You are seeing this message because your Web browser does not support basic Web standards. Find out more about why this message is appearing and what you can do to make your experience on this site better.


ABOUT JAMA
Advanced Search

Welcome   | My Account | E-mail Alerts | Access Rights | Sign In


  Vol. 260 No. 24, December 23, 1988 TABLE OF CONTENTS
  JAMA
  •  Online Features
  ARTICLE
 This Article
 •Send to a friend
 • Save in My Folder
 •Save to citation manager
 •Permissions
 Citing Articles
 •Citation map
 •Citing articles on HighWire
 •Contact me when this article is cited
 Related Content
 •Similar articles in JAMA

Interpreting hospital mortality data. The role of clinical risk adjustment

S. F. Jencks, J. Daley, D. Draper, N. Thomas, G. Lenhart and J. Walker
Office of Research, Health Care Financing Administration, Baltimore.

This study uses national Medicare data as well as data that were abstracted to calibrate the Medicare Mortality Predictor System to assess the usefulness of a risk adjustment system in interpreting hospital mortality rates. The majority of variation in annual hospital death rates for the four conditions studied (stroke, pneumonia, myocardial infarction, and congestive heart failure) is chance variability that results from the relatively small numbers of patients treated in most hospitals in a year. For hospitals in the highest and lowest quartiles of observed death rates, the difference between observed rates and those predicted by the Medicare Mortality Predictor System is not quite on third smaller than the difference between observed rates and unadjusted national rates. Risk adjustment methods do not show whether the unexplained difference in mortality rates results from differences in effectiveness of care or unmeasured differences in patient risk at the time of admission. Risk-adjusted mortality rates, therefore, should be supplemented by review of the actual care rendered before conclusions are drawn regarding effectiveness of care.

THIS ARTICLE HAS BEEN CITED BY OTHER ARTICLES

Standards for Statistical Models Used for Public Reporting of Health Outcomes: An American Heart Association Scientific Statement From the Quality of Care and Outcomes Research Interdisciplinary Writing Group: Cosponsored by the Council on Epidemiology and Prevention and the Stroke Council Endorsed by the American College of Cardiology Foundation
Krumholz et al.
Circulation 2006;113:456-462.
ABSTRACT | FULL TEXT  

Quality of Care Is Associated with Survival in Vulnerable Older Patients
Higashi et al.
ANN INTERN MED 2005;143:274-281.
ABSTRACT | FULL TEXT  

Re-evaluation and modification of the Stuivenberg Hospital Acute Renal Failure (SHARF) scoring system for the prognosis of acute renal failure: an independent multicentre, prospective study
Lins et al.
Nephrol Dial Transplant 2004;19:2282-2288.
ABSTRACT | FULL TEXT  

Accepting Critically Ill Transfer Patients: Adverse Effect on a Referral Center's Outcome and Benchmark Measures
Rosenberg et al.
ANN INTERN MED 2003;138:882-890.
ABSTRACT | FULL TEXT  

Patient safety research: does it have legs?
Lilford
Qual Saf Health Care 2002;11:113-114.
FULL TEXT  

Variations in mortality rates among Canadian neonatal intensive care units: interpretation and implications
Tyson and Kennedy
CMAJ 2002;166:191-192.
FULL TEXT  

Influencing Care in Acute Myocardial Infarction: A Randomized Trial Comparing 2 Types of Intervention
Sauaia et al.
American Journal of Medical Quality 2000;15:197-206.
ABSTRACT  

Proposed Agenda for the Measurement of Quality-of-Care Outcomes in Oncology Practice
Mandelblatt et al.
JCO 1999;17:2614-2614.
ABSTRACT | FULL TEXT  

Predicting survival using simple clinical variables: a case study in traumatic brain injury
Signorini et al.
J. Neurol. Neurosurg. Psychiatry 1999;66:20-25.
ABSTRACT | FULL TEXT  

Reliability of league tables of in vitro fertilisation clinics: retrospective analysis of live birth rates • Commentary: How robust are rankings? The implications of confidence intervals
Marshall et al.
BMJ 1998;316:1701-1705.
ABSTRACT | FULL TEXT  

Commentary: Inaccurate Data on the Quality of Care May Do More Harm than Good--An Alternative Approach Is Required
Boscarino and Chang
American Journal of Medical Quality 1997;12:196-200.
ABSTRACT  

ICU Admission Score for Predicting Morbidity and Mortality Risk After Coronary Artery Bypass Grafting
Higgins et al.
Ann. Thorac. Surg. 1997;64:1050-1058.
ABSTRACT | FULL TEXT  

Case-Mix Adjustment Using Administrative Databases: A Paradigm to Guide Future Research
Wray et al.
Med Care Res Rev 1997;54:326-356.
ABSTRACT  

Coronary Artery Bypass Risk Prediction Using Neural Networks
Lippmann and Shahian
Ann. Thorac. Surg. 1997;63:1635-1643.
ABSTRACT | FULL TEXT  

A Prediction Rule to Identify Low-Risk Patients with Community-Acquired Pneumonia
Fine et al.
NEJM 1997;336:243-250.
ABSTRACT | FULL TEXT  

Outcome After Surgery: An Evolving Concept
Kazmers
PERSPECT VASC SURG ENDOVASC THER 1995;8:109-128.
 

Measuring the Quality of Care: Reforming the Health Care System
Longo and Daugird
American Journal of Medical Quality 1994;9:104-115.
ABSTRACT  

Risk Adjustment Methods Can Affect Perceptions of Outcomes
Iezzoni et al.
American Journal of Medical Quality 1994;9:43-48.
ABSTRACT  

The Reliability of Peer Assessments: A Meta-Analysis
Goldman
Eval Health Prof 1994;17:3-21.
ABSTRACT  

Can Administrative Data be Used to Compare the Quality of Health Care?
Romano
Med Care Res Rev 1993;50:451-477.
 

Birthweight-adjusted Mortality Rates for Assessing the Effectiueness of Neonatal Intensive Care
Horbar
Med Decis Making 1992;12:259-264.
ABSTRACT  

Assessing Medicare's Prospective Payment System for Hospitals
Chulis
Med Care Res Rev 1991;48:167-206.
 

ASSESSING QUALITY OF CARE FOR MEDICARE PATIENTS
JWatch General 1989;1989:8-8.
FULL TEXT  





HOME | CURRENT ISSUE | PAST ISSUES | TOPIC COLLECTIONS | CME | SUBMIT | SUBSCRIBE | HELP
CONDITIONS OF USE | PRIVACY POLICY | CONTACT US | SITE MAP
 
© 1988 American Medical Association. All Rights Reserved.