Mapping ICD-10 and ICD-10-CM Codes to Phecodes: Workflow Development and Initial Evaluation
| Autor: | Xue Li, Aliya Gifford, Evropi Theodoratou, Xiangrui Meng, Wei-Qi Wei, Lisa Bastarache, Patrick Wu, Harry Campbell, Juan Zhao, Tim Varley, Joshua C. Denny, Robert J. Carroll |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
medicine.medical_specialty
phenotyping Health Informatics Genome-wide association study Disease phenome-wide association study medical informatics applications 03 medical and health sciences 0302 clinical medicine Health Information Management Internal medicine Medicine 030304 developmental biology Original Paper 0303 health sciences genome-wide association study business.industry Unified Medical Language System ICD-10 electronic health record Odds ratio Biobank 3. Good health Informatics Observational study data science business 030217 neurology & neurosurgery |
| Zdroj: | JMIR Medical Informatics Wu, P, Gifford, A, Meng, X, Li, X, Campbell, H, Varley, T, Zhao, J, Carroll, R, Bastarache, L, Denny, J C, Theodoratou, E & Wei, W-Q 2019, ' Mapping ICD-10 and ICD-10-CM Codes to Phecodes: Workflow Development and Initial Evaluation ', JMIR Medical Informatics, vol. 7, no. 4 . https://doi.org/10.2196/14325 |
| ISSN: | 2291-9694 |
| DOI: | 10.2196/14325 |
| Popis: | Background The phecode system was built upon the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) for phenome-wide association studies (PheWAS) using the electronic health record (EHR). Objective The goal of this paper was to develop and perform an initial evaluation of maps from the International Classification of Diseases, 10th Revision (ICD-10) and the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes to phecodes. Methods We mapped ICD-10 and ICD-10-CM codes to phecodes using a number of methods and resources, such as concept relationships and explicit mappings from the Centers for Medicare & Medicaid Services, the Unified Medical Language System, Observational Health Data Sciences and Informatics, Systematized Nomenclature of Medicine-Clinical Terms, and the National Library of Medicine. We assessed the coverage of the maps in two databases: Vanderbilt University Medical Center (VUMC) using ICD-10-CM and the UK Biobank (UKBB) using ICD-10. We assessed the fidelity of the ICD-10-CM map in comparison to the gold-standard ICD-9-CM phecode map by investigating phenotype reproducibility and conducting a PheWAS. Results We mapped >75% of ICD-10 and ICD-10-CM codes to phecodes. Of the unique codes observed in the UKBB (ICD-10) and VUMC (ICD-10-CM) cohorts, >90% were mapped to phecodes. We observed 70-75% reproducibility for chronic diseases and Conclusions This study introduces the beta versions of ICD-10 and ICD-10-CM to phecode maps that enable researchers to leverage accumulated ICD-10 and ICD-10-CM data for PheWAS in the EHR. |
| Databáze: | OpenAIRE |
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