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Evaluating the impact of alternative phenotype definitions on incidence rates across a global data network

Makadia, Rupa; Shoaibi, Azza; Rao, Gowtham A; Ostropolets, Anna; Rijnbeek, Peter R; Voss, Erica A; Duarte-Salles, Talita; ... Ryan, Patrick B; + view all (2023) Evaluating the impact of alternative phenotype definitions on incidence rates across a global data network. JAMIA Open , 6 (4) , Article ooad096. 10.1093/jamiaopen/ooad096. Green open access

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Abstract

OBJECTIVE: Developing accurate phenotype definitions is critical in obtaining reliable and reproducible background rates in safety research. This study aims to illustrate the differences in background incidence rates by comparing definitions for a given outcome. MATERIALS AND METHODS: We used 16 data sources to systematically generate and evaluate outcomes for 13 adverse events and their overall background rates. We examined the effect of different modifications (inpatient setting, standardization of code set, and code set changes) to the computable phenotype on background incidence rates. RESULTS: Rate ratios (RRs) of the incidence rates from each computable phenotype definition varied across outcomes, with inpatient restriction showing the highest variation from 1 to 11.93. Standardization of code set RRs ranges from 1 to 1.64, and code set changes range from 1 to 2.52. DISCUSSION: The modification that has the highest impact is requiring inpatient place of service, leading to at least a 2-fold higher incidence rate in the base definition. Standardization showed almost no change when using source code variations. The strength of the effect in the inpatient restriction is highly dependent on the outcome. Changing definitions from broad to narrow showed the most variability by age/gender/database across phenotypes and less than a 2-fold increase in rate compared to the base definition. CONCLUSION: Characterization of outcomes across a network of databases yields insights into sensitivity and specificity trade-offs when definitions are altered. Outcomes should be thoroughly evaluated prior to use for background rates for their plausibility for use across a global network.

Type: Article
Title: Evaluating the impact of alternative phenotype definitions on incidence rates across a global data network
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1093/jamiaopen/ooad096
Publisher version: https://doi.org/10.1093/jamiaopen/ooad096
Language: English
Additional information: © The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Keywords: algorithms, electronic health record, incidence study, phenotype
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/10183673
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