Point of care randomization (POCR) engine: demonstration of a transportable clinical informatics technology that improves health systems' ability to conduct embedded clinical trials.
8 affiliations
- 1Division of General Internal Medicine and Health Services Research, David Geffen School of Medicine at UCLA, Los Angeles, CA 90049, United States.
- 2Department of Pathology and Laboratory Medicine, University of California Los Angeles, Los Angeles, CA 90095, United States.
- 3University of California Los Angeles David Geffen School of Medicine Department of Medicine Statistics Core, Los Angeles, CA 90024, United States.
- 4Division of Medical Informatics, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, United States.
- 5Health Information Technology, Information Services & Solutions, Medical Informatics, University of California Los Angeles, Los Angeles, CA 90095, United States.
- 6School of Medicine Technology Services, University of California San Francisco, San Francisco, CA 94143, United States.
- 7Research Informatics, University of California San Francisco, San Francisco, CA 94143, United States.
- 8Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94143, United States.
Abstract
We describe a new point of care randomization (POCR) engine developed at UCSF and implemented at UCLA that supports randomization of patients, encounters, clinics, or any other "object" in Epic, with programmable ratios, strata, and randomly varying block sizes. The feature, programmed in Caché, uses Epic rule infrastructure to implement inclusion criteria and generate and use blocks of randomization assignments. Configuration details, randomization assignments, and context information (including stratification variables) are stored in custom master files in Chronicles and exported to Clarity (Epic's reporting database). As a demonstration use-case, we conducted a pragmatic RCT of a provider-facing alert for short-interval (30-day) repeat HbA1c orders at UCLA Health. At the instant providers initiated a repeat order, the POCR engine silently enrolled and randomized patients, stratified by age and previous HbA1c, with randomly varying block sizes. During the 3-month study, 333 patients were enrolled. The total number of orders signed in the intervention arm (primary outcome) was 18/172 (10%) vs 104/161 (65%) in the control arm (Incidence Rate Ratio 0.16, 0.95 CI, 0.10-0.27). We successfully transported and deployed a new technology with the capability to instantaneously perform automated stratified block randomization. By performing eligibility assessment, enrollment, and assignment using programmable ratios, strata, and randomly varying block sizes, the POCR engine preserves internal validity while minimizing disruption to care, representing a substantive advance in informatics infrastructure for embedded randomized trials. The POCR engine is a transportable clinical informatics technology that transforms health systems' ability to conduct pragmatic clinical trials within the EHR.
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BibTeX
@article{sarkisian2026point,
title = {{Point of care randomization (POCR) engine: demonstration of a transportable clinical informatics technology that improves health systems' ability to conduct embedded clinical trials.}},
author = {Catherine Sarkisian and Khalda Ibrahim and Sitaram Vangala and Chad Wes Villaflores and Eric M Cheng and William Turner and Richard K Leuchter and Amy Machado and Julia Tabar and Jade A Verdeflor and Jory Purvis and Alina Goncharova and Mark J Pletcher},
journal = {JAMIA open},
year = {2026},
month = oct,
doi = {10.1093/jamiaopen/ooag209},
url = {https://europepmc.org/article/MED/42953877},
note = {CC BY},
}
RIS
TY - JOUR
TI - Point of care randomization (POCR) engine: demonstration of a transportable clinical informatics technology that improves health systems' ability to conduct embedded clinical trials.
AU - Catherine Sarkisian
AU - Khalda Ibrahim
AU - Sitaram Vangala
AU - Chad Wes Villaflores
AU - Eric M Cheng
AU - William Turner
AU - Richard K Leuchter
AU - Amy Machado
AU - Julia Tabar
AU - Jade A Verdeflor
AU - Jory Purvis
AU - Alina Goncharova
AU - Mark J Pletcher
PY - 2026
DA - 2026/10/28
JO - JAMIA open
DO - 10.1093/jamiaopen/ooag209
UR - https://europepmc.org/article/MED/42953877
AB - We describe a new point of care randomization (POCR) engine developed at UCSF and implemented at UCLA that supports randomization of patients, encounters, clinics, or any other "object" in Epic, with programmable ratios, strata, and randomly varying block sizes. The feature, programmed in Caché, uses Epic rule infrastructure to implement inclusion criteria and generate and use blocks of randomization assignments. Configuration details, randomization assignments, and context information (including stratification variables) are stored in custom master files in Chronicles and exported to Clarity (Epic's reporting database). As a demonstration use-case, we conducted a pragmatic RCT of a provider-facing alert for short-interval (30-day) repeat HbA1c orders at UCLA Health. At the instant providers initiated a repeat order, the POCR engine silently enrolled and randomized patients, stratified by age and previous HbA1c, with randomly varying block sizes. During the 3-month study, 333 patients were enrolled. The total number of orders signed in the intervention arm (primary outcome) was 18/172 (10%) vs 104/161 (65%) in the control arm (Incidence Rate Ratio 0.16, 0.95 CI, 0.10-0.27). We successfully transported and deployed a new technology with the capability to instantaneously perform automated stratified block randomization. By performing eligibility assessment, enrollment, and assignment using programmable ratios, strata, and randomly varying block sizes, the POCR engine preserves internal validity while minimizing disruption to care, representing a substantive advance in informatics infrastructure for embedded randomized trials. The POCR engine is a transportable clinical informatics technology that transforms health systems' ability to conduct pragmatic clinical trials within the EHR.
SN - 2574-2531
ER -