DATA-DRIVEN OPTIMIZATION IN PHARMACY OPERATIONS: A PRESCRIPTION FOR ENHANCED PATIENT CARE

Abstract

The convergence of patient care and business efficiency in community pharmacies through a Comprehensive Datafication Approach marks a transformative journey toward enhanced healthcare services and operational effectiveness. The aim of this study was to examine diverse perspectives on datafication, AI, and emerging technologies in healthcare, with a particular focus on optimizing community pharmacy operations. The implementation of a Comprehensive Datafication Approach in community pharmacies significantly impacts overall operational efficiency and patient care outcomes. The strict criterion mandates studies to report outcomes related to patient care, business efficiency, or operational metrics, ensuring selected literature aligns cohesively with research objectives, providing a robust basis for exploring dimensions associated with optimizing community pharmacy operations through datafication. Drawing from multiple studies, our exploration encompasses the challenges and potentials inherent in the integration of digital technologies. As we delve into the optimization of community pharmacy operations through AI, these diverse perspectives contribute to a nuanced understanding of the challenges and opportunities in data-driven healthcare transformation. The integration of AI necessitates ethical considerations, inclusive practices, and a balance between optimization goals and individual rights, ensuring a holistic approach to healthcare datafication.

                

Peer Review History:

Received 2 October 2024;   Reviewed 17 November; Accepted 24 December; Available online 15 January 2025

Academic Editor: Dr. Emmanuel O. Olorunsola, Department of Pharmaceutics & Pharmaceutical Technology, University of Uyo, Nigeria, olorunsolaeo@yahoo.com

Average Peer review marks at initial stage: 6.5/10

Average Peer review marks at publication stage: 7.0/10