Writing Assignment - Report on Research Study #1

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© Managed Care & Healthcare Communications, LLC

H ospital readmission rates are an important measure of the quality and costs of healthcare. Recent estimates suggest that almost one-fifth of Medicare beneficiaries discharged

from a hospital are readmitted within 30 days, resulting in an estimat- ed annual cost of unplanned readmissions of $17.4 billion.1,2 Although factors outside of the hospital contribute to unplanned readmissions,3,4 the fact that one-quarter of readmissions occur within 30 days of dis- charge suggests that there is room for improvement in the quality of inpatient care and discharge planning. Therefore, understanding the factors associated with hospital readmission has important implica- tions for managing the provision of healthcare.

Until recently, the measurement of hospital quality has focused on how often the hospital delivers evidence-based clinical care. In June 2009, Medicare released the Hospital Care Quality Information from the Consumer Perspective (HCAHPS), a large database of information on patients’ perceptions of their hospital experiences and, in particular, their interactions with the hospital’s staff.5,6 It is unknown whether patients can “sense” from these interactions and experiences if they are getting high- quality care even if they do not have deep medical knowledge about the proper courses of treatment. Even if they can form beliefs about the appro- priateness of the treatments, it is unclear whether their responses to the HCAHPS capture these beliefs. It is also unclear whether these patient satisfaction data provide information about the overall quality of inpatient care beyond that obtained from commonly accepted clinical performance measures that also are used to assess the quality of a hospital’s care.

We sought to address these questions by studying hospital-level patient perceptions of their inpatient care and discharge planning at approximately 2500 hospitals in the United States for which we also have clinical perfor- mance measures and 30-day readmission rates for the following 3 clinical areas within the hospital: acute myocardial infarction, heart failure, and pneumonia. Specifically, we sought to determine whether hospitals where patients reported higher satisfaction with inpatient care and discharge planning were more likely to have lower 30-day readmission rates for these 3 clinical areas after adjustment for hospital clinical performance.

Methods Data Sources

Our goal was to obtain mea- sures of each hospital’s quality

Relationship Between Patient Satisfaction With Inpatient Care and Hospital Readmission Within 30 Days

William Boulding, Phd; seth W. Glickman, Md, MBA; Matthew P. Manar y, Mse;

Kevin A. schulman, Md; and Richard staelin, Phd

Objectives: To determine whether hospitals where patients report higher overall satisfaction with their interactions among the hospital and staff and specifically their experience with the discharge process are more likely to have lower 30-day readmission rates after adjustment for hospital clinical performance.

Study Design: Among patients 18 years or older, an observational analysis was conducted using Hospital Compare data on clinical performance, patient satisfaction, and 30-day risk-standardized readmission rates for acute myocardial infarction, heart failure, and pneumonia for the period July 2005 through June 2008.

Methods: A hospital-level multivariable logistic regression analysis was performed for each of 3 clinical conditions to determine the relationship between patient-reported measures of their satis- faction with the hospital stay and staff and the discharge process and 30-day readmission rates, while controlling for clinical performance.

Results: In samples ranging from 1798 hospitals for acute myocardial infarction to 2562 hospitals for pneumonia, higher hospital-level patient satis- faction scores (overall and for discharge planning) were independently associated with lower 30-day readmission rates for acute myocardial infarction (odds ratio [OR] for readmission per interquartile improvement in hospital score, 0.97; 95% confi- dence interval [CI], 0.94-0.99), heart failure (OR, 0.96; 95% CI, 0.95-0.97), and pneumonia (OR, 0.97; 95% CI, 0.96-0.99). These improvements were between 1.6 and 4.9 times higher than those for the 3 clinical performance measures.

Conclusions: Higher overall patient satisfaction and satisfaction with discharge planning are as sociated with lower 30-day risk-standardized hospital readmission rates after adjusting for clinical quality. This finding suggests that patient- centered information can have an important role in the evaluation and management of hospital performance.

(Am J Manag Care. 2011;17(1):41-48)

In this article Take-Away Points / p42 www.ajmc.com Full text and PDF

For author information and disclosures, see end of text.

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of care, as well as good indicators of the hospital’s objective clinical performance and patients’ perceptions of this perfor- mance. To do this, we used 2 major data sources.

The first major data source was the June 2009 release of the Hospital Compare database by the US Department of Health and Human Services.7 It contained a 3-year aggregat- ed mean of a hospital’s 30-day risk-standardized readmission rates for 3 clinical areas (acute myocardial infarction, heart failure, and pneumonia) for the period July 2005 through June 2008. We also used this data source to obtain the annual clinical process-of-care performance for the same 3 clinical areas for the same 3 years. We then combined these 3 years of data to form a 3-year mean for the same period for each hos- pital for each of the 3 clinical areas. We used the readmission rates to measure the hospital’s quality of care and the clinical process-of-care data to measure the hospital’s objective clini- cal performance.

The second major data source was the HCAHPS patient satisfaction survey for the period July 2007 through June 2008. We used this data source to measure patients’ percep- tions of a hospital’s clinical performance. Patients included in the satisfaction survey were 18 years or older, stayed at least 1 night in the hospital, and had a nonpsychiatric diag- nosis at discharge. The surveys covered admissions for medi- cal and surgical care and were initiated between 48 hours and 42 days after discharge. Hospital-level means were ad- justed by the Centers for Medicare & Medicaid Services to account for factors known to affect patient responses. These factors include the mode of survey delivery (eg, mail vs phone), patient mix (eg, self-reported health and time be- tween discharge and survey completion), and nonresponse percentages.

These data were supplemented by data on hospital struc- tural characteristics. These were obtained from the database of the American Hospital Association.

It should be noted that these data sources do not allow us to link individual patients to the objective clinical perfor- mance or their readmission. Instead, these should be viewed as fallible measures of a hospital’s objective quality of care (ie, readmission rates) and the performance of in-hospital care

provided to the hospital’s patients in general (ie, process-of-care and patient satisfaction scores).

Study Population We identified 4469 hospitals that reported

30-day risk-standardized readmission rates, 4488 hospitals that collected clinical perfor- mance measures, 3746 hospitals that collected HCAHPS surveys, and 6338 hospitals in the American Hospital Association database. Using

the hospital as the unit of analysis for a given clinical area (eg, acute myocardial infarction, heart failure, pneumonia), we included all hospitals that had complete information for readmission rates, clinical performance measures, patient sat- isfaction scores, and American Hospital Association hospital structural characteristics. This process resulted in a sample of 1798 hospitals for acute myocardial infarction, 2561 hospi- tals for heart failure, and 2562 hospitals for pneumonia. The clinical performance data were based on 430,982 patients with acute myocardial infarction (mean, 240 per hospital); 1,029,578 patients with heart failure (mean, 402 per hospi- tal); and 912,522 patients with pneumonia (mean, 356 per hospital).

Data Definitions There were 18 clinical performance measures in the 3 clin-

ical categories (7 for acute myocardial infarction, 4 for heart failure, and 7 for pneumonia). Using the composite scoring method by the Centers for Medicare & Medicaid Services, we calculated hospital-level scores for each clinical category by dividing the number of times the procedures in a category were followed by the total number of eligible times associated with those measures.8,9

The HCAHPS database contains patient assessments of 10 dimensions of patient care derived from 18 of 22 individ- ual survey questions. Most of the 10 dimensions of patient care were highly correlated. Based on prior work on customer satisfaction, we used 2 hospital-specific questions (“How do you rate the hospital overall?” and “Would you recommend the hospital to friends and family?”) to assess patients’ overall satisfaction with their hospital experience.10-12 We postulated that this overall patient satisfaction measure would be an ex- cellent (albeit fallible) measure of patients’ observations of the performance of the hospital’s staff and would be an im- portant predictor of readmission rates. Note that such patient observations do not require literacy in medicine but only an ability to know if the service provider “cares” and shows some concern. We also postulated that patient satisfaction with a hospital’s discharge process would be a good indicator of the hospital’s adherence to good discharge policies and predict re-

Take-Away Points Hospitals routinely use patient satisfaction surveys to assess the quality of care, although it remains unclear whether patient satisfaction data provide valid infor- mation about the medically related quality of hospital care.

n Higher patient satisfaction with inpatient care and discharge planning is as- sociated with lower 30-day readmission rates even after controlling for hospital adherence to evidence-based practice guidelines.

n Patient-centered information can have an important role in the evaluation and management of hospital performance.

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Patient Satisfaction With inpatient care and Hospital Readmission

their view of the hospital’s discharge process. We performed 3 separate logistic regression analyses in which the depen- dent measures were based on the risk-standardized hospital readmission rates for each of the 3 clinical areas.13 Specifi- cally, we converted the readmission rates to 1 or 0 to reflect whether patients were readmitted. Therefore, positive coef- ficients indicate higher readmission rates. The unit of analysis was the hospital; therefore, hospitals with more patients were weighted more heavily. The independent variables were hos- pital-level clinical performance, overall patient satisfaction, and patient satisfaction with discharge planning. We also in- cluded hospital structural characteristics to control for fixed effects that might influence the outcome measures.

To help inform the policy implications of the results, we performed sensitivity analyses to determine the change in predicted risk-standardized 30-day readmission rates associ- ated with a change in hospital score from the 25th percentile to the 75th percentile for the overall patient satisfaction score and for the patient satisfaction with discharge planning score, while keeping the hospital-level clinical composite score fixed. Conversely, we also examined the effect of the same in- terquartile change in hospital-level clinical composite score, while keeping the patient satisfaction measures fixed.

Finally, we calculated pairwise Pearson product moment correlation coefficients between the overall patient satisfac- tion score and the 8 other HCAHPS-reported dimensions of quality. This was to assess which dimensions were most associ- ated with the patients’ overall satisfaction with the hospital’s quality of care.

We used JMP version 7.0.2 (SAS Institute Inc, Cary, North Carolina) for all statistical analyses. P <.05 was consid- ered statistically significant.

Results Table 1 gives the characteristics of the study hospitals. Al-

though hospitals in the sample tended to be larger and bet- ter resourced than hospitals in the total sample of American Hospital Association acute care hospitals, the 3 samples rep- resent a broad cross-section of US hospitals. Table 2 gives the distributions of the variables of interest, including the scores for overall patient satisfaction and patient satisfaction with discharge planning, the clinical composite score, and 30-day risk-standardized readmission rates. There was considerable variability in patient-reported measures and clinical measures across hospitals. Note that the mean 30-day risk-standardized readmission rates are approximately 20% for all 3 clinical areas.

Table 3 gives the correlations among the variables. The 2 hospital-level patient-reported measures were not highly correlated with the hospitals’ clinical performance measures.

admission rates for each of the clinical areas. We captured these perceptions using the following 2 questions from the HCAHPS: “During this hospital stay, did doctors, nurses or other hospital staff talk with you about whether you would have the help you needed when you left the hospital?” and “During this hospital stay, did you get information in writ- ing about what symptoms or health problems to look out for after you left the hospital?”

We transformed the HCAHPS information on each hospital into overall satisfaction and discharge satisfaction scores as follows. The HCAHPS database reported the total number of patients surveyed and the percentage of patients who responded to the different levels of the particular ques- tion. For the 2 overall satisfaction questions, the database provided 3 levels (ie, a satisfaction rating of 1-6 [low], 7-8 [medium], or 9-10 [high]). We multiplied the percentage of patients who responded to a given level by the numerical values of 0, 0.5, and 1 for low, medium, and high, respec- tively, to obtain scores between 0 and 1, where 1 indicates that all patients gave a high response and 0 indicates that all patients gave a low response to the particular question. The hospital-level overall patient satisfaction score is the mean of these 2 numerical values. For the 2 discharge questions, we converted the reported percentages into numerical val- ues by assigning the percentage of “no” responses the value of 0 and the percentage of “yes” responses the value of 1 and averaging the 2 questions across respondents. Note that the Hospital Compare documentation does not provide patient satisfaction information for specific diagnosis related groups but instead reflects patient responses for several other units, as well as the 3 units we analyze. Therefore, the patient sat- isfaction scores used for analyzing readmission rates for acute myocardial infarction, heart failure, and pneumonia are the same for a given hospital.

The hospital-level 30-day risk-standardized readmission rates and sample sizes were obtained directly from the Hospi- tal Compare database, and our measures of hospital structur- al characteristics came directly from the American Hospital Association database. These measures included the number of beds, medical school affiliation, geographic region, and the presence of adult interventional cardiac catheterization facility, medical, and surgical intensive care units.

Statistical Analysis Our primary objectives were to determine the association

of hospital-level 30-day risk-standardized readmission rates with (1) hospital-level clinical performance as measured by the guideline adherence score in each clinical area and (2) hospital-level overall perception among patients of their hospital stay and interactions with the hospital staff and

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n Table 1. Characteristics of the Study Hospitals

Study Hospitals

Characteristic

Acute Myocardial Infarction (n = 1798)

Heart Failure

(n = 2561)

Pneumonia (n = 2562)

All AHA Acute Care Hospitals

(n = 4105)

No. of beds, median (interquartile range) 208 (122-333) 149 (69-276) 148 (69-275) 107 (42-230)

Interventional cardiac catheterization, No. (%) 1027 (57.1) 1046 (40.8) 1042 (40.7) 1314 (32.0)

Medical school affiliation, No. (%) 666 (37.0) 732 (28.6) 734 (28.6) 1026 (25.0)

Medical or surgical intensive care unit, No. (%) 1702 (94.7) 2219 (86.6) 2210 (86.3) 3038 (74.0)

US geographic region, No. (%)

New england 133 (7.4) 150 (5.9) 152 (5.9) 184 (4.5)

Mid-Atlantic 234 (13.0) 255 (10.0) 256 (10.0) 332 (8.1)

south Atlantic 330 (18.4) 424 (16.6) 418 (16.3) 579 (14.1)

east North Central 285 (15.9) 426 (16.6) 409 (16.0) 652 (15.9)

east south Central 132 (7.3) 224 (8.7) 225 (8.8) 349 (8.5)

West North Central 147 (8.2) 258 (10.1) 272 (10.6) 606 (14.8)

West south Central 224 (12.5) 372 (14.5) 367 (14.3) 644 (15.7)

Mountain 86 (4.8) 145 (5.7) 156 (6.1) 308 (7.5)

Pacific 227 (12.6) 307 (12.0) 307 (12.0) 451 (11.0)

AhA indicates American hospital Association.

n Table 2. Distribution of Hospital-Level Patient-Reported Measures, Clinical Composite Scores, and 30-Day Risk-Standardized Readmission Rates

Percentile

Variable 5th 25th Median 75th 95th

Patient-reported measures

Overall patient satisfaction

Acute myocardial infarction 66.3 74.5 78.5 82.3 87.0

heart failure 66.4 75.0 78.8 82.8 88.3

Pneumonia 66.5 75.0 79.0 83.0 88.5

Patient satisfaction with discharge planning

Acute myocardial infarction 71.0 77.0 80.0 83.0 87.0

heart failure 70.0 77.0 80.0 83.0 88.0

Pneumonia 70.0 77.0 80.0 83.0 88.0

Clinical composite score

Acute myocardial infarction 82.7 91.1 94.4 96.5 98.5

heart failure 57.1 76.0 84.1 89.7 96.0

Pneumonia 76.1 84.0 88.2 91.4 95.1

30-Day risk-standardized readmission rate

Acute myocardial infarction 17.8 19.0 19.9 20.7 22.2

heart failure 21.3 23.1 24.4 25.7 28.1

Pneumonia 15.6 17.0 18.0 19.2 21.2

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Overall patient satisfaction and patient satisfaction with dis- charge planning were negatively and significantly correlated with higher 30-day risk-standardized readmission rates for all 3 clinical conditions. In addition, all 3 clinical composite scores were negatively and significantly correlated with high- er 30-day risk-standardized readmission rates, although these correlations are smaller than those associated with the patient satisfaction scores.

Table 4 gives the results of the multivariable logistic re- gression analyses for the variables of interest. All 3 clinical performance measures were negatively associated with higher 30-day risk-standardized readmission rates, although the acute myocardial infarction and heart failure measures were not statistically significant (P = .16 and P = .06, respectively). Higher overall patient satisfaction scores also were associated with lower 30-day risk-standardized readmission rates for all 3 clinical conditions. In this case, all 3 measures were highly statistically significant (P <.001). Finally, scores for patient satisfaction with discharge planning were associated with low- er 30-day risk-standardized readmission rates for all 3 clinical areas and were statistically significant for heart failure and for pneumonia (P <.001 and P = .02, respectively).

The Figure shows that the odds of 30-day risk-standardized readmission were associated with interquartile improvements in hospitals’ patient total satisfaction scores (ie, overall patient satisfaction and patient satisfaction with discharge planning), while holding the clinical composite scores fixed, and vice versa. Interquartile improvements in patient total satisfaction scores were associated with significantly lower predicted 30-day

risk-standardized readmission rates for acute myocardial infarc- tion (odds ratio [OR] = 0.97; 95% confidence interval [CI], 0.94-0.99), heart failure (OR = 0.96; 95% CI, 0.95-0.97), and pneumonia (OR = 0.97; 95% CI, 0.96-0.99). Also shown are the interquartile improvements in the 3 clinical performance measures. The improvements in 30-day risk-standardized re- admission rates associated with interquartile improvements in the patient total satisfaction scores for heart failure, acute myocardial infarction, and pneumonia were 4.9, 2.2, and 1.6 times higher, respectively, than those associated with inter- quartile improvements in the same 3 clinical composite scores.

Table 5 gives the correlations of the overall patient sat- isfaction measure with each HCAHPS question category. Quality of communication by nurses had the strongest cor- relation with overall patient satisfaction, followed by several other measures that capture the patient’s interaction with the hospital staff. Patient satisfaction with discharge planning was seventh of the 8 questions in terms of correlation, indicating that it captured a different dimension from that captured by overall patient satisfaction. Also low in terms of correlation with overall patient satisfaction were the 2 questions con- cerning the hospital facilities (ie, cleanliness and noise level), again highlighting that overall patient satisfaction seems to be capturing the patients’ interactions with the hospital staff.

disCussioN A substantial proportion of Medicare beneficiaries expe-

rience an unplanned hospital readmission within 30 days of

n Table 3. Pairwise Correlations Among Variablesa

Correlation Coefficient

Variable

Patient Satisfaction With

Discharge Planning

Clinical Composite

Score

30-Day Risk- Standardized

Readmission Rate

Acute myocardial infarction

overall patient satisfaction 0.613 0.252 -0.199

Patient satisfaction with discharge planning — 0.211 -0.167

Clinical composite score — — -0.098

Heart failure

overall patient satisfaction 0.604 0.110 -0.203

Patient satisfaction with discharge planning — 0.126 -0.188

Clinical composite score — — -0.090

Pneumonia

overall patient satisfaction 0.599 0.211 -0.159

Patient satisfaction with discharge planning — 0.228 -0.129

Clinical composite score — — -0.105 aAll correlations are statistically significant at P <.001.

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discharge. In this study, we found that patients’ stated overall satisfaction score and their perception of the hospital’s dis- charge process were significantly and negatively correlated with the hospital’s 30-day readmission rates in the 3 clini- cal areas studied. Moreover, these 2 patient-related measures were more predictive than the objective clinical performance measures often used to assess the quality of hospital care. Al- though the key drivers of hospital readmission are complex, our findings suggest that patients’ perspectives on inpatient care and discharge planning provide important insights into hospital performance with respect to quality. Moreover, be- cause the overall satisfaction score is most highly correlated with factors associated with the patients’ interaction with the

hospital staff, our findings are consistent with the observation by the Institute of Medicine that high-quality care is “patient centered” and responsive to patients’ preferences, needs, and values.14 More generally, given the association between these patient perceptions and better outcomes, our findings suggest that patient-centered information can be used to assess the degree to which patients will be more likely to experience bet- ter health outcomes, at least as measured by hospital readmis- sion rates.

Our findings support the use of patient-reported informa- tion to complement the more used and more objective clinical measures when assessing the quality of patient care for a given hospital. These patient-level measures not only are more pre-

n Table 4. Multivariable Predictors of 30-Day Risk-Standardized Readmission Rates

Variable

Coefficient Estimate (SE)

c2 Statistic

P

Acute myocardial infarction

overall patient satisfaction -0.268 (0.084) 10.20 .001 Patient satisfaction with discharge planning -0.189 (0.113) 2.80 .09 Clinical composite score -0.184 (0.131) 1.98 .16 Heart failure

overall patient satisfaction -0.321 (0.048) 45.03 <.001 Patient satisfaction with discharge planning -0.284 (0.062) 20.75 <.001 Clinical composite score -0.051 (0.027) 3.54 .06 Pneumonia

overall patient satisfaction -0.232 (0.056) 17.11 <.001 Patient satisfaction with discharge planning -0.169 (0.072) 5.56 .02 Clinical composite score -0.150 (0.053) 7.90 .005

n Figure. Association Between Interquartile Improvements in Hospital-Level Patient Total Satisfaction Scores and 30-Day Risk-Standardized Readmission Rates

0.968 0.959 0.971

0.990 0.993 0.989

Acute Myocardial Infarction Heart Failure Pneumonia

Clinical composite

score

Patient total satisfaction

score

0.91 0.95 1.00 1.04 0.91 0.95 1.00

Odds of 30-Day Risk-Standardized Readmission

1.04 0.91 0.95 1.00 1.04

shown are the odds ratios for 30-day risk-standardized hospital readmission associated with 1-quartile improvements in hospital-level patient total satisfaction scores for acute myocardial infarction, heart failure, and pneumonia.

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dictive and offer insights into a different dimension of hospi- tal activities than those obtained from clinical performance measures alone, but they also seem to be clinically important in terms of providing a way to increase the quality of care. For example, using our model estimates we would predict that, if a hospital increased its patient total satisfaction score from the 25th percentile to the 75th percentile, this increase would be associated with decreases in 30-day readmission of 2.6% for acute myocardial infarction, 3.1% for heart failure, and 2.3% for pneumonia. If these reductions were obtained for our total sample of patients, this would have been associated with a reduction of more than 14,000 readmissions.

Our finding that good communication is associated with higher patient satisfaction is consistent with previous stud- ies15-17 that found a positive association between effective provider–patient communication and health outcomes. It also is compatible with a recent study18 by our author group that used more fine-grained measures of patient satisfaction. Specifically, the study found that overall satisfaction was best predicted by patients’ perceptions of the skill and responsive- ness of nurses and physicians, followed by issues concerning pain and communication with the staff about the patients’ concerns and emotional health. Again, the study found that factors associated with the physical plant had a much smaller influence on overall patient satisfaction. Consequently, pa- tients seem to differentiate between the technical (ie, medi- cal) and nontechnical (ie, aesthetic) aspects of medical care. This leads us to believe that patient satisfaction is less about trying to make patients “happy” (eg, improving the food or the decor of the room) and is more about increasing the qual- ity of their interactions with hospital personnel, especially nurses and physicians.

Finally, we note that hospitals have devoted substantial resources to managing the current core set of clinical perfor- mance measures.19 Despite dramatic improvements in clinical process performance for heart failure, there has been virtually

no reduction in these readmission rates or costs.20 Our findings confirm the lack of association between heart failure clinical measures and readmission rates.21,22 Conversely, we found that patient-reported measures were highly associated with 30-day readmission rates. Therefore, patient perceptions about hos- pital care in general and discharge planning specifically may provide an important new tool for measuring the quality of transitions of care.

Our study has several limitations. First, because our data are cross-sectional versus longitudinal, we were only able to make associational and not causal inferences about the relationship between patient satisfaction and hospital read- mission. Moreover, patient-reported information is likely a surrogate measure for specific hospital characteristics and practices (eg, quality of staff and the use of clinical protocols) that determine quality of care. More research is needed to evaluate these links.

Second, it is also possible that some patients actually were readmitted before they filled out the survey. Such patients may have used their readmission as a signal of the quality of the hospital’s performance. In any case, a key insight of this study is that patients notice and can assess hospital experi- ences that otherwise go unmeasured.

Third, our analysis is limited in that it does not include factors such as patient compliance and access to primary care, which are known to influence the likelihood of hospital read- mission.23 Moreover, our study only focused on short-term (ie, 30 day) readmission rates and provides little information on long-term care.

Fourth, because our focus was on determining whether the Centers for Medicare & Medicaid Services measures of clinical performance and patient satisfaction are useful indicators of the overall quality of hospital care, the unit of analysis was the hospi- tal and not the patient. This approach precluded the possibility of patient-level analyses that might provide insight into specific dimensions of the patient experience and related outcomes.

n Table 5. Pairwise Correlations of HCAHPS-Reported Dimensions of Quality and Overall Patient Satisfaction

Variable Correlation Coefficient

how often did nurses communicate well with patients? 0.845

how often was patient’s pain well controlled? 0.805

how often did patients receive help quickly from hospital staff? 0.776

how often did staff explain about medicines before giving them to patients? 0.740

how often did doctors communicate well with patients? 0.695

how often were the patients’ rooms and bathrooms kept clean? 0.675

Patient satisfaction with discharge planning 0.638

how often was the area around patients’ rooms kept quiet at night? 0.611

hCAhPs indicates hospital Care Quality information from the Consumer Perspective.

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Fifth, one could infer that the association between patient satisfaction and outcomes can be explained by healthier pa- tients’ being more likely to report being satisfied.24 However, this is unlikely because the Centers for Medicare & Medicaid Services corrected for this before releasing their data.

Sixth, the period for the satisfaction data (2008) is not en- tirely contemporaneous with that for the clinical data and the outcome data (2005-2008). This was owing to pragmatic rea- sons associated with the availability of data. However, when we compared the 2009 satisfaction measures with the 2008 mea- sures, we found no time trend and a correlation of 0.86 between the 2 yearly hospital-level measures, indicating that they were stable (reliable) and a good proxy for the 2 prior years.

In conclusion, higher hospital-level overall patient satis- faction and patient satisfaction with discharge planning are associated with lower 30-day risk-standardized readmission rates after adjustment for clinical quality. Although patients may have little insight into evidence-based medicine, they can assess other aspects of care that are associated with bet- ter health outcomes. Therefore, patient-reported information about hospital performance can have an important role in the evaluation and management of hospital quality.

Author Affiliations: From The Fuqua School of Business (WB, MPM, RS), the Duke Clinical Research Institute (SWG, KAS), and the School of Medicine (SWG, KAS), Duke University, Durham, NC; and the Depart- ment of Emergency Medicine (SWG), University of North Carolina, Chapel Hill, NC.

Funding Source: The authors report no external funding for this study. Author Disclosures: Dr Glickman reports receiving support through a

Physician Faculty Scholar Award from the Robert Wood Johnson Foundation. The other authors (WB, MPM, KAS, RS) report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (WB, SWG, KAS, RS); acquisition of data (MPM); analysis and interpretation of data (WB, SWG, MPM, RS); drafting of the manuscript (SWG, MPM, RS); critical revision of the manuscript for important intellectual content (WB, SWG, KAS, RS); statistical analysis (WB, MPM, RS); administrative, technical, and logistic support (WB, KAS, RS); and supervision (WB).

Address correspondence to: Seth W. Glickman, MD, MBA, Department of Emergency Medicine, University of North Carolina at Chapel Hill, 170 Manning Dr, CB #7594, Chapel Hill, NC 27599. E-mail: seth_glickman@ med.unc.edu.

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