Linking Demand Forecasting to Operational Outcomes: A Cross-Sectional Supply Chain Analysis of Kenyan Public Hospitals

Operational performance within Kenyan public hospitals has become an issue of growing public and policy concern, particularly in the context of frequent medicine stock imbalances and service delivery inefficiencies. Persistent challenges in balancing drug overstocking and stock-outs point to weaknesses in demand planning within hospital supply chains. This study examines the relationship between demand forecasting practices and operational outcomes in public hospitals in Kenya, using evidence from Siaya County. The research is anchored on the Resource-Based View (RBV) and Network Perspective Theory to explain how internal forecasting capabilities and inter-organizational supply chain relationships influence hospital performance. A cross-sectional survey design was employed involving personnel drawn from procurement, pharmacy, stores, and administrative departments across six public hospitals. Data were analyzed using descriptive statistics, correlation analysis, and linear regression modelling. The findings reveal a strong and statistically significant positive relationship between demand forecasting practices and operational outcomes (β = 0.876, p < 0.05). The model explains approximately 70.1% of the variation in operational performance (R² = 0.701). These results suggest that hospitals that institutionalize structured forecasting practices within their supply chain systems achieve improved operational efficiency and enhanced service delivery outcomes. The study concludes that strengthening forecasting capabilities is critical for improving drug availability and reducing service disruptions in public healthcare systems. The paper recommends adoption of data-driven forecasting approaches, strengthened supply chain coordination, and integration of digital health logistics systems to enhance healthcare service delivery in Kenya.