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Original Research |

Comparison of Hospital Risk-Standardized Mortality Rates Calculated by Using In-Hospital and 30-Day Models: An Observational Study With Implications for Hospital Profiling

Elizabeth E. Drye, MD, SM; Sharon-Lise T. Normand, PhD; Yun Wang, PhD; Joseph S. Ross, MD, MHS; Geoffrey C. Schreiner, BS; Lein Han, PhD; Michael Rapp, MD, JD; and Harlan M. Krumholz, MD, SM
[+] Article and Author Information

From Yale University School of Medicine, Yale-New Haven Hospital Center for Outcomes Research and Evaluation, and Yale University, New Haven, Connecticut; Harvard Medical School and Harvard School of Public Health, Boston, Massachusetts; Dartmouth Medical School, Hanover, New Hampshire; Centers for Medicare & Medicaid Services, Baltimore, Maryland; and George Washington University School of Medicine and Health Sciences, Washington, DC.

Disclaimer: The content of this publication does not necessarily reflect the views or policies of the U.S. Department of Health and Human Services, the National Heart, Lung, And Blood Institute, or the National Institutes of Health, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. government.

Acknowledgment: The authors thank Shantal Savage for her assistance with the preparation of this manuscript.

Financial Support: By the CMS (contract HHSM-500-2008-0025I, task order T0001) and the National Heart, Lung, and Blood Institute (award U01-HL105270-02).

Potential Conflicts of Interest: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M11-1060.

Reproducible Research Statement:Study protocol: Not available. Statistical code: The SAS code for calculating the CMS 30-day mortality measures is available by request at cmsmortalitymeasures@yale.edu. Data set: The data used in this study were made available through a data use agreement under CMS contract HHSM-500-2008-00251 and are not publicly available.

Corresponding Author: Elizabeth E. Drye, MD, SM, Yale University School of Medicine, Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, 1 Church Street, Suite 200, New Haven, CT 06510; e-mail, Elizabeth.Drye@yale.edu.

Current Author Addresses: Drs. Drye, Wang, and Krumholz: Yale University School of Medicine, Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, 1 Church Street, Suite 200, New Haven, CT 06510.

Dr. Normand: Department of Health Care Policy, 180 Longwood Avenue, Boston, MA 02115.

Dr. Ross: Section of General Internal Medicine, Yale University School of Medicine, Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, Box 208093, New Haven, CT 06520-8093.

Mr. Schreiner: Dartmouth Medical School, 208 Kellogg Building, Hanover, NH 03755.

Drs. Han and Rapp: 7500 Security Boulevard, Mailstop S3-02-01, Baltimore, MD 21244-1850.

Author Contributions: Conception and design: E.E. Drye, S.L.T. Normand, Y. Wang, J.S. Ross, G.C. Schreiner, L. Han, H.M. Krumholz.

Analysis and interpretation of the data: E.E. Drye, S.L.T. Normand, Y. Wang, J.S. Ross, H.M. Krumholz.

Drafting of the article: E.E. Drye.

Critical revision of the article for important intellectual content: E.E. Drye, S.L.T. Normand, Y. Wang, J.S. Ross, G.C. Schreiner, L. Han, M. Rapp, H.M. Krumholz.

Final approval of the article: E.E. Drye, S.L.T. Normand, Y. Wang, J.S. Ross, L. Han, M. Rapp, H.M. Krumholz.

Statistical expertise: S.L.T. Normand, Y. Wang.

Obtaining of funding: L. Han, M. Rapp, H.M. Krumholz.

Administrative, technical, or logistic support: E.E. Drye, G.C. Schreiner.

Collection and assembly of data: Y. Wang.


Ann Intern Med. 2012;156(1_Part_1):19-26. doi:10.7326/0003-4819-156-1-201201030-00004
Text Size: A A A

This article has been corrected. The original version (PDF) is appended to this article as a supplement.

Background: In-hospital mortality measures, which are widely used to assess hospital quality, are not based on a standardized follow-up period and may systematically favor hospitals with shorter lengths of stay (LOSs).

Objective: To assess the agreement between performance measures of U.S. hospitals by using risk-standardized in-hospital and 30-day mortality rates.

Design: Observational study.

Setting: Nonfederal acute care hospitals in the United States with at least 30 admissions for acute myocardial infarction (AMI), heart failure (HF), and pneumonia from 2004 to 2006.

Patients: Medicare fee-for-service patients admitted for AMI, HF, or pneumonia from 2004 to 2006.

Measurements: The primary outcomes were in-hospital and 30-day risk-standardized mortality rates (RSMRs).

Results: Included patients comprised 718 508 admissions to 3135 hospitals for AMI, 1 315 845 admissions to 4209 hospitals for HF, and 1 415 237 admissions to 4498 hospitals for pneumonia. The hospital-level mean patient LOS varied across hospitals for each condition, ranging from 2.3 to 13.7 days for AMI, 3.5 to 11.9 days for HF, and 3.8 to 14.8 days for pneumonia. The mean RSMR differences (30-day RSMR minus in-hospital RSMR) were 5.3% (SD, 1.3) for AMI, 6.0% (SD, 1.3) for HF, and 5.7% (SD, 1.4) for pneumonia; distributions varied widely across hospitals. Performance classifications differed between the in-hospital and 30-day models for 257 hospitals (8.2%) for AMI, 456 (10.8%) for HF, and 662 (14.7%) for pneumonia. Hospital mean LOS was positively correlated with in-hospital RSMRs for all 3 conditions.

Limitation: Medicare claims data were used for risk adjustment.

Conclusion: In-hospital mortality measures provide a different assessment of hospital performance than 30-day mortality and are biased in favor of hospitals with shorter LOSs.

Primary Funding Source: The Centers for Medicare & Medicaid Services and National Heart, Lung, and Blood Institute.

Figures

Grahic Jump Location
Figure 1.

Mean hospital lengths of stay for patients with acute myocardial infarction, heart failure, and pneumonia.

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Figure 2.

Distribution of differences in 30-day and in-hospital RSMRs for acute myocardial infarction, heart failure, and pneumonia.

RSMR = risk-standardized mortality rate.

Grahic Jump Location

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