Human Resource Forecasting as a Predictor of Perceived Health Service Delivery in Selected Districts of Central Uganda
Peter Kaddu, Regis Zombeire & Nazarious Rukanyangira
Department of Public Administration and Management
Nkumba University, Uganda
https://orcid.org/0009-0009-5036-1596
Email: kaddupeter2@gmail.com
Abstract: Human resource forecasting is a critical component of workforce planning because it enables healthcare organizations to anticipate staffing requirements and sustain effective service delivery. Despite ongoing workforce planning initiatives, public health facilities in Uganda continue to experience staffing shortages, workforce imbalances, and delayed replacement of exiting personnel, which may undermine service delivery outcomes. This study examined the relationship between human resource forecasting and perceived health service delivery in selected districts of Central Uganda. A convergent mixed-methods design was employed. Data were collected from 150 health workers through questionnaires and from 33 key informants through interviews, focus group discussions, and document review. Quantitative data were analysedusing descriptive statistics, Pearson correlation, and simple linear regression, while qualitative data were analysedthematically. Findings revealed a statistically significant positive relationship between human resource forecasting and perceived health service delivery (r = .386, p < .001). Regression analysis further indicated that human resource forecasting significantly predicted perceived health service delivery (B = .648, β = .386, t = 5.091, p < .001), explaining 14.9% of the variance in service delivery outcomes. Qualitative findings showed that forecasting enhanced service delivery through strategic anticipation of staffing needs, workforce specialisation, continuity of care, equitable workload distribution, and professional development opportunities. The study concludes that human resource forecasting significantly influences perceived health service delivery. It recommends institutionalising workforce forecasting within district health planning systems, strengthening workforce information systems, and conducting regular staffing forecasts to improve healthcare service delivery.
