2026 Southeastern Residency Conference

Background: Auto-verification of medication orders is a critical clinical decision support function intended to improve efficiency while maintaining medication safety. Following a large health system merger, variation in auto-verification protocols may occur, introducing potential safety risks and workflow inefficiencies. This project was initiated prior to the January 1, 2026 update of Joint Commission standards and is therefore based on the previous version, which specified that blanket auto-verification of select medications is not acceptable and required pharmacist review of all medication orders, with limited exceptions as outlined in the “Notes” section of MM.05.01.01.

Objectives: This study aims to describe current auto-verification practices across Prisma Health post-merger, identify discrepancies in clinical appropriateness, and assess potential impacts on medication safety and pharmacist workload, including the potential for increased pharmacist full-time equivalent (FTE) needs if inappropriately auto-verified orders were incorporated into routine verification workload, while ensuring alignment with Joint Commission standards in effect at the time of project initiation.

Methods: A retrospective, descriptive analysis was conducted using Epic SlicerDicer to extract deidentified auto-verified medication orders from December 2025 across Prisma Health. As this project was initiated prior to the January 1, 2026 update to Joint Commission standards, orders were classified as appropriate based on MM.05.01.01. Under these standards, orders were considered appropriate if they fell within specific scenarios in which prospective pharmacy review is not required, as outlined in the “Notes” section. This includes settings such as emergency departments and hospital radiology services, as well as hospital-affiliated ambulatory radiology. Primary outcomes include the proportion of appropriate versus inappropriate auto-verified orders, with subgroup analyses by order type, provider type, and identification of high-alert medications. Secondary outcomes will estimate pharmacist workload impact associated with inappropriate auto-verification.

Results:  A total of 84,310 medication orders were auto-verified across Prisma Health from December 1–31, 2025. Of these, 57,062 orders (68%) were classified as appropriate for auto-verification based on Joint Commission–defined exceptions that were in effect at the time of project initiation. Appropriate orders were most commonly associated with Emergency Medicine (n = 45,743), followed by Radiology (n = 6,510), inpatient diagnostic (n = 2,891), ASC radiology (n = 1,884), and ASC diagnostic services (n = 34).
A total of 27,248 orders (32%) were deemed inappropriate for auto-verification. Among these inappropriate orders, the most frequently represented medication categories were fluids, analgesics, gastrointestinal agents, diagnostic agents, and anesthetics.
High alert medications accounted for approximately 22,000 auto-verified orders during the study period. Of these, an estimated 3,900 occurred in Ambulatory Surgery Center settings and approximately 18,000 occurred in inpatient settings.
Analysis by provider type could not be completed due to limitations in data availability and will be addressed in the study’s limitations.
Sites with meaningful staffing impact included GMH (1.7 FTE), Greer (0.3 FTE), and Patewood (0.2 FTE). The top five sites contributed approximately 77% of total workload associated with inappropriate auto-verification, with GMH accounting for 40% alone.

Conclusions: Post-merger variability in auto-verification practices resulted in a substantial proportion of medication orders being inappropriately auto-verified, including high-alert medications. These findings highlight opportunities to standardize auto-verification protocols to ensure safe medication practices. Targeted interventions at high-impact sites may significantly reduce inappropriate auto-verification, improve medication safety, and optimize pharmacist workload.