Scenario Planning for Health Supply Chain Integration with Intuitive Fuzzy Logic Approach

Introduction and Objectives: Supply chain integration in the health sector is one of the key challenges that can have a significant impact on improving the quality of healthcare services and increasing the resilience of health systems. Given the complex and dynamic nature of this key supply chain, the use of traditional methods for its management faces limitations. Scenario planning has been proposed as an efficient and effective method for analyzing uncertainties and developing optimal solutions in different situations. In this study, a combination of scenario planning and intuitive fuzzy logic has been used to promote the integration of the health supply chain. The aim of the present study is to provide a comprehensive analytical model for developing appropriate strategies in conditions of complex uncertainties in the decision-making space. Methods: The main question in the present study is how to provide a set of efficient scenarios for integrating the health supply chain using the scenario-based method? For this purpose, this study uses a combined approach based on scenario analysis and intuitive fuzzy logic-based decision-making. First, through environmental analysis and expert opinions, key uncertainties in the health supply chain were identified, including economic sanctions and inflation. Then, based on these uncertainties, four possible scenarios were developed. In the next step, intuitive fuzzy logic was used to evaluate these scenarios, which allows for the consideration of the degree of uncertainty and instability in decision-making. Finally, the effects of these scenarios on health supply chain performance indicators were analyzed using an optimization model. Findings: The results showed that economic sanctions and inflation are two key factors affecting health supply chain performance that can disrupt the supply of medical equipment, increase operating costs, and reduce the efficiency of the healthcare system. Based on these uncertainties, four different scenarios were analyzed, which are: removal of economic sanctions and low inflation, presence of economic sanctions and low inflation, presence of economic sanctions and high inflation, and removal of economic sanctions and high inflation. The results of the analysis show that the strategy of extensive cooperation between stakeholders and the development of digitalization can help reduce the negative effects of sanctions and inflation. In addition, the proposed model showed that the use of modern information technologies and improved communication between suppliers and health centers has a positive effect on increasing the resilience of the supply chain. Also, the findings showed that the proposed model, by reducing the effects of uncertainty, reduces operating costs, increases the speed of response in critical situations, and improves the quality of health services. Comparing the results of the intuitive fuzzy logic method with other decision-making methods also showed that this model has higher accuracy in analyzing uncertainty scenarios. Conclusion: This research showed that the combination of scenario planning and intuitive fuzzy logic can be used as an effective tool for managing uncertainty in the health supply chain. In addition to increasing the accuracy of decision-making, the use of this approach improves the flexibility and resilience of the supply chain in the face of economic crises and environmental changes. It is suggested that future research should consider the effects of other uncertainty factors, such as policy changes and technology-based developments, in modeling health supply chain integration.