ArticleInternational journal of biomedical data mining2015
ePhenotyping for Abdominal Aortic Aneurysm in the Electronic Medical Records and Genomics (eMERGE) Network: Algorithm Development and Konstanz Information Miner Workflow.
Article in International journal of biomedical data mining, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 8 citations in OpenAlex.
- Near Real-time Natural Language Processing for the Extraction of Abdominal Aortic Aneurysm Diagnoses From Radiology Reports: Algorithm Development and Validation Study.JMIR medical informatics · 2023Article
- Defining Major Depressive Disorder Cohorts Using the EHR: Multiple Phenotypes Based on ICD-9 Codes and Medication Orders.Neurology, psychiatry, and brain research · 2020Article
- Abdominal aortic aneurysm in prostate cancer patients: the "road map" from incidental detection to advanced predictive, preventive, and personalized approach utilizing common follow-up for both pathologies.The EPMA journal · 2019Article
- Genetic risk models: Influence of model size on risk estimates and precision.Genetic epidemiology · 2017Article
- Association Between Telomere Length and Risk of Cancer and Non-Neoplastic Diseases: A Mendelian Randomization Study.JAMA oncology · 2017Article
- PheKB: a catalog and workflow for creating electronic phenotype algorithms for transportability.Journal of the American Medical Informatics Association : JAMIA · 2016Article
Corrections and comments
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Authors and funding
29 authors at 1 institution in 1 country.
Funding
Abstract
BACKGROUND AND
objectiveWe designed an algorithm to identify abdominal aortic aneurysm cases and controls from electronic health records to be shared and executed within the "electronic Medical Records and Genomics" (eMERGE) Network. MATERIALS AND
methodsStructured Query Language, was used to script the algorithm utilizing "Current Procedural Terminology" and "International Classification of Diseases" codes, with demographic and encounter data to classify individuals as case, control, or excluded. The algorithm was validated using blinded manual chart review at three eMERGE Network sites and one non-eMERGE Network site. Validation comprised evaluation of an equal number of predicted cases and controls selected at random from the algorithm predictions. After validation at the three eMERGE Network sites, the remaining eMERGE Network sites performed verification only. Finally, the algorithm was implemented as a workflow in the Konstanz Information Miner, which represented the logic graphically while retaining intermediate data for inspection at each node. The algorithm was configured to be independent of specific access to data and was exportable (without data) to other sites.
resultsThe algorithm demonstrated positive predictive values (PPV) of 92.8% (CI: 86.8-96.7) and 100% (CI: 97.0-100) for cases and controls, respectively. It performed well also outside the eMERGE Network. Implementation of the transportable executable algorithm as a Konstanz Information Miner workflow required much less effort than implementation from pseudo code, and ensured that the logic was as intended. DISCUSSION AND
conclusionThis ePhenotyping algorithm identifies abdominal aortic aneurysm cases and controls from the electronic health record with high case and control PPV necessary for research purposes, can be disseminated easily, and applied to high-throughput genetic and other studies.
Indexed as
Identifiers
27054044PMC4820287W2238456835What 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.