Literature DB >> 26683778

The Best Use of the Charlson Comorbidity Index With Electronic Health Care Database to Predict Mortality.

Aurélie Bannay1, Christophe Chaignot, Pierre-Olivier Blotière, Mickaël Basson, Alain Weill, Philippe Ricordeau, François Alla.   

Abstract

BACKGROUND: The most used score to measure comorbidity is the Charlson index. Its application to a health care administrative database including International Classification of Diseases, 10th edition (ICD-10) codes, medical procedures, and medication required studying its properties on survival. Our objectives were to adapt the Charlson comorbidity index to the French National Health Insurance database to predict 1-year mortality of discharged patients and to compare discrimination and calibration of different versions of the Charlson index.
METHODS: Our cohort included all adults discharged from a hospital stay in France in 2010 registered in the French National Health Insurance general scheme. The pathologies of the Charlson index were identified through ICD-10 codes of discharge diagnoses and long-term disease, specific medical procedures, and reimbursement of specific medications in the past 12 months before inclusion.
RESULTS: We included 6,602,641 subjects at the date of their first discharge from medical, surgical, or obstetrical department in 2010. One-year survival was 94.88%, decreasing from 98.41% for Charlson index of 0-71.64% for Charlson index of ≥5. With a discrimination of 0.91 and an appropriate calibration curve, we retained the crude Cox model including the age-adjusted Charlson index as a 4-level score.
CONCLUSIONS: Our study is the first to adapt the Charlson index to a large health care database including >6 million of inpatients. When mortality is the outcome, we recommended using the age-adjusted Charlson index as 4-level score to take into account comorbidities.

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Year:  2016        PMID: 26683778     DOI: 10.1097/MLR.0000000000000471

Source DB:  PubMed          Journal:  Med Care        ISSN: 0025-7079            Impact factor:   2.983


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