Optimizing the Medication Trajectory: A Multidisciplinary Framework for High-Reliability Prescribing, Administration, and Pharmacovigilance
Abstract
Background: Medication errors persist as a leading cause of preventable patient harm globally, despite advancements in healthcare technology and protocols. These errors occur not within isolated silos but across a complex, interdependent pathway involving multiple disciplines. Aim: This narrative review aims to synthesize current evidence (2015-2024) on the integrated, interdisciplinary process of medication management, focusing on strategies for error reduction and enhanced patient safety from prescription through to monitoring.
Methods: A comprehensive literature search was conducted across PubMed, Scopus, CINAHL, and Web of Science databases. The included literature comprised peer-reviewed articles, systematic reviews, meta-analyses, and key grey literature from professional organizations, published between 2015 and 2024. Thematic analysis was used to synthesize findings across eight core healthcare domains: Pharmacy, Medical Laboratories, Nursing, Radiology, Health Services & Hospital Management, Health Assistant/Health Security, Disaster Management, and Hospital Management. Results: The review identifies that high-reliability is achieved not through individual excellence but through seamless interoperability between disciplines. Critical nodes include technology-supported prescribing, interdisciplinary medication reconciliation, diagnostic stewardship informing therapy, and robust post-administration surveillance. Fragmentation in communication, information system incompatibility, and inadequate cross-disciplinary training remain significant vulnerabilities. Conclusion: A truly high-reliability medication pathway requires a systemic, socio-technical approach that embeds safety culture, interoperable health information technology, and structured interdisciplinary collaboration at every stage. Future efforts must prioritize integrated system design over domain-specific optimization.
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Authors
Copyright (c) 2024 Waleed Abdullah Alhabeeb, Layth Talal Raji Alabdali, Hassan Abdullah Hassan Kuriri, Meshari Rushaydan Almutairi, Abdulmajeed Abdulrahman Alanazi, Noof Makrb Alfuhaigi, Najah Atallah Alanazi, Ibrahim Mohammed Abddullah Safhi, Hassan Ali Hassan Albariqi, Jaber Abdullah Ahmed Alkhaldi, Mohammed Mujahid Ateeq Alkuwaykibi, Mazen Khulaif Buthul Alruwaili
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