Home LiteratureArticle Details
PMID: 1556797 Published · ppublish English Journal Article Research Support, U.S. Gov't, P.H.S.

Comorbidities, complications, and coding bias. Does the number of diagnosis codes matter in predicting in-hospital mortality?

JAMA ·Vol. 267 ·No. 16 ·1992-00-00 ·Pages 2197-203

Iezzoni LI, Foley SM, Daley J, Hughes J, Fisher ES, Heeren T

Abstract

Incomplete coding of secondary diagnoses may bias assessments of patient risks of poor outcomes using administrative health care databases, most of which allow only five diagnoses. The Medicare program is expanding the number of possible diagnoses from five to nine, aiming to improve coding completeness. We examined the impact of having more diagnosis codes available on assessments of risk of death. We used 1988 computerized hospital discharge abstract data from California, which allow up to 25 diagnoses per discharge, to select a sample of hospitalized patients and assessed the relationship between the presence of 29 specific secondary diagnoses and the risk of in-hospital death. Nonfederal acute-care hospitals in California. All patients at least 65 years of age who were hospitalized for stroke, pneumonia, acute myocardial infarction, or congestive heart failure in California in 1988 (N = 162,790). Relative risk of death for each specific secondary diagnosis. Many conditions that on a clinical basis would be expected to increase the risk of death, such as adult-onset diabetes mellitus, previous myocardial infarction, angina, and ventricular premature beats, were associated with a lower risk of in-hospital death. Bias against coding of chronic or comorbid conditions on the computerized discharge abstracts of patients who die best explains these results. Efforts to improve diagnosis coding completeness solely by increasing the number of available coding spaces may not succeed.

MeSH Terms
Aged Bias California/epidemiology Cerebrovascular Disorders/mortality Comorbidity Diagnosis-Related Groups/statistics & numerical data Heart Failure/mortality Hospital Mortality Humans Massachusetts Myocardial Infarction/mortality Patient Discharge/statistics & numerical data Pneumonia/mortality Risk Factors
Authors & Affiliations
6 authors, click to expand affiliations / ORCID
Iezzoni L I
Department of Medicine, Harvard Medical School, Beth Israel Hospital, Boston, MA 02215.
Foley S M
Daley J
Hughes J
Fisher E S
Heeren T
Article Info
Journal
JAMA
Abbr.
JAMA
ISSN
0098-7484
Published
1992-00-00
Pages
2197-203
Language
English
Region
United States
NLM ID
7501160
Subset
IM
Grants
AHRQ HHS · R01 HS06512-02 · United States
Corrections
CommentIn
Analysis Services
Analysis Services

Contact

No. 2 Wenbo Road, Zhangqiu District, Jinan, Shandong

Qilu Normal University · Genelibs Bioinformatics Lab

750 Shunhua Rd, Jinan

2F, Bldg F, University Science Park

Tel: 0531-88819269

WeChat Official Account

Follow our WeChat subscription account for real-time updates and the latest in medical and biological research.


Business Email

E-mail: [email protected]