Health Workers’ Perceptions on Data-informed Decision-Making practices in Primary Health Care Units at Awi Zone, Northwest Ethiopia

Abstract

Background: Data-informed decision making is influenced by organizational, technical, and behavioral factors. Behavioral factors are the major contributing factors for data-informed decision-making practices. This study aimed to explore health workers’ perceptions of data-informed decision making at primary health care units in Awi zone.
Method: A cross-sectional qualitative study was undertaken to explore health workers’ perceptions on the barriers of health data-informed decision-making practices. Eleven healthcare workers were purposively selected from primary hospitals, health centers and health posts. Medical doctors, nurses, midwifes and health extension workers were selected as key informants for the in-depth interview. The selected healthcare workers were asked about their perceptions that affect health data use practices. The data obtained was analyzed through thematic analysis using Open Code software. Analysis was performed using three themes namely, organizational, behavioral, and technical barriers of data-informed decision making.
Results: All the health care workers including health extension workers utilized a data-informed decision-making practice at least once during their point of care. Five of the eleven key informants reported their data-informed decision-making practice as reviewing quality of facility data, while none of them reported data-informed decision-making practices for their monthly performance monitoring. Behavioral factors included negligence, workarounds, and skill gaps. Organizational factors included staff turnover and shortage of recording tools. Technical factors included high workloads which lead to data error and paper-based systems were considered major barriers to data-informed decision-making practices.
Conclusion: Data-informed decision-making practices were low at primary health care units. Behavioral, organizational, and technical factors contributed to the decreased use of data.