Page History
Algorithm Details
- Implements a loyalty cohort algorithm described and evaluated in
Klann, Jeffrey G., Darren W. Henderson, Michele Morris, Hossein Estiri, Griffin M. Weber, Shyam Visweswaran, and Shawn N. Murphy. 2023. “A Broadly Applicable Approach to Enrich Electronic-Health-Record Cohorts by Identifying Patients with
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Complete Data: A Multisite Evaluation.” Journal of the American Medical Informatics Association: JAMIA, August. https://doi.org/10.1093/jamia/ocad166.
- Developed from a regression equation validated in
Lin, Kueiyu Joshua, Gary E. Rosenthal, Shawn N. Murphy, Kenneth D. Mandl, Yinzhu Jin, Robert J. Glynn, and Sebastian Schneeweiss. 2020. “External Validation of an Algorithm to Identify Patients with High Data-Completeness in Electronic Health Records for Comparative Effectiveness Research
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.” Clinical Epidemiology 12 (February): 133–41.
- Written primarily by Darren Henderson with contributions from:
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- Jeffrey Klann, PhD; Michele Morris; Andrew Cagan; Barbara Benoit
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Outline of algorithm
The program accepts a cohort definition consisting of: patient ids with per-patient index_dates (the date at which patient loyalty is to be evaluated), the number of years to look backwards from the index date to evaluate each binary variable, and a number of control variables to alter the behavior of the summary table output (such as number of lookback years and whether demographic data are stored in the observation_fact table). Both the model coefficients and the ontology elements mapped to each variable are stored in database tables and can be customized at each site. Specifically, the tool performs the following steps:
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From supplementary data in Klann, Jeffrey G., Darren W. Henderson, Michele Morris, Hossein Estiri, Griffin M. Weber, Shyam Visweswaran, and Shawn N. Murphy. 2023. “A Broadly Applicable Approach to Enrich Electronic-Health-Record Cohorts by Identifying Patients with Complete Data: A Multisite Evaluation.” Journal of the American Medical Informatics Association: JAMIA, August. https://doi.org/10.1093/jamia/ocad166.
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The regression equation can be found in appendix table S1 in Lin, Kueiyu Joshua, Gary E. Rosenthal, Shawn N. Murphy, Kenneth D. Mandl, Yinzhu Jin, Robert J. Glynn, and Sebastian Schneeweiss. 2020. “External Validation of an Algorithm to Identify Patients with High Data-Completeness in Electronic Health Records for Comparative Effectiveness Research.
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