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PMID: 8676173 Published · ppublish English Comparative Study Journal Article Research Support, Non-U.S. Gov't

Searching for an improved clinical comorbidity index for use with ICD-9-CM administrative data.

Journal of clinical epidemiology ·Vol. 49 ·No. 3 ·1996-03-00 ·Pages 273-8

Ghali WA, Hall RE, Rosen AK, Ash AS, Moskowitz MA

Abstract

We studied approaches to comorbidity risk adjustment by comparing two ICD-9-CM adaptations (Deyo, Dartmouth-Manitoba) of the Charlson comorbidity index applied to Massachusetts coronary artery bypass surgery data. We also developed a new comorbidity index by assigning study-specific weights to the original Charlson comorbidity variables. The 2 ICD-9-CM coding adaptations assigned identical Charlson comorbidity scores to 90% of cases, and specific comorbidities were largely found in the same cases (kappa values of 0.72-1.0 for 15 of 16 comorbidities). Meanwhile, the study-specific comorbidity index identified a 10% subset of patients with 15% mortality, whereas the 5% highest-risk patients according to the Charlson index had only 8% mortality (p = 0.01). A model using the new index to predict mortality had better validated performance than a model based on the original Charlson index (c = 0.74 vs. 0.70). Thus, in our population, the ICD-9-CM adaptation used to create the Charlson score mattered little, but using study-specific weights with the Charlson variables substantially improved the power of these data to predict mortality.

MeSH Terms
Aged Comorbidity Coronary Artery Bypass/mortality Coronary Disease/epidemiology,mortality,surgery Female Hospital Mortality Humans Male Middle Aged Models, Statistical Multivariate Analysis Reproducibility of Results
Authors & Affiliations
5 authors, click to expand affiliations / ORCID
Ghali W A
Health Care Research Unit, Boston University Medical Center, MA 02118, USA.
Hall R E
Rosen A K
Ash A S
Moskowitz M A
Article Info
Journal
Journal of clinical epidemiology
Abbr.
J Clin Epidemiol
ISSN
0895-4356
Published
1996-03-00
Pages
273-8
Language
English
Region
United States
NLM ID
8801383
Subset
IM
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