IEEE Access (Jan 2024)
Development of a Hybrid AHP-TOPSIS Decision-Making Framework for Technology Selection in Hospital Medication Dispensing Processes
Abstract
Hospitals play a crucial role in delivering high-quality patient care, and the healthcare industry is experiencing significant changes driven by the integration of advanced technology. This integration aims to enhance patient care, streamline operations, and minimize errors. Therefore, this study seeks to propose a comprehensive decision-making framework for selecting appropriate technologies, focusing on the medication dispensing process within hospital settings. Through an extensive literature review and expert input, seven critical criteria for technology adoption in hospitals have been identified. Additionally, the study considers the Pick-to-Light system, Carousel Storage System, and Robotic Dispensing System as alternative technologies for integrating medication dispensing processes, with a focus on enhancing labeling, picking, and packing activities. The evaluation involves participants from five tertiary care hospitals in Thailand. The Analytic Hierarchy Process (AHP) is used to assess the relative importance of criteria, followed by the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) for technology selection. The analysis results, including criteria weights and technology selection, are presented separately for each hospital case and overall. The top-three criteria identified as having high priority weights across hospitals are budget and funding support (BF) (0.329), staff technological proficiency levels (TP) (0.147), and leadership support (LS) (0.128). These findings can guide healthcare organizations in making informed decisions during technology implementation, particularly in improving medication dispensing processes. The study identifies the “Pick-to-Light” technology as a suitable solution across all hospital cases, as it can streamline dispensing processes, improve accuracy, and enhance overall operational efficiency. This research, along with the proposed decision-making framework, contributes valuable insights for healthcare institutions seeking to effectively select and integrate technologies, ultimately leading to improved outcomes in hospital medication services.
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