ArticleGigaScience2021
Desiderata for the development of next-generation electronic health record phenotype libraries.
Article in GigaScience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Systematic Review to Summarize and Critically Appraise Existing Phenotype Libraries Using Electronic Health Records.Pharmacoepidemiology and drug safety · 2026Pooled it
- Introducing the TOP framework: a novel phenotyping solution for collaborative phenotype algorithm development and application.Journal of biomedical semantics · 2026Article
- A platform for generating clinical intelligence from routine health data in hospitals: PICTURE.Future healthcare journal · 2026Article
- PhenoFit: a framework for determining computable phenotyping algorithm fitness for purpose and reuse.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Recommendations to Enable Broader Use of Real-World Evidence to Inform Decision-Making Throughout Pharmacovigilance Signal Management.Pharmacoepidemiology and drug safety · 2025Review
- Computational definition of medical exclusion and feasibility of excluding people not eligible for French population-based colorectal cancer screening from the French medico-administrative database.BMC medical informatics and decision making · 2025Review
- Utilization of Computable Phenotypes in Electronic Health Record Research: A Review and Case Study in Atopic Dermatitis.The Journal of investigative dermatology · 2025Review
- CohortDiagnostics: Phenotype evaluation across a network of observational data sources using population-level characterization.PloS one · 2025Article
- Machine learning based prediction models for cardiovascular disease risk using electronic health records data: systematic review and meta-analysis.European heart journal. Digital health · 2025Review
- Real-World Evidence BRIDGE: A Tool to Connect Protocol With Code Programming.Pharmacoepidemiology and drug safety · 2024Article
- Adopting a Framework for Rapid Real-World Data Analyses in Safety Signal Assessment.Therapeutic innovation & regulatory science · 2024Article
- Centralized and Federated Models for the Analysis of Clinical Data.Annual review of biomedical data science · 2024Review
- Phenotype execution and modeling architecture to support disease surveillance and real-world evidence studies: English sentinel network evaluation.JAMIA open · 2024Article
- Creating a next-generation phenotype library: the health data research UK Phenotype Library.JAMIA open · 2024Article
- Centralized Interactive Phenomics Resource: an integrated online phenomics knowledgebase for health data users.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Article
- Data Resource Profile: Victorian Comprehensive Cancer Centre Data Connect.International journal of epidemiology · 2023Article
- UK research data resources based on primary care electronic health records: review and summary for potential users.BJGP open · 2023Article
- Framework of the Centralized Interactive Phenomics Resource (CIPHER) standard for electronic health data-based phenomics knowledgebase.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Characterizing variability of electronic health record-driven phenotype definitions.Journal of the American Medical Informatics Association : JAMIA · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
Abstract
backgroundHigh-quality phenotype definitions are desirable to enable the extraction of patient cohorts from large electronic health record repositories and are characterized by properties such as portability, reproducibility, and validity. Phenotype libraries, where definitions are stored, have the potential to contribute significantly to the quality of the definitions they host. In this work, we present a set of desiderata for the design of a next-generation phenotype library that is able to ensure the quality of hosted definitions by combining the functionality currently offered by disparate tooling.
methodsA group of researchers examined work to date on phenotype models, implementation, and validation, as well as contemporary phenotype libraries developed as a part of their own phenomics communities. Existing phenotype frameworks were also examined. This work was translated and refined by all the authors into a set of best practices.
resultsWe present 14 library desiderata that promote high-quality phenotype definitions, in the areas of modelling, logging, validation, and sharing and warehousing.
conclusionsThere are a number of choices to be made when constructing phenotype libraries. Our considerations distil the best practices in the field and include pointers towards their further development to support portable, reproducible, and clinically valid phenotype design. The provision of high-quality phenotype definitions enables electronic health record data to be more effectively used in medical domains.
Indexed as
Identifiers
What OpenQuestion holds
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.