improves short-term outcomes.

Citation: Friedman SM, Mendelson DA, Bingham KW, Kates SL. Impact of a comanaged geriatric fracture center on short-term hip fracture outcomes. Arch Intern Med. 2009;169 (18):1712-1717.

 

Niacin Is Superior to Ezetimibe in Causing Significant Regression of Carotid Intima-Media Thickness when Combined with a Statin

Clinical question: Is ezetimibe superior to niacin for reducing carotid intima-media thickness (CIMT) in patients with coronary artery disease (CAD) already on statin monotherapy?

Background: Statin montherapy significantly reduces the risk of cardiovascular events, and further lowering of this risk can be achieved by reducing the LDL, using statin intensification, or adding ezetimibe, or by raising the HDL levels by adding niacin therapy. This comparative-effectiveness trial compared the efficacy of these two approaches.

Study design: Prospective, randomized, parallel-group, open-label study.

Setting: Tertiary-care military medical center, and private tertiary-care hospital in Washington, D.C.

Synopsis: Three hundred sixty-three patients with known CAD or CAD equivalent were enrolled, and all of the patients were maintained on statin therapy with LDL <100 and HDL <50. Patients were randomized to ezetimibe 10 mg/day or niacin, starting at 500 mg at bedtime and titrated to 2 g/day. Primary endpoint was a mean change in CIMT after 14 months. Secondary endpoints were change in lipid levels, composite of major cardiovascular events, drug discontinuation, and quality of life.

The trial was terminated early after 208 patients had completed the trial. Although ezetimibe showed greater reduction of LDL, niacin showed significantly greater reduction in the progression of CIMT. Patients receiving niacin experienced fewer cardiovascular events (1% vs. 5%) but had higher rates of withdrawal (15% vs. 9%) due to flushing.

Limitations of the study are small sample size, short follow-up period, and use of CIMT as a surrogate marker for clinical endpoint.

 

Bottom line: Niacin is superior to ezetimibe in reducing CIMT and raising HDL levels and might be more efficacious in reducing cardiovascular risk.

Citation: Taylor AJ, Villines TC, Stanek EJ, et al. Extended-release niacin or ezetimibe and carotid intima-media thickness. N Engl J Med. 2009;361(22):2113-2122.

 

Pharmacist-Facilitated Hospital Discharge Program Didn’t Reduce Post-Discharge Healthcare Resource Utilization

Clinical question: Does pharmacist-facilitated hospital discharge reduce hospital readmission rates?

Background: Medication discrepancies at the time of discharge often lead to confusion, medical errors, and readmission to the hospital. Patients who are at high risk of medication errors often are on multiple medications and experience adverse drug events upon discharge.

Study design: Prospective cohort study.

Setting: Tertiary-care, academic teaching hospital in Michigan.

Synopsis: One pharmacist alternated between the resident service and hospitalist service every month. The pharmacist monitored the patients being discharged for appropriateness and accuracy of medications. The pharmacist assessed medication therapy, reconciled medications, screened for adherence concerns, counseled and educated patients, and performed post-discharge telephone follow-up.

Primary outcomes were ED visits within 72 hours and readmission rates by day 14 and day 30.

The study found high numbers of medication discrepancies in the control (33.5%) and intervention (59.6%) groups, and these discrepancies were resolved prior to discharge; however, there was no significant impact on post-discharge ED visits, or 14- and 30-day readmission rates. Post-discharge telephone calls reduced 14-day readmission rates.

Bottom line: Pharmacist-facilitated hospital discharge did not significantly reduce post-discharge ED visits or readmissions.

Citation: Walker PC, Bernstein SJ, Jones JN, et al. Impact of a pharmacist-facilitated hospital discharge program. Arch Intern Med. 2009;169(21):2003-2010.

 

Questionable Antibiotic Benefit for Patients with Acute COPD Exacerbations

Clinical question: Does the addition of antibiotics to systemic corticosteroids provide additional benefits for patients hospitalized with acute exacerbations of chronic obstructive pulmonary disease (AECOPD)?

Background: The role of antibiotics in the treatment of AECOPD is unclear, particularly in addition to systemic corticosteroids. Many of the studies demonstrating the benefit of antibiotics were conducted several decades before systemic steroids were used routinely for the treatment of AECOPD.

Study design: Randomized, double-blinded, placebo-controlled study.

Setting: Two academic teaching hospitals in the Netherlands.

Synopsis: Two hundred sixty-five acute exacerbations of COPD were enrolled in the study, and patients were randomized to a seven-day course of 200 mg/day of doxycycline or placebo. All patients received systemic corticosteroids, nebulized bronchodilator therapy, and physiotherapy. The study found that doxycycline was equivalent to placebo for the primary endpoint of clinical success on day 30; however, doxycycline was superior to placebo for secondary outcomes of clinical success, clinical cure, symptomatic improvement, microbiological success, and reducing open label antibiotic use on day 10, but not on day 30.

Because the population studied had low levels of advanced antimicrobial resistance, the findings might not be generalizable. Results suggested a difference of treatment effect between subgroups based on C-reactive protein values, but further research is needed.

Bottom line: Patients treated with doxycycline for acute exacerbation of COPD had improved clinical outcomes at day 10, but the benefits were not significant at day 30. Data are still equivocal regarding benefits of antibiotics in patients with acute exacerbations of COPD.

Citation: Daniels JM, Snijders D, de Graaff CS, Vlaspolder F, Jansen HM, Boersma WG. Antibiotics in addition to systemic corticosteroids for acute exacerbations of chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2010;181(2):150-157. TH

 

In This Edition

Literature at a Glance

A guide to this month’s studies

• ICU volume and outcomes
• Bicarbonate and contrast-induced nephropathy
• Rate of incidental findings in chest CT angiography
• Consequences of adverse-event reporting by physicians
• Hip fracture comanagement
• Niacin vs. ezetimibe in atherosclerosis
• Effect of hospital pharmacists on readmission rates
• Antibiotics in acute exacerbations of COPD

 

Higher Patient ICU Inflow Volumes Are Associated with Unplanned Readmissions to ICU

Clinical question: Do higher rates of unplanned ICU readmissions occur on days with high patient inflow volumes?

Background: Patients readmitted to ICUs have longer lengths of stay (LOS) and higher rates of in-hospital mortality. Previous studies suggest many ICU readmissions might be due to premature discharge, but there is little evidence evaluating the impact of patient inflow volumes on the incidence of ICU readmissions.

Study design: Retrospective, cohort study.

Setting: Large, urban, tertiary-care academic medical center in Baltimore.

Synopsis: A retrospective review of 3,233 discharges from a neurosciences critical-care unit revealed 95 unplanned readmissions to the ICU setting within 72 hours of discharge to lower level of care. The odds of one or more discharges becoming an unplanned readmission became significantly higher on days when ≥8 patients were admitted to the ICU (OR, 1.66; 95% CI, 1.03-2.68), and the odds of an unplanned readmission were almost five times higher on days when ≥10 patients were admitted, compared with days when ≤9 patients were admitted (OR, 4.99; 95% CI, 2.45-10.17).

After adjusting for patient complexity, patients discharged on days with ≥10 admissions had higher than twice the odds of becoming an unplanned readmission than patients discharged on days with ≤9 admissions (OR, 2.34; 95% CI, 1.27-4.34).

This study was limited to patients in a neurosciences critical-care unit at a single academic medical center. Further research is needed to better understand how high admission volumes lead to increased unplanned readmission rates.

Bottom line: Days with high patient inflow volumes to the ICU are associated with higher rates of unplanned readmissions to the ICU, and the rate of unplanned readmissions becomes significant once a daily threshold of eight admissions is reached.

Citation: Baker DR, Pronovost PJ, Morlock LL, Geocadin RG, Holzmueller CG. Patient flow variability and unplanned readmissions to an intensive care unit. Crit Care Med. 2009;37(11):2882-2887.

 

Effectiveness of Sodium Bicarbonate in Contrast-Induced Nephropathy Prevention

Clinical question: Is IV sodium bicarbonate effective for prevention of contrast-induced nephropathy (CIN) in high-risk patients?

Background: CIN is a leading cause of acute kidney injury in the hospital setting. Some studies have suggested IV sodium bicarbonate might reduce risk for CIN; other studies challenge this conclusion.

 

Study design: Systematic review.

Setting: Published and unpublished randomized, controlled trials performed worldwide.

Synopsis: The research examined in this study was composed of randomized, controlled trials that investigated CIN prevention and included IV sodium bicarbonate in one of the treatment groups. Nine published and 15 unpublished trials were selected for a total of 3,563 patients studied. The overall pooled relative risk of CIN in patients treated with IV sodium bicarbonate compared with normal saline was 0.62 (95% CI, 0.45-0.86), though the strength of this evidence was questioned.

Significant heterogeneity across studies was found (I²=49.1%; P=0.004), partially related to substantially greater treatment effect in published (RR 0.43, 95% CI, 0.25-0.75) versus unpublished (RR 0.78, 95% CI, 0.52-1.17) studies. Publication bias was confirmed statistically. Among the published studies, greater treatment effect favoring bicarbonate over saline tended to be reported in those published before 2008, had fewer patients (<200) and events (<15), had measured events within 48 hours, and were studies of lower quality.

No effects regarding the risk of heart failure, the need for dialysis, or mortality were found, though the studies were not specifically designed to investigate those clinical outcomes. Larger studies are needed to better assess these questions.

Bottom line: IV sodium bicarbonate for CIN prevention in high-risk patients could be less effective than previous reports have suggested.

Citation: Zoungas S, Ninomiya T, Huxley R, et al. Systematic review: sodium bicarbonate treatment regimens for the prevention of contrast-induced nephropathy. Ann Intern Med. 2009;151(9):631-638.

 

Incidental Findings More Frequent than PE in Chest CT Angiograms

Clinical question: What is the prevalence of incidental findings on chest-computed tomographic angiograms (CTAs) ordered by an ED to evaluate for pulmonary embolism (PE)?

Background: CTAs commonly are ordered by ED physicians to assess for PE. While CTAs might yield findings to support an alternate diagnosis to PE, incidental findings might be found that often require further radiographic or clinical followup. The workup of these incidental findings can be burdensome and low-yield.

Study design: Retrospective chart review.

Setting: Single, academic, tertiary-care hospital in North Carolina.

Synopsis: All patients who underwent CTA evaluation for PE in the ED over two enrollment periods were selected; radiographic findings were compiled and their medical records reviewed. Fifty-five of 589 CTAs (9%) were positive for PE. New incidental findings requiring radiographic or clinical followup were found in 141 cases (24%).

Overall, pulmonary nodules were most common, requiring followup in 73 (13%) cases. Adenopathy requiring followup was seen in 51 cases (9%), and new masses requiring followup were found in 12 cases (2%). Findings to support alternate diagnoses for shortness of breath, hypoxemia, or tachycardia were found in 195 patients (33%), most commonly pleural effusion (19%) and infiltrates (11%). Other incidental findings that required less-urgent clinical attention were common with 615 total findings, most frequently nonmalignant bone findings in 144 cases (24%), mild dependent atelectasis in 137 cases (23%), and emphysema in 69 cases (12%).

 

Bottom line: Incidental findings requiring followup were more than twice as common as PE (24% vs. 9%) in CTAs ordered to evaluate for PE in an ED.

Citation: Hall WB, Truitt SG, Scheunemann LP, et al. The prevalence of clinically relevant incidental findings on chest computed tomographic angiograms ordered to diagnose pulmonary embolism. Arch Intern Med. 2009;169(21):1961-1965.

 

Patients Don’t Penalize for Adverse-Outcome Disclosure

Clinical question: What patient or clinical characteristics affect the likelihood of physician reporting of an adverse outcome, and how does adverse-outcome disclosure affect patient perceptions of quality of care?

Background: Harmful adverse events (AE), injuries caused by medical management rather than by the underlying condition of the patient, are common in the U.S. Previous studies have focused on physician and provider attitudes about disclosure. Little is known about how characteristics of the AE affect disclosure, and how disclosure affects patients’ perceptions of quality of care.

Study design: Retrospective cohort study.

Setting: Acute-care hospitals in Massachusetts.

Synopsis: Of 4,143 eligible patients, 2,582 (62%) agreed to a telephone interview that asked about patient experiences with adverse events during their hospital stay. Respondents reporting an AE were asked about disclosure by medical staff, effects of adverse events on their hospital course, and the quality of their hospital care.

Of the 845 AEs reported by 608 patients, only 40% were disclosed, defined as “anyone from the hospital explaining why the negative effects occurred.” The majority of the AEs were related to newly prescribed medications (40%) and surgical procedures (34%). Researchers determined that 31% of the AEs were preventable and 75% were severe. In multivariate analysis, disclosure was less likely if the AE was preventable or if patients had long-term effects from the AE. Patients with an AE were more likely to rate the quality of their hospitalization higher if there had been disclosure.

Bottom line: Disclosure of adverse events by medical personnel is low (40%) in hospitalized patients, even though disclosure of adverse events increases patients’ ratings of quality of care.

Citation: López L, Weismann JS, Schneider EC, Weingart SN, Cohen AP, Epstein AM. Disclosure of hospital adverse events and its association with patients’ ratings of the quality of care. Arch Intern Med. 2009;169(20):1888-1894.

 

Comanagement of Hip-Fracture Patients by Geriatricians Decreases Time to Surgery, LOS, and Complications

Clinical question: Does comanagement of hip-fracture patients by geriatricians and orthopedic surgeons improve short-term outcomes?

 

Background: Hip fractures in older adults are associated with considerable morbidity and mortality. A model at a single center, where hip fracture patients are comanaged by geriatricians and orthopedic surgeons, demonstrated decreased LOS, readmission rates, and mortality when compared with national data. This study compares results to a usual-care site.

Study design: Retrospective cohort study.

Setting: Community-based teaching hospital and a tertiary-care hospital in Rochester, N.Y.

Synopsis: Researchers enrolled 314 patients with hip fractures. The 193 patients in the intervention group were comanaged by geriatricians and orthopedic surgeons. The 121 patients in the usual-care group were admitted under the care of orthopedic surgeons, and hospitalists were consulted when deemed necessary. Retrospective chart reviews were performed; complications were defined a priori.

When compared with usual care, patients in the intervention group had significantly shorter times to surgery (24.1 hours vs. 37.4 hours), shorter LOS (4.6 days vs. 8.3 days), fewer complications (30.6% vs. 46.3%), including fewer postoperative infections (2.3% vs. 19.8%), cardiac complications (1.0% vs. 7.4%), cases of thromboembolism (0.5% vs. 5.0%), episodes of bleeding (0% vs. 3.3%), and episodes of hypoxia (6.7% vs. 14.1%). There was no difference in inpatient mortality or 30-day readmission rates.

Further assessment comanagement by hospitalists and comanagement by geriatricians is needed.

Bottom line: Perioperative comanagement of hip-fracture patients by geriatricians and orthopedic surgeons significantly improves short-term outcomes.

Citation: Friedman SM, Mendelson DA, Bingham KW, Kates SL. Impact of a comanaged geriatric fracture center on short-term hip fracture outcomes. Arch Intern Med. 2009;169 (18):1712-1717.

 

Niacin Is Superior to Ezetimibe in Causing Significant Regression of Carotid Intima-Media Thickness when Combined with a Statin

Clinical question: Is ezetimibe superior to niacin for reducing carotid intima-media thickness (CIMT) in patients with coronary artery disease (CAD) already on statin monotherapy?

Background: Statin montherapy significantly reduces the risk of cardiovascular events, and further lowering of this risk can be achieved by reducing the LDL, using statin intensification, or adding ezetimibe, or by raising the HDL levels by adding niacin therapy. This comparative-effectiveness trial compared the efficacy of these two approaches.

Study design: Prospective, randomized, parallel-group, open-label study.

Setting: Tertiary-care military medical center, and private tertiary-care hospital in Washington, D.C.

Synopsis: Three hundred sixty-three patients with known CAD or CAD equivalent were enrolled, and all of the patients were maintained on statin therapy with LDL <100 and HDL <50. Patients were randomized to ezetimibe 10 mg/day or niacin, starting at 500 mg at bedtime and titrated to 2 g/day. Primary endpoint was a mean change in CIMT after 14 months. Secondary endpoints were change in lipid levels, composite of major cardiovascular events, drug discontinuation, and quality of life.

The trial was terminated early after 208 patients had completed the trial. Although ezetimibe showed greater reduction of LDL, niacin showed significantly greater reduction in the progression of CIMT. Patients receiving niacin experienced fewer cardiovascular events (1% vs. 5%) but had higher rates of withdrawal (15% vs. 9%) due to flushing.

Limitations of the study are small sample size, short follow-up period, and use of CIMT as a surrogate marker for clinical endpoint.

 

Bottom line: Niacin is superior to ezetimibe in reducing CIMT and raising HDL levels and might be more efficacious in reducing cardiovascular risk.

Citation: Taylor AJ, Villines TC, Stanek EJ, et al. Extended-release niacin or ezetimibe and carotid intima-media thickness. N Engl J Med. 2009;361(22):2113-2122.

 

Pharmacist-Facilitated Hospital Discharge Program Didn’t Reduce Post-Discharge Healthcare Resource Utilization

Clinical question: Does pharmacist-facilitated hospital discharge reduce hospital readmission rates?

Background: Medication discrepancies at the time of discharge often lead to confusion, medical errors, and readmission to the hospital. Patients who are at high risk of medication errors often are on multiple medications and experience adverse drug events upon discharge.

Study design: Prospective cohort study.

Setting: Tertiary-care, academic teaching hospital in Michigan.

Synopsis: One pharmacist alternated between the resident service and hospitalist service every month. The pharmacist monitored the patients being discharged for appropriateness and accuracy of medications. The pharmacist assessed medication therapy, reconciled medications, screened for adherence concerns, counseled and educated patients, and performed post-discharge telephone follow-up.

Primary outcomes were ED visits within 72 hours and readmission rates by day 14 and day 30.

The study found high numbers of medication discrepancies in the control (33.5%) and intervention (59.6%) groups, and these discrepancies were resolved prior to discharge; however, there was no significant impact on post-discharge ED visits, or 14- and 30-day readmission rates. Post-discharge telephone calls reduced 14-day readmission rates.

Bottom line: Pharmacist-facilitated hospital discharge did not significantly reduce post-discharge ED visits or readmissions.

Citation: Walker PC, Bernstein SJ, Jones JN, et al. Impact of a pharmacist-facilitated hospital discharge program. Arch Intern Med. 2009;169(21):2003-2010.

 

Questionable Antibiotic Benefit for Patients with Acute COPD Exacerbations

Clinical question: Does the addition of antibiotics to systemic corticosteroids provide additional benefits for patients hospitalized with acute exacerbations of chronic obstructive pulmonary disease (AECOPD)?

Background: The role of antibiotics in the treatment of AECOPD is unclear, particularly in addition to systemic corticosteroids. Many of the studies demonstrating the benefit of antibiotics were conducted several decades before systemic steroids were used routinely for the treatment of AECOPD.

Study design: Randomized, double-blinded, placebo-controlled study.

Setting: Two academic teaching hospitals in the Netherlands.

Synopsis: Two hundred sixty-five acute exacerbations of COPD were enrolled in the study, and patients were randomized to a seven-day course of 200 mg/day of doxycycline or placebo. All patients received systemic corticosteroids, nebulized bronchodilator therapy, and physiotherapy. The study found that doxycycline was equivalent to placebo for the primary endpoint of clinical success on day 30; however, doxycycline was superior to placebo for secondary outcomes of clinical success, clinical cure, symptomatic improvement, microbiological success, and reducing open label antibiotic use on day 10, but not on day 30.

Because the population studied had low levels of advanced antimicrobial resistance, the findings might not be generalizable. Results suggested a difference of treatment effect between subgroups based on C-reactive protein values, but further research is needed.

Bottom line: Patients treated with doxycycline for acute exacerbation of COPD had improved clinical outcomes at day 10, but the benefits were not significant at day 30. Data are still equivocal regarding benefits of antibiotics in patients with acute exacerbations of COPD.

Citation: Daniels JM, Snijders D, de Graaff CS, Vlaspolder F, Jansen HM, Boersma WG. Antibiotics in addition to systemic corticosteroids for acute exacerbations of chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2010;181(2):150-157. TH

 

In This Edition

Literature at a Glance

A guide to this month’s studies

• ICU volume and outcomes
• Bicarbonate and contrast-induced nephropathy
• Rate of incidental findings in chest CT angiography
• Consequences of adverse-event reporting by physicians
• Hip fracture comanagement
• Niacin vs. ezetimibe in atherosclerosis
• Effect of hospital pharmacists on readmission rates
• Antibiotics in acute exacerbations of COPD

 

Higher Patient ICU Inflow Volumes Are Associated with Unplanned Readmissions to ICU

Clinical question: Do higher rates of unplanned ICU readmissions occur on days with high patient inflow volumes?

Background: Patients readmitted to ICUs have longer lengths of stay (LOS) and higher rates of in-hospital mortality. Previous studies suggest many ICU readmissions might be due to premature discharge, but there is little evidence evaluating the impact of patient inflow volumes on the incidence of ICU readmissions.

Study design: Retrospective, cohort study.

Setting: Large, urban, tertiary-care academic medical center in Baltimore.

Synopsis: A retrospective review of 3,233 discharges from a neurosciences critical-care unit revealed 95 unplanned readmissions to the ICU setting within 72 hours of discharge to lower level of care. The odds of one or more discharges becoming an unplanned readmission became significantly higher on days when ≥8 patients were admitted to the ICU (OR, 1.66; 95% CI, 1.03-2.68), and the odds of an unplanned readmission were almost five times higher on days when ≥10 patients were admitted, compared with days when ≤9 patients were admitted (OR, 4.99; 95% CI, 2.45-10.17).

After adjusting for patient complexity, patients discharged on days with ≥10 admissions had higher than twice the odds of becoming an unplanned readmission than patients discharged on days with ≤9 admissions (OR, 2.34; 95% CI, 1.27-4.34).

This study was limited to patients in a neurosciences critical-care unit at a single academic medical center. Further research is needed to better understand how high admission volumes lead to increased unplanned readmission rates.

Bottom line: Days with high patient inflow volumes to the ICU are associated with higher rates of unplanned readmissions to the ICU, and the rate of unplanned readmissions becomes significant once a daily threshold of eight admissions is reached.

Citation: Baker DR, Pronovost PJ, Morlock LL, Geocadin RG, Holzmueller CG. Patient flow variability and unplanned readmissions to an intensive care unit. Crit Care Med. 2009;37(11):2882-2887.

 

Effectiveness of Sodium Bicarbonate in Contrast-Induced Nephropathy Prevention

Clinical question: Is IV sodium bicarbonate effective for prevention of contrast-induced nephropathy (CIN) in high-risk patients?

Background: CIN is a leading cause of acute kidney injury in the hospital setting. Some studies have suggested IV sodium bicarbonate might reduce risk for CIN; other studies challenge this conclusion.

 

Study design: Systematic review.

Setting: Published and unpublished randomized, controlled trials performed worldwide.

Synopsis: The research examined in this study was composed of randomized, controlled trials that investigated CIN prevention and included IV sodium bicarbonate in one of the treatment groups. Nine published and 15 unpublished trials were selected for a total of 3,563 patients studied. The overall pooled relative risk of CIN in patients treated with IV sodium bicarbonate compared with normal saline was 0.62 (95% CI, 0.45-0.86), though the strength of this evidence was questioned.

Significant heterogeneity across studies was found (I²=49.1%; P=0.004), partially related to substantially greater treatment effect in published (RR 0.43, 95% CI, 0.25-0.75) versus unpublished (RR 0.78, 95% CI, 0.52-1.17) studies. Publication bias was confirmed statistically. Among the published studies, greater treatment effect favoring bicarbonate over saline tended to be reported in those published before 2008, had fewer patients (<200) and events (<15), had measured events within 48 hours, and were studies of lower quality.

No effects regarding the risk of heart failure, the need for dialysis, or mortality were found, though the studies were not specifically designed to investigate those clinical outcomes. Larger studies are needed to better assess these questions.

Bottom line: IV sodium bicarbonate for CIN prevention in high-risk patients could be less effective than previous reports have suggested.

Citation: Zoungas S, Ninomiya T, Huxley R, et al. Systematic review: sodium bicarbonate treatment regimens for the prevention of contrast-induced nephropathy. Ann Intern Med. 2009;151(9):631-638.

 

Incidental Findings More Frequent than PE in Chest CT Angiograms

Clinical question: What is the prevalence of incidental findings on chest-computed tomographic angiograms (CTAs) ordered by an ED to evaluate for pulmonary embolism (PE)?

Background: CTAs commonly are ordered by ED physicians to assess for PE. While CTAs might yield findings to support an alternate diagnosis to PE, incidental findings might be found that often require further radiographic or clinical followup. The workup of these incidental findings can be burdensome and low-yield.

Study design: Retrospective chart review.

Setting: Single, academic, tertiary-care hospital in North Carolina.

Synopsis: All patients who underwent CTA evaluation for PE in the ED over two enrollment periods were selected; radiographic findings were compiled and their medical records reviewed. Fifty-five of 589 CTAs (9%) were positive for PE. New incidental findings requiring radiographic or clinical followup were found in 141 cases (24%).

Overall, pulmonary nodules were most common, requiring followup in 73 (13%) cases. Adenopathy requiring followup was seen in 51 cases (9%), and new masses requiring followup were found in 12 cases (2%). Findings to support alternate diagnoses for shortness of breath, hypoxemia, or tachycardia were found in 195 patients (33%), most commonly pleural effusion (19%) and infiltrates (11%). Other incidental findings that required less-urgent clinical attention were common with 615 total findings, most frequently nonmalignant bone findings in 144 cases (24%), mild dependent atelectasis in 137 cases (23%), and emphysema in 69 cases (12%).

 

Bottom line: Incidental findings requiring followup were more than twice as common as PE (24% vs. 9%) in CTAs ordered to evaluate for PE in an ED.

Citation: Hall WB, Truitt SG, Scheunemann LP, et al. The prevalence of clinically relevant incidental findings on chest computed tomographic angiograms ordered to diagnose pulmonary embolism. Arch Intern Med. 2009;169(21):1961-1965.

 

Patients Don’t Penalize for Adverse-Outcome Disclosure

Clinical question: What patient or clinical characteristics affect the likelihood of physician reporting of an adverse outcome, and how does adverse-outcome disclosure affect patient perceptions of quality of care?

Background: Harmful adverse events (AE), injuries caused by medical management rather than by the underlying condition of the patient, are common in the U.S. Previous studies have focused on physician and provider attitudes about disclosure. Little is known about how characteristics of the AE affect disclosure, and how disclosure affects patients’ perceptions of quality of care.

Study design: Retrospective cohort study.

Setting: Acute-care hospitals in Massachusetts.

Synopsis: Of 4,143 eligible patients, 2,582 (62%) agreed to a telephone interview that asked about patient experiences with adverse events during their hospital stay. Respondents reporting an AE were asked about disclosure by medical staff, effects of adverse events on their hospital course, and the quality of their hospital care.

Of the 845 AEs reported by 608 patients, only 40% were disclosed, defined as “anyone from the hospital explaining why the negative effects occurred.” The majority of the AEs were related to newly prescribed medications (40%) and surgical procedures (34%). Researchers determined that 31% of the AEs were preventable and 75% were severe. In multivariate analysis, disclosure was less likely if the AE was preventable or if patients had long-term effects from the AE. Patients with an AE were more likely to rate the quality of their hospitalization higher if there had been disclosure.

Bottom line: Disclosure of adverse events by medical personnel is low (40%) in hospitalized patients, even though disclosure of adverse events increases patients’ ratings of quality of care.

Citation: López L, Weismann JS, Schneider EC, Weingart SN, Cohen AP, Epstein AM. Disclosure of hospital adverse events and its association with patients’ ratings of the quality of care. Arch Intern Med. 2009;169(20):1888-1894.

 

Comanagement of Hip-Fracture Patients by Geriatricians Decreases Time to Surgery, LOS, and Complications

Clinical question: Does comanagement of hip-fracture patients by geriatricians and orthopedic surgeons improve short-term outcomes?

 

Background: Hip fractures in older adults are associated with considerable morbidity and mortality. A model at a single center, where hip fracture patients are comanaged by geriatricians and orthopedic surgeons, demonstrated decreased LOS, readmission rates, and mortality when compared with national data. This study compares results to a usual-care site.

Study design: Retrospective cohort study.

Setting: Community-based teaching hospital and a tertiary-care hospital in Rochester, N.Y.

Synopsis: Researchers enrolled 314 patients with hip fractures. The 193 patients in the intervention group were comanaged by geriatricians and orthopedic surgeons. The 121 patients in the usual-care group were admitted under the care of orthopedic surgeons, and hospitalists were consulted when deemed necessary. Retrospective chart reviews were performed; complications were defined a priori.

When compared with usual care, patients in the intervention group had significantly shorter times to surgery (24.1 hours vs. 37.4 hours), shorter LOS (4.6 days vs. 8.3 days), fewer complications (30.6% vs. 46.3%), including fewer postoperative infections (2.3% vs. 19.8%), cardiac complications (1.0% vs. 7.4%), cases of thromboembolism (0.5% vs. 5.0%), episodes of bleeding (0% vs. 3.3%), and episodes of hypoxia (6.7% vs. 14.1%). There was no difference in inpatient mortality or 30-day readmission rates.

Further assessment comanagement by hospitalists and comanagement by geriatricians is needed.

Bottom line: Perioperative comanagement of hip-fracture patients by geriatricians and orthopedic surgeons significantly improves short-term outcomes.

Citation: Friedman SM, Mendelson DA, Bingham KW, Kates SL. Impact of a comanaged geriatric fracture center on short-term hip fracture outcomes. Arch Intern Med. 2009;169 (18):1712-1717.

 

Niacin Is Superior to Ezetimibe in Causing Significant Regression of Carotid Intima-Media Thickness when Combined with a Statin

Clinical question: Is ezetimibe superior to niacin for reducing carotid intima-media thickness (CIMT) in patients with coronary artery disease (CAD) already on statin monotherapy?

Background: Statin montherapy significantly reduces the risk of cardiovascular events, and further lowering of this risk can be achieved by reducing the LDL, using statin intensification, or adding ezetimibe, or by raising the HDL levels by adding niacin therapy. This comparative-effectiveness trial compared the efficacy of these two approaches.

Study design: Prospective, randomized, parallel-group, open-label study.

Setting: Tertiary-care military medical center, and private tertiary-care hospital in Washington, D.C.

Synopsis: Three hundred sixty-three patients with known CAD or CAD equivalent were enrolled, and all of the patients were maintained on statin therapy with LDL <100 and HDL <50. Patients were randomized to ezetimibe 10 mg/day or niacin, starting at 500 mg at bedtime and titrated to 2 g/day. Primary endpoint was a mean change in CIMT after 14 months. Secondary endpoints were change in lipid levels, composite of major cardiovascular events, drug discontinuation, and quality of life.

The trial was terminated early after 208 patients had completed the trial. Although ezetimibe showed greater reduction of LDL, niacin showed significantly greater reduction in the progression of CIMT. Patients receiving niacin experienced fewer cardiovascular events (1% vs. 5%) but had higher rates of withdrawal (15% vs. 9%) due to flushing.

Limitations of the study are small sample size, short follow-up period, and use of CIMT as a surrogate marker for clinical endpoint.

 

Bottom line: Niacin is superior to ezetimibe in reducing CIMT and raising HDL levels and might be more efficacious in reducing cardiovascular risk.

Citation: Taylor AJ, Villines TC, Stanek EJ, et al. Extended-release niacin or ezetimibe and carotid intima-media thickness. N Engl J Med. 2009;361(22):2113-2122.

 

Pharmacist-Facilitated Hospital Discharge Program Didn’t Reduce Post-Discharge Healthcare Resource Utilization

Clinical question: Does pharmacist-facilitated hospital discharge reduce hospital readmission rates?

Background: Medication discrepancies at the time of discharge often lead to confusion, medical errors, and readmission to the hospital. Patients who are at high risk of medication errors often are on multiple medications and experience adverse drug events upon discharge.

Study design: Prospective cohort study.

Setting: Tertiary-care, academic teaching hospital in Michigan.

Synopsis: One pharmacist alternated between the resident service and hospitalist service every month. The pharmacist monitored the patients being discharged for appropriateness and accuracy of medications. The pharmacist assessed medication therapy, reconciled medications, screened for adherence concerns, counseled and educated patients, and performed post-discharge telephone follow-up.

Primary outcomes were ED visits within 72 hours and readmission rates by day 14 and day 30.

The study found high numbers of medication discrepancies in the control (33.5%) and intervention (59.6%) groups, and these discrepancies were resolved prior to discharge; however, there was no significant impact on post-discharge ED visits, or 14- and 30-day readmission rates. Post-discharge telephone calls reduced 14-day readmission rates.

Bottom line: Pharmacist-facilitated hospital discharge did not significantly reduce post-discharge ED visits or readmissions.

Citation: Walker PC, Bernstein SJ, Jones JN, et al. Impact of a pharmacist-facilitated hospital discharge program. Arch Intern Med. 2009;169(21):2003-2010.

 

Questionable Antibiotic Benefit for Patients with Acute COPD Exacerbations

Clinical question: Does the addition of antibiotics to systemic corticosteroids provide additional benefits for patients hospitalized with acute exacerbations of chronic obstructive pulmonary disease (AECOPD)?

Background: The role of antibiotics in the treatment of AECOPD is unclear, particularly in addition to systemic corticosteroids. Many of the studies demonstrating the benefit of antibiotics were conducted several decades before systemic steroids were used routinely for the treatment of AECOPD.

Study design: Randomized, double-blinded, placebo-controlled study.

Setting: Two academic teaching hospitals in the Netherlands.

Synopsis: Two hundred sixty-five acute exacerbations of COPD were enrolled in the study, and patients were randomized to a seven-day course of 200 mg/day of doxycycline or placebo. All patients received systemic corticosteroids, nebulized bronchodilator therapy, and physiotherapy. The study found that doxycycline was equivalent to placebo for the primary endpoint of clinical success on day 30; however, doxycycline was superior to placebo for secondary outcomes of clinical success, clinical cure, symptomatic improvement, microbiological success, and reducing open label antibiotic use on day 10, but not on day 30.

Because the population studied had low levels of advanced antimicrobial resistance, the findings might not be generalizable. Results suggested a difference of treatment effect between subgroups based on C-reactive protein values, but further research is needed.

Bottom line: Patients treated with doxycycline for acute exacerbation of COPD had improved clinical outcomes at day 10, but the benefits were not significant at day 30. Data are still equivocal regarding benefits of antibiotics in patients with acute exacerbations of COPD.

Citation: Daniels JM, Snijders D, de Graaff CS, Vlaspolder F, Jansen HM, Boersma WG. Antibiotics in addition to systemic corticosteroids for acute exacerbations of chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2010;181(2):150-157. TH