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

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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https://hal.univ-lorraine.fr/hal-01817541
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Submitted on : Monday, June 18, 2018 - 10:08:44 AM
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Aurélie Bannay, Christophe Chaignot, Pierre-Olivier Blotiere, Mickaël Basson, Alain Weill, et al.. The Best Use of the Charlson Comorbidity Index With Electronic Health Care Database to Predict Mortality. Medical Care, American Public Health Association, 2016, 54 (2), pp.188-194. ⟨10.1097/MLR.0000000000000471⟩. ⟨hal-01817541⟩

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