Literature DB >> 3172404

Flaws in mortality data. The hazards of ignoring comorbid disease.

S Greenfield1, H U Aronow, R M Elashoff, D Watanabe.   

Abstract

Recent public releases of hospital mortality data have sparked debate over methods to identify poor-quality care. We examined variations among hospitals in patient characteristics known independently to affect the risk of adverse outcomes and focused on patient comorbidity, defined as the state of health at admission apart from the primary diagnosis. Data from a study of 2935 incident cancer patients treated in seven Southern California hospitals revealed substantial variations among hospitals in age, cancer stage, and the burden of comorbid conditions. In the highest-ranked hospital, 17.9% of patients had high levels of comorbidity, compared with 9.3% in the lowest-ranked hospital. The three hospitals with the highest comorbidity were also identified as high-mortality outliers in a recent California report on hospital mortality rates. We conclude that comorbidity must be considered in any hospital quality assessment method based on patient outcome. If it is not considered, variations in referral and admission patterns may be misinterpreted as differences in hospital quality.

Entities:  

Mesh:

Year:  1988        PMID: 3172404

Source DB:  PubMed          Journal:  JAMA        ISSN: 0098-7484            Impact factor:   56.272


  38 in total

1.  Learning from differences within the NHS. Clinical indicators should be used to learn, not to judge.

Authors:  A G Mulley
Journal:  BMJ       Date:  1999-08-28

2.  Explaining differences in English hospital death rates using routinely collected data.

Authors:  B Jarman; S Gault; B Alves; A Hider; S Dolan; A Cook; B Hurwitz; L I Iezzoni
Journal:  BMJ       Date:  1999-06-05

3.  Overcoming potential pitfalls in the use of Medicare data for epidemiologic research.

Authors:  E S Fisher; J A Baron; D J Malenka; J Barrett; T A Bubolz
Journal:  Am J Public Health       Date:  1990-12       Impact factor: 9.308

4.  External monitoring of quality of health care in the United States.

Authors:  N J Wareham
Journal:  Qual Health Care       Date:  1994-06

5.  Comparing comorbid-illness indices assessing outcome variation: the case of prostatectomy.

Authors:  M A Krousel-Wood; A Abdoh; R Re
Journal:  J Gen Intern Med       Date:  1996-01       Impact factor: 5.128

Review 6.  Comorbidity in patients with cancer of the head and neck: prevalence and impact on treatment and prognosis.

Authors:  Jay F Piccirillo; Anna Vlahiotis
Journal:  Curr Oncol Rep       Date:  2006-03       Impact factor: 5.075

7.  The accuracy of Medicare's hospital claims data: progress has been made, but problems remain.

Authors:  E S Fisher; F S Whaley; W M Krushat; D J Malenka; C Fleming; J A Baron; D C Hsia
Journal:  Am J Public Health       Date:  1992-02       Impact factor: 9.308

8.  Ambulatory care groups: a categorization of diagnoses for research and management.

Authors:  B Starfield; J Weiner; L Mumford; D Steinwachs
Journal:  Health Serv Res       Date:  1991-04       Impact factor: 3.402

9.  Using patient reports to assess health-related quality of life after total hip replacement.

Authors:  P D Cleary; D T Reilly; S Greenfield; A G Mulley; L Wexler; F Frankel; B J McNeil
Journal:  Qual Life Res       Date:  1993-02       Impact factor: 4.147

10.  Self-reported medical morbidity among informal caregivers of chronic illness: the case of cancer.

Authors:  Youngmee Kim; Charles S Carver; Rachel S Cannady; Kelly M Shaffer
Journal:  Qual Life Res       Date:  2012-08-21       Impact factor: 4.147

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