A Multi-Criteria Decision Analysis Framework to Explore Determinants of Catastrophic Healthcare Expenses

Bibliographic Data

ID13024915
AuthorsSavita Kumari Jarika (0009-0006-8149-5587, Ranchi University), S D Choudhury (0000-0001-9890-8364, Ranchi University), Sanjib Biswa (0000-0002-9243-2403, corresponding author), Biplab Kr Biswas (0000-0001-5869-4998), Prasenjit Chatterjee (0000-0002-7994-4252, Széchenyi István University)
Year2025
Volume15
Issue12
Pages353-353
Publication date2025-12-15
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueSocieties (JOURNAL)
Journal identifiersISSN: 2075-4698 • E-ISSN: 2075-4698
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/soc15120353
OpenAlexW4417329350
LanguageEN
References cited72

Despite significant advances in the medical sciences, out-of-pocket (OOP) healthcare costs have remained a concern, especially for lower-middle-class and poor people. The current study aims to investigate the critical factors that notably contribute to catastrophic healthcare expenses (CHCEs). To this end, the ongoing research is conducted through two phases. The first phase aims to identify the key determinants of CHCEs through expert and household evaluations. A multi-criteria decision analysis (MCDA) framework using the FullEX method is developed to analyze expert and household opinions. In the second phase, the experts investigate the hierarchical relationships among key determinants. Interpretive structural modeling (ISM) and MICMAC analysis are carried out to examine the structural relationships among the determinants. The findings of the FullEX analysis reveal that experts and households are in consensus. It is found that low-income level, number of dependable members, frequent birth rate, high child mortality, and lack of job security and risk pooling mechanisms notably contribute to the higher CHCEs. The ISM analysis indicates the strong driving power of income, education, and job security, leading to disparities in rural economic conditions, reflecting the need for holistic development. The MICMAC analysis confirms the hierarchical relationships among the key determinants of CHCEs. The findings necessitate formulating an inclusive strategy to reduce financial distress and improve the healthcare outlook for rural households, leading to sustainable development

Decision analysis · Financial distress · Health care · Key (lock · Pooling · Scenario analysis · Situation analysis · Global Maternal and Child Health · Healthcare Policy and Management · Healthcare Systems and Reforms

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