Influence of health management information systems on decision-making in a level 5 public hospital in Tharaka Nithi County, Kenya

Abstract

The effective utilization of Health Management Information Systems (HMIS) plays a pivotal role in evidence-based decision-making in healthcare. In Kenya, the rollout of digital platforms such as Afya Kenya, under the Digital Health Act 2023, underscores the government’s commitment to improving data-driven planning and service delivery. However, limited evidence exists on how healthcare workers, particularly in public facilities, use HMIS for operational and strategic decisions. The study examined the influence of HMIS on decision-making among healthcare workers at Chuka County Referral Hospital, a Level 5 public hospital in Tharaka Nithi County, Kenya. The objectives were to evaluate the technical, behavioral, organizational, and environmental factors influencing the use of HMIS data for decision-making. It was anchored on the PRISM Framework and Theory of planned behavior, which together provided a structured approach to understanding the enablers of data-driven decision-making in healthcare. A descriptive cross-sectional design was employed. The study adopted a census method, targeting all 250 departmental heads and clinical staff involved in data management and decision-making within the facility. Data were collected using semi-structured questionnaires and analyzed using descriptive statistics, Pearson correlation, and multiple linear regression. Correlation results showed, organizational factors had the strongest correlation (r = 0.682), followed by behavioral (r = 0.634), technical (r = 0.501), and environmental (r = 0.372) factors. However, regression analysis revealed a more nuanced picture by identifying which factors significantly predict actual HMIS data use. It showed that organizational factors were most statistically significant predictors (β = 0.476, p < 0.05) in strategic and (β = 0.521, p < 0.05) in operational decision making. The study concluded that while technical infrastructure and staff attitudes are important, organizational leadership, policies, and governance structures are the most critical drivers of effective HMIS data utilization. Recommendations made include strengthening internal leadership and accountability mechanisms, enhancing system interoperability, providing regular staff training, and developing policy frameworks that decentralize data-driven decision-making. These findings offer practical guidance for healthcare managers and policymakers seeking to optimize HMIS adoption for improved healthcare delivery.