Digital Interoperability and Diagnostic Redundancy Reduction: Cost-Efficiency Evidence from Indonesian Vertical Hospitals - Ramli (Journal of Health Service Administration and Hospital Management, 2026)
Digital transformation through Indonesia's SatuSehat platform aims to mitigate medical data fragmentation, which historically contributed to excessive diagnostic redundancy within referral institutions. This study evaluates the impact of data interoperability on laboratory operational cost-efficiency and the reduction of duplicative investigations in Vertical Hospitals. Employing a retrospective observational design, the research analyzed secondary datasets from 14 national referral Vertical Hospitals across Java and Bali, encompassing a sample population of 12,450,000 laboratory transactions from the 2023–2024 period. Data were synthesized from the SatuSehat national dashboard, Audited Financial Reports (LKA), and BPJS Health claim records, focusing on variables such as redundant test volumes (categorized by LOINC codes) and realized reagent expenditures. The findings reveal a significant 11.21% decline in laboratory examination volumes alongside an 11.27% improvement in medical consumable efficiency, totaling IDR 54.30 Billion in fiscal savings. Inferential analysis using a paired-sample t-test confirmed a highly significant reduction in operational costs following integration (t = 8.42, df = 13, p < 0.001, 95% CI [0.78, 0.92]), with a substantial effect size (Cohen's d = 1.15). Furthermore, regression modeling indicates that every 1% reduction in redundancy contributes to a 0.85% gain in budgetary efficiency ( ,  ). These results imply that SatuSehat functions as a high-precision fiscal stabilizer that directly correlates clinical interoperability with the mitigation of systemic financial leakage in the Indonesian health sector. The study concludes that strengthening national digital data governance effectively optimizes healthcare resources and recommends the integration of Artificial Intelligence-based clinical decision support systems for future investigative frameworks.