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.

[1]  Harlan M Krumholz,et al.  Research in action: using positive deviance to improve quality of health care , 2009, Implementation science : IS.

[2]  Medicine in the era of outcomes measurement. , 2009, Circulation. Cardiovascular quality and outcomes.

[3]  Sharon-Lise T. Normand,et al.  An Administrative Claims Measure Suitable for Profiling Hospital Performance on the Basis of 30-Day All-Cause Readmission Rates Among Patients With Heart Failure , 2008, Circulation. Cardiovascular quality and outcomes.

[4]  Harlan M Krumholz,et al.  Statistical models and patient predictors of readmission for heart failure: a systematic review. , 2008, Archives of internal medicine.

[5]  S. Normand,et al.  Measuring performance for treating heart attacks and heart failure: the case for outcomes measurement. , 2007, Health affairs.

[6]  S. Normand,et al.  An Administrative Claims Model Suitable for Profiling Hospital Performance Based on 30-Day Mortality Rates Among Patients With an Acute Myocardial Infarction , 2006, Circulation.

[7]  Harlan M Krumholz,et al.  An Administrative Claims Model Suitable for Profiling Hospital Performance Based on 30-Day Mortality Rates Among Patients With Heart Failure , 2006, Circulation.

[8]  S. Chinn,et al.  Intraclass correlation coefficient and outcome prevalence are associated in clustered binary data. , 2005, Journal of clinical epidemiology.

[9]  Haya R Rubin,et al.  Comprehensive discharge planning with postdischarge support for older patients with congestive heart failure: a meta-analysis. , 2004, JAMA.

[10]  H. Krumholz,et al.  Quality of Care of Medicare Beneficiaries with Acute Myocardial Infarction: Who Is Included in Quality Improvement Measurement? , 2003, Journal of the American Geriatrics Society.

[11]  Harlan M Krumholz,et al.  Randomized trial of an education and support intervention to prevent readmission of patients with heart failure. , 2002, Journal of the American College of Cardiology.

[12]  M. Sandra Wood,et al.  Health care financing administration , 2000 .

[13]  J. Stoker,et al.  The Department of Health and Human Services. , 1999, Home healthcare nurse.

[14]  K. Kupka,et al.  International classification of diseases: ninth revision. , 1978, WHO chronicle.