Obstacle analysis for implementing civil helicopter emergency medical service in Thailand as a low and middle-income country: An integrated Delphi-WING-ISM under q-rung orthorpair fuzzy approach

Abstract

The implementation of Civil Helicopter Emergency Medical Services (CHEMS) in low- and middle-income countries (LMICs), such as Thailand, faces a range of complex, interrelated challenges. This study aims to systematically identify and analyze the critical obstacles to CHEMS deployment using an integrated decision-support framework that combines the Delphi method, the Weighted Influence Non-linear Gauge System (WINGS), and Interpretive Structural Modeling (ISM) under a q-rung orthopair fuzzy set ( q -ROFS) environment. The q -ROFS framework enhances uncertainty handling in expert evaluations by capturing hesitation and degrees of agreement more effectively than traditional fuzzy logic approaches. Through expert consensus via Delphi rounds, nine key obstacles to CHEMS implementation are identified, including regulatory gaps, infrastructure limitations, coordination inefficiencies, and resource constraints. The WINGS method is applied to quantify the influence and dependence of each barrier, enabling the development of a total strength–influence matrix. ISM is subsequently used to construct a multi-level hierarchical model, revealing that regulatory support and compliance and lack of infrastructure serve as root-cause obstacles exerting significant influence on the system. In contrast, barriers such as shortage of skilled personnel and lack of telemedicine integration are identified as effect-level challenges. The results provide both theoretical insights into the structural interdependencies among implementation barriers and practical implications for prioritizing policy, managerial, and infrastructure interventions. This study offers a roadmap for phased CHEMS implementation in LMICs, emphasizing the importance of addressing foundational systemic issues to ensure operational sustainability and enhanced emergency medical response capacity.