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Robotic Process Automation as an EHR Reliability Layer for Inpatient Care Gaps: Automating Virtual Huddles Using
Jared Silberlust1, Tiffany Rose Martinez2, Katerina Andreadis2
1NYU Langone Health, MCIT Department of Health Informatics, New York, United States, New York.
Objectives:
This case report describes the implementation and outcomes of robotic process automation (RPA) interventions used as an electronic health record (EHR)-based reliability layer for 2 inpatient quality initiatives: First Contact Provider (FCP) assignment and admission medication reconciliation (AMR) within 24 hours.
Methods:
RPA bots were created to support 2 inpatient quality initiatives by monitoring EHR patient lists for predefined care gaps: missing FCP assignment and incomplete AMR. When a gap was identified, the bot opened the patient chart, initiated a secure-message conversation with frontline clinicians and quality improvement champions, and generated operational reports to support follow-up. Chi-square tests compared FCP before (September 1, 2022-February 28, 2023) versus after implementation (March 1-August 31, 2023), and AMR before (December 1, 2022-May 31, 2023) versus after implementation (June 1-November 30, 2023).
Results:
For FCP, the bot identified 9,361 encounters without an assignment across 118 hospital units and generated 14,984 secure-message conversations linking 17 quality improvement champions with 2,336 providers. FCP assignment improved from 81.2% (5,096,966/6,269,754 patient-hours) to 88.5% (5,858,442/6,619,047; p < 0.001). For AMR, the bot identified 10,680 incomplete reconciliations across 131 hospital units and generated 21,502 secure-message conversations linking 208 quality improvement champions with 3,234 unique providers. Timely completion improved from 86% (33,886/39,489 encounters) to 96% (39,790/41,624; p < 0.001).
Conclusions:
Implementation of RPA was associated with substantial improvement in FCP assignment and timely AMR completion. Initiating a bot-enabled secure-chat "virtual safety huddle" may provide a practical EHR reliability layer for rule-based inpatient care gaps.
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