Optimization of Pharmacist Resources at a Community Internal Medicine Teaching Hospital: Development of a Tool Through Pharmacist and Physician Expert Panels

<b>Purpose:</b> Expansion of acute care clinical pharmacist roles requires pharmacy departments to optimize allocation of pharmacist resources. This study aimed to develop an objective resource optimization tool to rank clinical service needs to assign internal medicine pharmacist resources at a community hospital within an academic medical center health system. Additionally, this study aimed to collect and analyze physician expert opinion to supplement the pharmacist-developed tool. <b>Method:</b> A pharmacist expert panel was convened to determine patient characteristics necessitating additional pharmacist services. Retrospective electronic health record data were aggregated by patient characteristic categories and ranked by clinical services. Separately, a survey of attending physicians rated patient cases on the need for additional pharmacy services and provided rationale. Results of both panels were analyzed and compared to develop and strengthen the tool. <b>Results:</b> The pharmacist-developed tool included three patient characteristic categories: Patient Acuity, Critical Drug Monitoring, and Transitions of Care. An internal medicine teaching service scored highest for needing additional pharmacy services; surgery and urology resulted in lowest scores. Highest ranked cases surveyed by physicians were patients with more complex transitions of care, inpatient medication management, and disease state optimization. Comparing panels, 92.5% of physician comments were related to one of the three categories included in the pharmacist developed tool. Remaining comments fell within a new category, Patient Allergies. <b>Conclusion:</b> Pharmacists and physicians identified similar patient characteristic categories requiring more robust pharmacist services across internal medicine patients. Alignment of the two panels confirms the inputs used to develop the tool and increases confidence in its application for pharmacist resource optimization.