Zhenqiu Lin

Patterns of Hospital Performance in Acute Myocardial Infarction and Heart Failure 30-Day Mortality and Readmission

Background—In 2009, the Centers for Medicare & Medicaid Services is publicly reporting hospital-level risk-standardized 30-day mortality and readmission rates after acute myocardial infarction (AMI) and heart failure (HF). We provide patterns of hospital performance, based on these measures. Methods and Results—We calculated the 30-day mortality and readmission rates for all Medicare fee-for-service beneficiaries ages 65 years or older with a primary diagnosis of AMI or HF, discharged between July 2005 and June 2008. We compared weighted risk-standardized mortality and readmission rates across Hospital Referral Regions and hospital structural characteristics. The median 30-day mortality rate was 16.6% for AMI (range, 10.9% to 24.9%; 25th to 75th percentile, 15.8% to 17.4%; 10th to 90th percentile, 14.7% to 18.4%) and 11.1% for HF (range, 6.6% to 19.8%; 25th to 75th percentile, 10.3% to 12.0%; 10th to 90th percentile, 9.4% to 13.1%). The median 30-day readmission rate was 19.9% for AMI (range, 15.3% to 29.4%; 25th to 75th percentile, 19.5% to 20.4%; 10th to 90th percentile, 18.8% to 21.1%) and 24.4% for HF (range, 15.9% to 34.4%; 25th to 75th percentile, 23.4% to 25.6%; 10th to 90th percentile, 22.3% to 27.0%). We observed geographic differences in performance across the country. Although there were some differences in average performance by hospital characteristics, there were high and low hospital performers among all types of hospitals. Conclusions—In a recent 3-year period, 30-day risk-standardized mortality rates for AMI and HF varied among hospitals and across the country. The readmission rates were particularly high.

An Administrative Claims Measure Suitable for Profiling Hospital Performance on the Basis of 30-Day All-Cause Readmission Rates Among Patients With Heart Failure

Background—Readmission soon after hospital discharge is an expensive and often preventable event for patients with heart failure. We present a model approved by the National Quality Forum for the purpose of public reporting of hospital-level readmission rates by the Centers for Medicare & Medicaid Services. Methods and Results—We developed a hierarchical logistic regression model to calculate hospital risk-standardized 30-day all-cause readmission rates for patients hospitalized with heart failure. The model was derived with the use of Medicare claims data for a 2004 cohort and validated with the use of claims and medical record data. The unadjusted readmission rate was 23.6%. The final model included 37 variables, had discrimination ranging from 15% observed 30-day readmission rate in the lowest predictive decile to 37% in the upper decile, and had a c statistic of 0.60. The 25th and 75th percentiles of the risk-standardized readmission rates across 4669 hospitals were 23.1% and 24.0%, with 5th and 95th percentiles of 22.2% and 25.1%, respectively. The odds of all-cause readmission for a hospital 1 standard deviation above average was 1.30 times that of a hospital 1 standard deviation below average. State-level adjusted readmission rates developed with the use of the claims model are similar to rates produced for the same cohort with the use of a medical record model (correlation, 0.97; median difference, 0.06 percentage points). Conclusions—This claims-based model of hospital risk-standardized readmission rates for heart failure patients produces estimates that may serve as surrogates for those derived from a medical record model.

Patients With Depressive Symptoms Have Lower Health Status Benefits After Coronary Artery Bypass Surgery

Background—Depression is an established independent prognostic factor for mortality, readmission, and cardiac events after CABG surgery. However, limited data exist on whether depression influences functional outcomes after CABG. Methods and Results—We followed 963 patients who underwent first CABG between February 1999 and February 2001. At baseline and at 6 months after CABG, we interviewed patients to assess depressive symptoms using the Geriatric Depression Scale (GDS) and physical function using the Short Form-36 Physical Component Scale (PCS). The patient’s physical function was considered improved if the PCS score increased ≥5 points at 6 months. Patients with high GDS scores were younger, were more often female, and had worse physical function and higher comorbidity than patients with low GDS scores. Rates of improvement in physical function were 60.1% for a GDS score <5 (below 75th percentile), 49.8% for a GDS score between 5 and 9 (75th to 90th percentile), and 39.7% for a GDS score ≥10 (≥90th percentile; P=0.002 for the trend). Depressive symptoms remained a significant independent predictor of lack of functional improvement after adjustment for severity of coronary artery disease, angina class, baseline PCS score, and medical history. A GDS score ≥10 was a stronger inverse risk factor for functional improvement after CABG than such traditional measures of disease severity as previous myocardial infarction, heart failure on admission, history of diabetes, and left ventricular ejection fraction. Conclusions—Higher levels of depressive symptoms at the time of CABG are a strong risk factor for lack of functional benefits 6 months after CABG.

Relationship Between Hospital Readmission and Mortality Rates for Patients Hospitalized With Acute Myocardial Infarction, Heart Failure, or Pneumonia

IMPORTANCE The Centers for Medicare & Medicaid Services publicly reports hospital 30-day, all-cause, risk-standardized mortality rates (RSMRs) and 30-day, all-cause, risk-standardized readmission rates (RSRRs) for acute myocardial infarction, heart failure, and pneumonia. The evaluation of hospital performance as measured by RSMRs and RSRRs has not been well characterized. OBJECTIVE To determine the relationship between hospital RSMRs and RSRRs overall and within subgroups defined by hospital characteristics. DESIGN, SETTING, AND PARTICIPANTS We studied Medicare fee-for-service beneficiaries discharged with acute myocardial infarction, heart failure, or pneumonia between July 1, 2005, and June 30, 2008 (4506 hospitals for acute myocardial infarction, 4767 hospitals for heart failure, and 4811 hospitals for pneumonia). We quantified the correlation between hospital RSMRs and RSRRs using weighted linear correlation; evaluated correlations in groups defined by hospital characteristics; and determined the proportion of hospitals with better and worse performance on both measures. MAIN OUTCOME MEASURES Hospital 30-day RSMRs and RSRRs. RESULTS Mean RSMRs and RSRRs, respectively, were 16.60% and 19.94% for acute myocardial infarction, 11.17% and 24.56% for heart failure, and 11.64% and 18.22% for pneumonia. The correlations between RSMRs and RSRRs were 0.03 (95% CI, -0.002 to 0.06) for acute myocardial infarction, -0.17 (95% CI, -0.20 to -0.14) for heart failure, and 0.002 (95% CI, -0.03 to 0.03) for pneumonia. The results were similar for subgroups defined by hospital characteristics. Although there was a significant negative linear relationship between RSMRs and RSRRs for heart failure, the shared variance between them was only 2.9% (r2 = 0.029), with the correlation most prominent for hospitals with RSMR <11%. CONCLUSION AND RELEVANCE Risk-standardized mortality rates and readmission rates were not associated for patients admitted with an acute myocardial infarction or pneumonia and were only weakly associated, within a certain range, for patients admitted with heart failure.

An Administrative Claims Measure Suitable for Profiling Hospital Performance Based on 30-Day All-Cause Readmission Rates Among Patients With Acute Myocardial Infarction

Background— National attention has increasingly focused on readmission as a target for quality improvement. We present the development and validation of a model approved by the National Quality Forum and used by the Centers for Medicare & Medicaid Services for hospital-level public reporting of risk-standardized readmission rates for patients discharged from the hospital after an acute myocardial infarction. Methods and Results— We developed a hierarchical logistic regression model to calculate hospital risk-standardized 30-day all-cause readmission rates for patients hospitalized with acute myocardial infarction. The model was derived using Medicare claims data for a 2006 cohort and validated using claims and medical record data. The unadjusted readmission rate was 18.9%. The final model included 31 variables and had discrimination ranging from 8% observed 30-day readmission rate in the lowest predictive decile to 32% in the highest decile and a C statistic of 0.63. The 25th and 75th percentiles of the risk-standardized readmission rates across 3890 hospitals were 18.6% and 19.1%, with fifth and 95th percentiles of 18.0% and 19.9%, respectively. The odds of all-cause readmission for a hospital 1 SD above average were 1.35 times that of a hospital 1 SD below average. Hospital-level adjusted readmission rates developed using the claims model were similar to rates produced for the same cohort using a medical record model (correlation, 0.98; median difference, 0.02 percentage points). Conclusions— This claims-based model of hospital risk-standardized readmission rates for patients with acute myocardial infarction produces estimates that are excellent surrogates for those produced from a medical record model.

National Patterns of Risk-Standardized Mortality and Readmission for Acute Myocardial Infarction and Heart Failure: Update on Publicly Reported Outcomes Measures Based on the 2010 Release

Background—Patient outcomes provide a critical perspective on quality of care. The Centers for Medicare and Medicaid Services (CMS) is publicly reporting hospital 30-day risk-standardized mortality rates (RSMRs) and risk-standardized readmission rates (RSRRs) for patients hospitalized with acute myocardial infarction (AMI) and heart failure (HF). We provide a national perspective on hospital performance for the 2010 release of these measures. Methods and Results—The hospital RSMRs and RSRRs are calculated from Medicare claims data for fee-for-service Medicare beneficiaries, 65 years or older, hospitalized with AMI or HF between July 1, 2006, and June 30, 2009. The rates are calculated using hierarchical logistic modeling to account for patient clustering, and are risk-adjusted for age, sex, and patient comorbidities. The median RSMR for AMI was 16.0% and for HF was 10.8%. Both measures had a wide range of hospital performance with an absolute 5.2% difference between hospitals in the 5th versus 95th percentile for AMI and 5.0% for HF. The median RSRR for AMI was 19.9% and for HF was 24.5% (3.9% range for 5th to 95th percentile for AMI, 6.7% for HF). Distinct regional patterns were evident for both measures and both conditions. Conclusions—High RSRRs persist for AMI and HF and clinically meaningful variation exists for RSMRs and RSRRs for both conditions. Our results suggest continued opportunities for improvement in patient outcomes for HF and AMI.

Sex Differences in Health Status After Coronary Artery Bypass Surgery

Background—Although previous studies have shown functional improvements in patients who undergo coronary artery bypass graft (CABG) surgery, data are conflicting on whether the gains achieved by women are similar to or less than those achieved by men. Methods and Results—We compared physical and psychological functional gains and readmission rates between 777 men and 295 women who underwent first CABG consecutively between February 1999 and February 2001. Physical function and mental health were measured by means of the Short Form 36-Item Health Survey (SF-36). At 6 months, both men and women showed, on average, a significant improvement in physical function and mental health, but men improved significantly more than women. After adjustment for baseline characteristics, the mean score improvement in women was half that of men for physical function (7.3 versus 14.0, P =0.0002) and 25% less than that of men for mental health (−3.0 versus 8.9, P =0.026). The absolute rates of adverse outcomes, such as hospital readmission, worsening functional status, and worsening mental health, were significantly higher in women (32.6%, 25.7%, and 17.5%, respectively) than in men (21.2%, 11.1%, and 12.6%, respectively) and remained significantly different in multivariable analysis. Conclusions—CABG surgery is associated with lower functional gains and higher readmission rates in women compared with men 6 months after operation.

Development, validation, and results of a measure of 30-day readmission following hospitalization for pneumonia

BACKGROUND Readmission following hospital discharge has become an important target of quality improvement. OBJECTIVE To describe the development, validation, and results of a risk-standardized measure of hospital readmission rates among elderly patients with pneumonia employed in federal quality measurement and efficiency initiatives. DESIGN A retrospective cohort study using hospital and outpatient Medicare claims from 2005 and 2006. SETTING A total of 4675 hospitals in the United States. PATIENTS Medicare beneficiaries aged >65 years with a principal discharge diagnosis of pneumonia. INTERVENTION None. MEASUREMENTS Hospital-specific, risk-standardized 30-day readmission rates calculated as the ratio of predicted-to-expected readmissions, multiplied by the national unadjusted rate. Comparison of the areas under the receiver operating curve (ROC) and measurement of correlation coefficient in development and validation samples. RESULTS The development sample consisted of 226,545 hospitalizations at 4675 hospitals, with an overall unadjusted 30-day readmission rate of 17.4%. The median risk-standardized hospital readmission rate was 17.3%, and the odds of readmission for a hospital one standard deviation above average was 1.4 times that of a hospital one standard deviation below average. Performance of the medical record and administrative models was similar (areas under the ROC curve 0.59 and 0.63, respectively) and the correlation coefficient of estimated state-specific standardized readmission rates from the administrative and medical record models was 0.96. CONCLUSIONS Rehospitalization within 30 days of treatment for pneumonia is common, and rates vary across hospitals. A risk-standardized measure of hospital readmission rates derived from administrative claims has similar performance characteristics to one based on medical record review.

Is same-hospital readmission rate a good surrogate for all-hospital readmission rate?

Background:The Centers for Medicare & Medicaid Services (CMS) readmission measure is based on all-cause readmissions to any hospital within 30 days of discharge. Whether a measure based on same-hospital readmission, an outcome that is easier for hospitals and some systems to track, could serve as a proxy for the all-hospital measure is not known. Objectives:Evaluate whether same-hospital readmission rate is a good surrogate for all-hospital readmission rate. Research Design:The study population was derived from the Medicare inpatient, outpatient, and carrier (physician) Standard Analytic Files. Thirty-day risk-standardized readmission rates (RSRRs) for heart failure (HF) for both all-hospital readmission and same-hospital readmission were assessed by using hierarchical logistic regression models. Subjects:The sample consisted of 501,234 hospitalizations in 4674 hospitals with at least 1 hospitalization. Measures:Thirty-day readmission was defined as occurrence of at least 1 hospitalization in any US acute care hospital for any cause within 30 days of discharge after an index hospitalization. Same-hospital readmission was considered if the patient was admitted to the hospital that produced the original discharge within 30 days. Results:Overall, 80.9% of all HF readmissions occurred in the same- hospital, whereas 19.1% of readmissions occurred in a different hospital. The mean difference between all- versus same-hospital RSRR was 4.7 ± 1.0%, ranging from 0.9% to 10.5% across these hospitals with 25th, 50th, and 75th percentiles of 4.1%, 4.7%, and 5.2%, respectively, and was variable across the range of average RSRR. Conclusion:Same-hospital readmission rate is an unreliable and biased indicator of all-hospital readmission rate with limited value as a benchmark for quality of care processes.

The performance of US hospitals as reflected in risk-standardized 30-day mortality and readmission rates for medicare beneficiaries with pneumonia†‡

BACKGROUND Pneumonia is a leading cause of hospitalization and death in the elderly, and remains the subject of both local and national quality improvement efforts. OBJECTIVE To describe patterns of hospital and regional performance in the outcomes of elderly patients with pneumonia. DESIGN Cross-sectional study using hospital and outpatient Medicare claims between 2006 and 2009. SETTING A total of 4,813 nonfederal acute care hospitals in the United States and its organized territories. PATIENTS Hospitalized fee-for-service Medicare beneficiaries age 65 years and older who received a principal diagnosis of pneumonia. INTERVENTION None. MEASUREMENTS Hospital and regional level risk-standardized 30-day mortality and readmission rates. RESULTS Of the 1,118,583 patients included in the mortality analysis 129,444 (11.6%) died within 30 days of hospital admission. The median (Q1, Q3) hospital 30-day risk-standardized mortality rate for patients with pneumonia was 11.1% (10.0%, 12.3%), and despite controlling for differences in case mix, ranged from 6.7% to 20.9%. Among the 1,161,817 patients included in the readmission analysis 212,638 (18.3%) were readmitted within 30 days of hospital discharge. The median (Q1, Q3) 30-day risk-standardized readmission rate was 18.2% (17.2%, 19.2%) and ranged from 13.6% to 26.7%. Risk-standardized mortality rates varied across hospital referral regions from a high of 14.9% to a low of 8.7%. Risk-standardized readmission rates varied across hospital referral regions from a high of 22.2% to a low of 15%. CONCLUSIONS Risk-standardized 30-day mortality and, to a lesser extent, readmission rates for patients with pneumonia vary substantially across hospitals and regions and may present opportunities for quality improvement, especially at low performing institutions and areas.