ReviewJournal of the American Medical Informatics Association : JAMIA2015
Review and evaluation of electronic health records-driven phenotype algorithm authoring tools for clinical and translational research.
Review in Journal of the American Medical Informatics Association : JAMIA, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 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
22 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Technological progress in electronic health record system optimization: Systematic review of systematic literature reviews.International journal of medical informatics · 2021Pooled it
- A Novel Screening Method to Identify Late-Stage Dementia Patients for Palliative Care Research and Practice.Journal of pain and symptom management · 2018Trial
- CohortDiagnostics: Phenotype evaluation across a network of observational data sources using population-level characterization.PloS one · 2025Article
- A general framework for developing computable clinical phenotype algorithms.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Variation in Phenotype Definitions in Observational Clinical Research: A Review of Three Conditions.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Review
- Design and validation of a FHIR-based EHR-driven phenotyping toolbox.Journal of the American Medical Informatics Association : JAMIA · 2022Article
- Accuracy of identifying hospital acquired venous thromboembolism by administrative coding: implications for big data and machine learning research.Journal of clinical monitoring and computing · 2022Article
- Real-World Evidence of COVID-19 Patients' Data Quality in the Electronic Health Records.Healthcare (Basel, Switzerland) · 2021Article
- A Patient-Screening Tool for Clinical Research Based on Electronic Health Records Using OpenEHR: Development Study.JMIR medical informatics · 2021Article
- Electronic Medical Record-Based Case Phenotyping for the Charlson Conditions: Scoping Review.JMIR medical informatics · 2021Article
- Polar labeling: silver standard algorithm for training disease classifiers.Bioinformatics (Oxford, England) · 2020Article
- Electronic Health Record Phenotypes for Identifying Patients with Late-Stage Disease: a Method for Research and Clinical Application.Journal of general internal medicine · 2019Article
- UK phenomics platform for developing and validating electronic health record phenotypes: CALIBER.Journal of the American Medical Informatics Association : JAMIA · 2019Article
- A case study evaluating the portability of an executable computable phenotype algorithm across multiple institutions and electronic health record environments.Journal of the American Medical Informatics Association : JAMIA · 2018Article
- Impact of problem-based charting on the utilization and accuracy of the electronic problem list.Journal of the American Medical Informatics Association : JAMIA · 2018Article
- Development of an automated phenotyping algorithm for hepatorenal syndrome.Journal of biomedical informatics · 2018Article
- Phenotyping through Semi-Supervised Tensor Factorization (PSST).AMIA ... Annual Symposium proceedings. AMIA Symposium · 2018Article
- Clinical Informatics Researcher's Desiderata for the Data Content of the Next Generation Electronic Health Record.Applied clinical informatics · 2017Article
- Development of Type 2 Diabetes Mellitus Phenotyping Framework Using Expert Knowledge and Machine Learning Approach.Journal of diabetes science and technology · 2017Article
- An information model for computable cancer phenotypes.BMC medical informatics and decision making · 2016Article
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
objectiveTo review and evaluate available software tools for electronic health record-driven phenotype authoring in order to identify gaps and needs for future development. MATERIALS AND
methodsCandidate phenotype authoring tools were identified through (1) literature search in four publication databases (PubMed, Embase, Web of Science, and Scopus) and (2) a web search. A collection of tools was compiled and reviewed after the searches. A survey was designed and distributed to the developers of the reviewed tools to discover their functionalities and features.
resultsTwenty-four different phenotype authoring tools were identified and reviewed. Developers of 16 of these identified tools completed the evaluation survey (67% response rate). The surveyed tools showed commonalities but also varied in their capabilities in algorithm representation, logic functions, data support and software extensibility, search functions, user interface, and data outputs. DISCUSSION: Positive trends identified in the evaluation included: algorithms can be represented in both computable and human readable formats; and most tools offer a web interface for easy access. However, issues were also identified: many tools were lacking advanced logic functions for authoring complex algorithms; the ability to construct queries that leveraged un-structured data was not widely implemented; and many tools had limited support for plug-ins or external analytic software.
conclusionsExisting phenotype authoring tools could enable clinical researchers to work with electronic health record data more efficiently, but gaps still exist in terms of the functionalities of such tools. The present work can serve as a reference point for the future development of similar tools.
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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.