Yeni Rimadeni, Hizir Sofyan, Safrizal Rahman, Setia Pramana, Muhammad Ikhwan
This qualitative case study examines the management practices and challenges of medical logistics following the 2016 Pidie Jaya earthquake in Indonesia. Through in-depth interviews, observations, and focus group discussions with key informants from the Pidie Jaya Health Office and Primary Health Care Pharmaceutical Installations, the study investigates 14 critical aspects of medical logistics preparedness and response. The findings indicate that while standard operating procedures are adhered to for routine medical logistics management, there is a lack of specific planning for earthquake scenarios. An innovative regional planning approach involving 18-month advance procurement has been effective in managing minor disasters. However, the study underscores the need for more comprehensive disaster-specific medical logistics planning, particularly for large-scale events like earthquakes. This paper contributes to the limited literature on optimizing medical logistics in disaster response within developing country contexts and provides practical insights for policymakers and practitioners. Despite this, the transferability of the findings may be constrained by the single case study design and the reliance on qualitative methods. Future research should explore the applicability of these lessons to other disaster contexts and use mixed-methods approaches to enhance the generalizability of the findings. © 2024, Success Culture Press. All rights reserved.
Graduate School of Mathematics and Applied Science, Universitas Syiah Kuala, Banda Aceh, 23111, Indonesia; Polytechnic of Health, Ministry of Health, Aceh, 23231, Indonesia; Department of Statistics, Universitas Syiah Kuala, Banda Aceh, 23111, Indonesia; Faculty of Mathematics and Natural Sciences, Universitas Syiah Kuala, Banda Aceh, 23111, Indonesia; Department of surgery sub division of Orthopedic and Traumatology, Faculty of Medicine, Universitas Syiah Kuala, Banda Aceh, 23111, Indonesia; Department of Computational Statistics, Institute of Statistics, Jakarta, 13330, Indonesia; Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Syiah Kuala, Banda Aceh, 23111, Indonesia
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