Summary
This paper reports on the Phenotype KnowledgeBase (PheKB), an online platform enabling researchers to build, share, and validate electronic phenotype algorithms for mining electronic health records. As of June 2015, the repository contained 30 finalized and 62 in-development phenotype algorithms with demonstrated high transportability across institutions: median case PPV was 96.0% at authoring sites and 97.5% at implementation sites, demonstrating that algorithms developed at one institution generalise effectively to others. The findings support PheKB's utility as a central repository for developing research-grade phenotypes from health care data.
UK applicability
The methodology and findings regarding phenotype algorithm development and transportability are broadly applicable to UK NHS and health research settings, particularly for researchers working with NHS electronic health record data. However, direct adoption would require adaptation to UK coding systems (e.g. SNOMED CT) and NHS-specific data structures, and UK researchers would benefit from equivalent UK-based repositories.
Key measures
Positive predictive value (PPV) for cases and controls at authoring vs. implementation sites; algorithm component frequency (ICD codes, medications, natural language processing); phenotype reuse metrics
Outcomes reported
The study documented the development, sharing, and validation of 30 finalized electronic phenotype algorithms and 62 in-development algorithms across multiple health care systems. Performance metrics including positive predictive values (PPVs) for case and control identification were compared between authoring institutions and secondary implementation sites.
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