Hostname: page-component-586b7cd67f-tf8b9 Total loading time: 0 Render date: 2024-12-01T04:06:00.416Z Has data issue: false hasContentIssue false

Mortality Rates as a Quality Indicator: A Simple Answer to a Complex Question

Published online by Cambridge University Press:  07 February 2022

William B. Crede
Affiliation:
Departments of Quality Assurance, Yale-New Haven Hospital, New Haven, Connecticut
Walter J. Hierholzer Jr.*
Affiliation:
Hospital Epidemiology, Yale-New Haven Hospital, New Haven, Connecticut
*
Department of Hospital Epidemiology, Yale-New Haven Hospital, New Haven, CT 06509

Abstract

As the consumers and regulators of health care have become more concerned with quality of delivered services, interest has focused on hospital- and physician-specific mortality rates as an index of quality. Mortality rates have several characteristics that promote their use as a performance indicator. The numerator, death, is generally (but perhaps incorrectly) accepted as an adverse outcome of health care. Death is thought to be easily measured, and is recorded in several locations, including the medical record abstract and death certificates, where the information is accessible without provider consent. The denominator, persons or patients, is also available from several public sources. The desirability of mortality data is further enhanced by the wide variety of statistical methods to manipulate and compare rates and proportions. The conceptual validity of mortality rates as reflecting quality is supported by a long tradition of using mortality rates at the “macro” level to compare the quality of national health care delivery systems (eg, infant mortality rates) and at the “micro” level to compare the outcome of different therapies (eg, thrombolytics for acute myocardial infarction). However, despite face validity, ease of measurement, and widespread acceptance in other areas, hospital-specific mortality rates, as calculated from current data sources, have a variety of potential problems.This article will explore the clinical, administrative, and information-based difficulties in using mortality rates as an indicator of the quality of medical care delivered by specific hospitals or physicians.

Type
Special Sections
Copyright
Copyright © The Society for Healthcare Epidemiology of America 1988

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Feinstein, AR: Clinical Judgment. Baltimore, Williams and Wilkins. 1967.Google Scholar
2. Gross, PA, Van Antwerpen, C: Nosocomial infections and hospital deaths: A case-control study. Am J Med 1983;75:658662.CrossRefGoogle ScholarPubMed
3. Gonella, JS, Hornbrook, MC, Louis, DZ: Staging of disease: A case-mix measurement. JAMA 1984;251:637644.Google Scholar
4. Brewster, AG, Karlin, BG, Hyde, LA, et al: MEDISGROUPS: A clinically based approach to classifying hospital patients at admission. Inquiry 1985;22:377387.Google Scholar
5. Wagner, DP, Draper, LA: Acute physiology and chronic health evaluation (APACHE II) and Medicare reimbursement. Health Care Financing Rev 1984; 6(suppl):91105.Google Scholar
6. Jencks, SF, Dobson, A: Refining case-mix adjustment: The research evidence. N Engl J Med 1987;317:379386.CrossRefGoogle ScholarPubMed
7. Dubois, RW, Rogers, WH, Moxley, JH III, et al: Hospital inpatient mortality: Is it a predictor of quality? N Engl J Med 1987: 317:16741679.CrossRefGoogle ScholarPubMed
8. Sears, MA, Rea, HH, de Boer, G, et al: Accuracy of certilication of deaths due to asthma: A national study. Am J Epidemiol 1986;124:10041011.CrossRefGoogle ScholarPubMed
9. Blumberg, MS: Risk adjusting health care outcomes: A methodologic review. Med Care Rev 1986;43:350393.CrossRefGoogle ScholarPubMed
10. Dubois, RW, Brook, RH, Rogers, WH: Adjusted hospital death rates: A potential screen for quality of medical care. Am J Public Health 1987;77:11621166.CrossRefGoogle ScholarPubMed