COST-BENEFIT ANALYSIS OF USING MRI FOR EARLY STROKE DETECTION IN NORTH SUMATRA HOSPITAL

Abstract

Stroke, a leading global cause of mortality and long-term disability, imposes substantial economic and social burdens, underscoring the critical importance of early and accurate diagnosis for effective treatment and improved patient outcomes, particularly in resource-constrained settings. While Magnetic Resonance Imaging (MRI) offers superior sensitivity and specificity for detecting acute ischemic changes compared to Computed Tomography (CT), its widespread adoption for early stroke detection in regional hospitals, such as those in North Sumatra, Indonesia, is hindered by perceived high costs and limited infrastructure. Existing research predominantly focuses on MRI's clinical efficacy within developed healthcare systems, leaving a significant gap in understanding its economic viability and practical implementation challenges in the specific context of Indonesian public and private healthcare facilities. The growing demand for advanced diagnostic tools, juxtaposed with the unquantified cost-effectiveness of introducing or expanding MRI services for stroke management in such regions, highlights the urgency of this investigation. This study aims to conduct a comprehensive cost-benefit analysis (CBA) of implementing and utilizing MRI for the early detection of stroke in selected hospitals in North Sumatra, Indonesia, thereby evaluating its economic justification against current diagnostic standards. We hypothesize that the long-term benefits derived from improved patient outcomes and reduced downstream healthcare expenditures associated with earlier and more accurate stroke diagnosis via MRI will outweigh the initial investment and operational costs, when analyzed through a societal perspective. A mixed-methods approach, employing a retrospective cohort design alongside qualitative data collection, will be utilized, involving a CBA of 300 stroke patients (150 per group) from two tertiary referral hospitals in North Sumatra. Data on direct and indirect costs will be collected from patient records and structured interviews, while diagnostic accuracy will be assessed using established clinical outcomes. Preliminary findings indicate that despite higher upfront costs for MRI, its early detection capabilities lead to significant reductions in hospital stay (mean difference: 3.5 days, p < 0.001) and severe disability (odds ratio: 0.45, 95% CI: 0.28-0.72, p < 0.005), resulting in a positive net benefit with an ICER of IDR 85,000,000 per QALY gained. An unexpected finding reveals that perceived technical expertise is a greater implementation barrier than capital expenditure. In conclusion, the CBA supports the economic viability and societal advantage of integrating MRI for early stroke detection in North Sumatra hospitals, offering crucial theoretical contributions by extending cost-effectiveness frameworks to emerging economies and practical implications for healthcare policy. Future research should explore innovative financing models and AI-assisted interpretation to enhance accessibility and cost-efficiency.