PREDICTIVE MODEL OF HEALTH FACILITIES AND DATA FOR QUALITY IMPROVEMENT (QI) IN MATERNAL AND NEONATAL MORTALITY REDUCTION IN JEMBER REGENCY

Background: Maternal and neonatal mortality remain serious global health problems, particularly in developing countries such as Indonesia. In 2020, the WHO recorded 287,000 maternal deaths and 2.4 million neonatal deaths. Jember Regency has the highest maternal mortality rate in East Java. This study analyzes the influence of health facilities and data on the implementation of Quality Improvement (QI) in reducing maternal and neonatal mortality. Method: This research employed a quantitative approach with a cross-sectional design, involving 105 pregnant women as respondents. Data analysis was conducted using Structural Equation Modeling (SEM) with LISREL. The research model involved three latent variables: health facilities, data, and QI implementation. Result: The Confirmatory Factor Analysis (CFA) results indicated that all indicators were valid and reliable. The SEM model demonstrated a good fit based on RMSEA, CFI, and TLI indices. Structural analysis revealed that health facilities had no significant effect on QI implementation (t-value = 0.37), whereas data had a significant and dominant effect (t-value = 4.99; coefficient = 0.88). Conclusion: These findings indicate that the mere existence of health facilities is insufficient without quality services and an effective referral system. In contrast, data play a crucial role in evidence-based decision-making, monitoring, and evaluation within the QI framework. Strengthening the data system is therefore essential to maximize maternal and neonatal health programs