ArticleJMIR medical informatics2019
Mapping ICD-10 and ICD-10-CM Codes to Phecodes: Workflow Development and Initial Evaluation.
Article in JMIR medical informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 361 papers, 4 of them syntheses that pooled it.
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Who cites it
361 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- A Systematic Review to Summarize and Critically Appraise Existing Phenotype Libraries Using Electronic Health Records.Pharmacoepidemiology and drug safety · 2026Pooled it
- Multi-ancestry genome-wide association study of severe pregnancy nausea and vomiting.Nature genetics · 2026Pooled it
- Genome-wide association study provides novel insight into the genetic architecture of severe obesity.PLoS genetics · 2025Pooled it
- Discovery of novel ancestry specific genes for androgens and hypogonadism in Million Veteran Program Men.Nature communications · 2025Pooled it
- Conditional Perplexity Scoring for Large Language Model-Generated Differential Diagnoses in Case Reports: Preliminary Computational Evaluation.JMIR formative research · 2026Article
- Characterization and validation of EHR computable phenotypes for Long COVID using patient-reported symptoms: insights from the nationwide RECOVER program.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Rare variant effect estimation and polygenic risk prediction.Nature genetics · 2026Article
- Paediatric proteomic signatures of cardiometabolic disease-associated traits predict adult disease outcomes.Nature metabolism · 2026Article
- Accelerometer-derived real-world sleep stages and risk of incident diseases: A UK Biobank cohort study and phenome-wide association analysis.PLoS medicine · 2026Article
- Article
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- RESCUE: An end-to-end multi-agent LLM system for proactive rare-disease patient screening in the EHR.medRxiv : the preprint server for health sciences · 2026Article
- Transformer-DAPT: AI-based dynamic assessment of ischemic and bleeding risks in patients on DAPT following PCI.NPJ digital medicine · 2026Article
- Convergent human genetic evidence implicates serine biosynthesis in diabetic peripheral neuropathy.medRxiv : the preprint server for health sciences · 2026Article
- Early Prediction of Parkinson's Disease Progression by Integrating Research Cohort and Real-World Data Using Knowledge-Anchored Graph Learning.medRxiv : the preprint server for health sciences · 2026Article
- Large language models are powerful electronic health record encoders.NPJ digital medicine · 2026Article
- Pediatric precision sleep network: a study protocol for identifying sleep signatures of mental health risk in peri-adolescents.BMC pediatrics · 2026Article
- Multimorbidity patterns and phenotype transitions in patients with clinician-coded long COVID: a multicenter US electronic health record cohort study.BMC infectious diseases · 2026Article
- Unsupervised characterization of 100,272 EHR patients identifies high-risk groups and comorbidities linked to premature aging.NPJ digital medicine · 2026Article
- Polygenic risk factors for comorbid diagnoses in individuals with substance use disorders: A phenome-wide survival analysis.Psychological medicine · 2026Article
301 more citing papers are in PubMed but not listed here.
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Authors and funding
12 authors.
Funding
Abstract
backgroundThe 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).
objectiveThe 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.
methodsWe 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.
resultsWe 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 <10% for an acute disease for phenotypes sourced from the ICD-10-CM phecode map. Using the ICD-9-CM and ICD-10-CM maps, we conducted a PheWAS with a Lipoprotein(a) genetic variant, rs10455872, which replicated two known genotype-phenotype associations with similar effect sizes: coronary atherosclerosis (ICD-9-CM: P<.001; odds ratio (OR) 1.60 [95% CI 1.43-1.80] vs ICD-10-CM: P<.001; OR 1.60 [95% CI 1.43-1.80]) and chronic ischemic heart disease (ICD-9-CM: P<.001; OR 1.56 [95% CI 1.35-1.79] vs ICD-10-CM: P<.001; OR 1.47 [95% CI 1.22-1.77]).
conclusionsThis 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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.