Intuitionistic Fuzzy Best-Worst Method for Multi-Criteria Decision Making with Application in Health Care Resource Allocation

Abstract

In the health care industry, decision-making is critical for determining the most efficient use of limited resources. Multi-criteria decision-making is a significant area that has been used to solve complex problems. To construct an accurate, adaptable, and sustainable framework for decision-making, an intuitionistic fuzzy best-worst method for multi-criteria decision-making in healthcare resource allocation is being developed. To understand the resource allocation mechanisms in different hospitals, the proposed methods employ a pairwise comparison of seven main criteria: infrastructure, consultancy time, paramedics, hospital stay, healthcare resource allocation, healthcare professionals' satisfaction, and improvements in resource allocation. The weights calculated from the intuitionistic fuzzy best-worst method indicate that health professional satisfaction is the best criterion, whereas the consultancy time is the worst. The goal of this approach is to effectively handle the inherent ambiguity, complexity, and uncertainty that define problems with healthcare resource allocation. This methodology has a wide range of applications, including: hospital resource management, prioritizing patient care during peak times or emergencies such as pandemics, budgeting and financial planning, evaluating the cost-effectiveness of new treatments or technologies, public health planning, planning and executing community health interventions, strategic planning, and policy making.