Denaxas, S;
Parkinson, H;
Fitzpatrick, N;
Sudlow, C;
Hemingway, H;
(2019)
Analyzing the heterogeneity of rule-based EHR phenotyping algorithms in CALIBER and the UK Biobank.
In: Wiratunga, N and Coenen, F and Sani, S, (eds.)
CEUR Workshop Proceedings vol 2429.
(pp. pp. 6-14).
CEUR: Macao, China.
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Abstract
Electronic Health Records (EHR) are data generated during routine interactions across healthcare settings and contain rich, longitudinal information on diagnoses, symptoms, medications, investigations and tests. A primary use-case for EHR is the creation of phenotyping algorithms used to identify disease status, onset and progression or extraction of information on risk factors or biomarkers. Phenotyping however is challenging since EHR are collected for different purposes, have variable data quality and often require significant harmonization. While considerable effort goes into the phenotyping process, no consistent methodology for representing algorithms exists in the UK. Creating a national repository of curated algorithms can potentially enable algorithm dissemination and reuse by the wider community. A critical first step is the creation of a robust minimum information standard for phenotyping algorithm components (metadata, implementation logic, validation evidence) which involves identifying and reviewing the complexity and heterogeneity of current UK EHR algorithms. In this study, we analyzed all available EHR phenotyping algorithms (n=70) from two large-scale contemporary EHR resources in the UK (CALIBER and UK Biobank). We documented EHR sources, controlled clinical terminologies, evidence of algorithm validation, representation and implementation logic patterns. Understanding the heterogeneity of UK EHR algorithms and identifying common implementation patterns will facilitate the design of a minimum information standard for representing and curating algorithms nationally and internationally.
| Type: | Proceedings paper |
|---|---|
| Title: | Analyzing the heterogeneity of rule-based EHR phenotyping algorithms in CALIBER and the UK Biobank |
| Event: | KDH 2019: 4th International Workshop on Knowledge Discovery in Healthcare Data co-located with The 28th International Joint Conference on Artificial Intelligence (IJCAI 2019) |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | http://ceur-ws.org/Vol-2429/ |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics > Clinical Epidemiology |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10097445 |
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