Validation of an International Classification of Disease, 10th revision coding adaptation for the Charlson Comorbidity Index in United States healthcare claims data.


Journal

Pharmacoepidemiology and drug safety
ISSN: 1099-1557
Titre abrégé: Pharmacoepidemiol Drug Saf
Pays: England
ID NLM: 9208369

Informations de publication

Date de publication:
05 2021
Historique:
received: 31 07 2020
accepted: 08 02 2021
pubmed: 14 2 2021
medline: 25 11 2021
entrez: 13 2 2021
Statut: ppublish

Résumé

An International Classification of Disease (ICD-10) Charlson Comorbidity Index (CCI) adaptation had not been previously developed and validated for United States (US) healthcare claims data. Many researchers use the Canadian adaption by Quan et al (2005), not validated in US data. We sought to evaluate the predictive validity of a US ICD-10 CCI adaptation in US claims and compare it with the Canadian standard. Diverse patient cohorts (rheumatoid arthritis, hip/knee replacement, lumbar spine surgery, acute myocardial infarction [AMI], stroke, pneumonia) in the IBM® MarketScan® Research Databases were linked with the IBM MarketScan Mortality file. Predictive performance was measured using c-statistics for binary outcomes (1-year and postoperative mortality, in-hospital complications) and root mean square prediction error (RMSE) for continuous outcomes (1-year all-cause medical costs, index hospitalization costs, length of stay [LOS]), after adjusting for age and sex. C-statistics were compared by the method of DeLong and colleagues (1988); RMSEs, by resampling. C-statistics were generally high (≥ ~ 0.8) for mortality but lower for in-hospital complications (~0.6-0.7). RMSEs for costs and hospitalization LOS were relatively large and comparable to standard deviations. Results were similar overall between the US and Canadian adaptations, with relative differences typically <1%. This US-based coding adaptation and a previously published Canadian adaptation resulted in similar predictive ability for all outcomes evaluated but may have different construct validity (not evaluated in our study). We recommend using adaptations specific to the country of data origin based on good research practice.

Identifiants

pubmed: 33580525
doi: 10.1002/pds.5204
pmc: PMC8252530
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

582-593

Informations de copyright

© 2021 John Wiley & Sons Ltd.

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Auteurs

Julie Beyrer (J)

Global Patient Outcomes and Real World Evidence, Eli Lilly and Company, Indianapolis, Indiana, USA.

Janna Manjelievskaia (J)

IBM's Life Sciences, IBM Watson Health, Cambridge, Massachusetts, USA.

Machaon Bonafede (M)

IBM's Life Sciences, IBM Watson Health, Cambridge, Massachusetts, USA.

Gregory Lenhart (G)

IBM's Life Sciences, IBM Watson Health, Cambridge, Massachusetts, USA.

Sandra Nolot (S)

Global Patient Outcomes and Real World Evidence, Eli Lilly and Company, Indianapolis, Indiana, USA.

Diane Haldane (D)

Global Patient Outcomes and Real World Evidence, Eli Lilly and Company, Indianapolis, Indiana, USA.

Joseph Johnston (J)

Global Patient Outcomes and Real World Evidence, Eli Lilly and Company, Indianapolis, Indiana, USA.

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