DOI: 10.1093/ajhp/zxad329 ISSN: 1079-2082

A facility-level self-assessment of Autonomous Pharmacy Framework levels

Nicholas Goldsmith, Mark Sullivan, Sabrina W Cole, Gee Mathen, Nikki Polis, Deepak Sisodiya, Trish Tanner, Jeff Wagner, Allen J Flynn
  • Health Policy
  • Pharmacology



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The objective of this study was to understand at what level of the Autonomous Pharmacy Framework facilities are operating, in terms of the current state of data collection and analysis in the medication-use process, and to gather insights about systems integration and automation use.


The Autonomous Pharmacy Advisory Board, a group of chief pharmacy officers and operational leaders, developed a self-assessment instrument based on the previously published Autonomous Pharmacy Framework, made the self-assessment instrument available via the internet, and reviewed respondents’ self-reported results. The data collection period for the survey started in March of 2021 and ended in January of 2023.


A total of 119 facility-level self-assessments were completed and analyzed. On a scale of 1 to 5, where 1 represented little or no data-driven automation with lots of manual tasks and 5 represented the utmost data-driven automation with few manual tasks, the average overall facility-level score was 2.77 (range, 1.38-4.41). Results revealed slight variance by facility bed capacity. Much more variation was found in the degrees to which individual facilities have automated core processes like inventory management, intravenous medication preparation, and financial reporting.


As a baseline, this automation-focused facility self-assessment suggests that for essentially all health-system pharmacy facilities and their larger organizations, a substantial body of work needs to be done to further develop and upgrade technology and practice in tandem, greatly expand data collection and analysis, and thereby achieve better operational, financial, and clinical outcomes. Significant advancements are needed to arrive at the highly reliable, highly automated, data-driven medication-use process involving few repetitive manual tasks envisioned in the Autonomous Pharmacy Framework.

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