ArticlePloS one2017
Evaluating phecodes, clinical classification software, and ICD-9-CM codes for phenome-wide association studies in the electronic health record.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 254 papers, 8 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
254 citing papers in PubMed, 8 syntheses or guidelines pooled it, 418 citations in OpenAlex.
- Phenome- and laboratory-wide meta-analyses of sickle cell trait reveal multi-system disease associations.American journal of human genetics · 2026Pooled it
- Polygenic prediction of preeclampsia and gestational hypertension.Nature medicine · 2023Pooled it
- Genome-wide meta-analysis of iron status biomarkers and the effect of iron on all-cause mortality in HUNT.Communications biology · 2022Pooled it
- Comprehensive genetic analysis of the human lipidome identifies loci associated with lipid homeostasis with links to coronary artery disease.Nature communications · 2022Pooled it
- A multi-population phenome-wide association study of genetically-predicted height in the Million Veteran Program.PLoS genetics · 2022Pooled it
- Clinical Characterization of Copy Number Variants Associated With Neurodevelopmental Disorders in a Large-scale Multiancestry Biobank.JAMA psychiatry · 2022Pooled it
- Leveraging deep phenotyping from health check-up cohort with 10,000 Korean individuals for phenome-wide association study of 136 traits.Scientific reports · 2022Pooled it
- ATLAS: an automated association test using probabilistically linked health records with application to genetic studies.Journal of the American Medical Informatics Association : JAMIA · 2021Pooled it
- Enhanced pain relief with guanfacine as an adjuvant for trigeminal nerve blocks: insights from a PheWAS-guided randomized controlled study.Pain medicine (Malden, Mass.) · 2025Trial
- Accelerometer-derived real-world sleep stages and risk of incident diseases: A UK Biobank cohort study and phenome-wide association analysis.PLoS medicine · 2026Article
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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
- Large language models are powerful electronic health record encoders.NPJ digital medicine · 2026Article
- Polygenic risk factors for comorbid diagnoses in individuals with substance use disorders: A phenome-wide survival analysis.Psychological medicine · 2026Article
- Genomic Evidence on Antihypertensive Drug Targets and Oral Disease Outcomes.Journal of periodontal research · 2026Article
- Evaluating the feasibility of the CIPHER metadata framework towards building a conceptual phenotype standard.JAMIA open · 2026Article
- Faster CYP2A6 increases COPD and lung cancer risk by increasing smoking quantity: a mediated mendelian randomization and observational mediation study.Respiratory research · 2026Observational
- Distinguishing Age-specific Patterns in Comorbidities of Obstructive Sleep Apnea Using Real-World Data.medRxiv : the preprint server for health sciences · 2026Article
194 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 2 countries.
Funding
Abstract
objectiveTo compare three groupings of Electronic Health Record (EHR) billing codes for their ability to represent clinically meaningful phenotypes and to replicate known genetic associations. The three tested coding systems were the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes, the Agency for Healthcare Research and Quality Clinical Classification Software for ICD-9-CM (CCS), and manually curated "phecodes" designed to facilitate phenome-wide association studies (PheWAS) in EHRs. METHODS AND MATERIALS: We selected 100 disease phenotypes and compared the ability of each coding system to accurately represent them without performing additional groupings. The 100 phenotypes included 25 randomly-chosen clinical phenotypes pursued in prior genome-wide association studies (GWAS) and another 75 common disease phenotypes mentioned across free-text problem lists from 189,289 individuals. We then evaluated the performance of each coding system to replicate known associations for 440 SNP-phenotype pairs.
resultsOut of the 100 tested clinical phenotypes, phecodes exactly matched 83, compared to 53 for ICD-9-CM and 32 for CCS. ICD-9-CM codes were typically too detailed (requiring custom groupings) while CCS codes were often not granular enough. Among 440 tested known SNP-phenotype associations, use of phecodes replicated 153 SNP-phenotype pairs compared to 143 for ICD-9-CM and 139 for CCS. Phecodes also generally produced stronger odds ratios and lower p-values for known associations than ICD-9-CM and CCS. Finally, evaluation of several SNPs via PheWAS identified novel potential signals, some seen in only using the phecode approach. Among them, rs7318369 in PEPD was associated with gastrointestinal hemorrhage.
conclusionOur results suggest that the phecode groupings better align with clinical diseases mentioned in clinical practice or for genomic studies. ICD-9-CM, CCS, and phecode groupings all worked for PheWAS-type studies, though the phecode groupings produced superior results.
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Registered trials
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.