ArticleJournal of biomedical informatics2014
Design patterns for the development of electronic health record-driven phenotype extraction algorithms.
Article in Journal of biomedical informatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
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Who cites it
38 citing papers in PubMed.
- Sociotechnical Intervention for Improved Delivery of Preventive Cardiovascular Care to Rural Communities: Participatory Design Approach.Journal of medical Internet research · 2022Trial
- Fragile X Syndrome in Adulthood: A Study of Electronic Health Records.American journal on intellectual and developmental disabilities · 2026Article
- Enhancing patient representation learning with inferred family pedigrees improves disease risk prediction.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- A general framework for developing computable clinical phenotype algorithms.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Natural language processing to identify lupus nephritis phenotype in electronic health records.BMC medical informatics and decision making · 2024Article
- Automated Family Histories Significantly Improve Risk Prediction in an EHR.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2024Article
- Characterizing variability of electronic health record-driven phenotype definitions.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Performance of EHR classifiers for patient eligibility in a clinical trial of precision screening.Contemporary clinical trials · 2022Article
- Advancing artificial intelligence-assisted pre-screening for fragile X syndrome.BMC medical informatics and decision making · 2022Article
- Development and validation of techniques for phenotyping ST-elevation myocardial infarction encounters from electronic health records.JAMIA open · 2021Article
- Artificial intelligence-assisted phenotype discovery of fragile X syndrome in a population-based sample.Genetics in medicine : official journal of the American College of Medical Genetics · 2021Article
- Medical records-based chronic kidney disease phenotype for clinical care and "big data" observational and genetic studies.NPJ digital medicine · 2021Article
- Evaluation of structured data from electronic health records to identify clinical classification criteria attributes for systemic lupus erythematosus.Lupus science & medicine · 2021Article
- Computerized Adjudication of Coronary Heart Disease Events Using the Electronic Medical Record in HIV Clinical Research: Possibilities and Challenges Ahead.AIDS research and human retroviruses · 2020Article
- High-throughput phenotyping with electronic medical record data using a common semi-supervised approach (PheCAP).Nature protocols · 2019Article
- Making work visible for electronic phenotype implementation: Lessons learned from the eMERGE network.Journal of biomedical informatics · 2019Article
- Identifying Opioid Use Disorder in the Emergency Department: Multi-System Electronic Health Record-Based Computable Phenotype Derivation and Validation Study.JMIR medical informatics · 2019Article
- Data-driven phenotype discovery ofScience advances · 2019Article
- Facilitating phenotype transfer using a common data model.Journal of biomedical informatics · 2019Article
- A Roadmap for Foundational Research on Artificial Intelligence in Medical Imaging: From the 2018 NIH/RSNA/ACR/The Academy Workshop.Radiology · 2019Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
backgroundDesign patterns, in the context of software development and ontologies, provide generalized approaches and guidance to solving commonly occurring problems, or addressing common situations typically informed by intuition, heuristics and experience. While the biomedical literature contains broad coverage of specific phenotype algorithm implementations, no work to date has attempted to generalize common approaches into design patterns, which may then be distributed to the informatics community to efficiently develop more accurate phenotype algorithms.
methodsUsing phenotyping algorithms stored in the Phenotype KnowledgeBase (PheKB), we conducted an independent iterative review to identify recurrent elements within the algorithm definitions. We extracted and generalized recurrent elements in these algorithms into candidate patterns. The authors then assessed the candidate patterns for validity by group consensus, and annotated them with attributes.
resultsA total of 24 electronic Medical Records and Genomics (eMERGE) phenotypes available in PheKB as of 1/25/2013 were downloaded and reviewed. From these, a total of 21 phenotyping patterns were identified, which are available as an online data supplement.
conclusionsRepeatable patterns within phenotyping algorithms exist, and when codified and cataloged may help to educate both experienced and novice algorithm developers. The dissemination and application of these patterns has the potential to decrease the time to develop algorithms, while improving portability and accuracy.
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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.