| dc.description.abstract | A health management information system (HMIS) is a data collection system that supports planning, management, and decision-making in health facilities and organizations. A functioning HMIS is essential for health system strengthening, but the effective use of HMIS data for decision-making needs to be better documented. As such, this thesis investigates the practices of, enablers, and barriers to data use in Rwanda's HMIS. It documents data use practices across all health system levels and which factors enable and constrain local implementations. Rwanda has a well-established HMIS, building on a decade of experience with the DHIS2 platform, making it a suitable research place. The research was a qualitative case study, based on a four-week fieldwork in Rwanda, collecting data through interviews, observations, and participating in workshops and meetings. The analysis positioned the fieldwork findings as enablers or barriers to the constructs of an adapted Theory of Effective Use framework (TEU). The TEU examines what effective system use involves and what drives it. Rwanda HMIS supports data-driven decision-making. Stakeholders have high access to relevant health data, and the system collects comprehensive and local data that accurately represent health status and services. Decision-making heavily relies on HMIS information, facilitating program development, policy-making, and coordination. Best practices are actively shared, and significant resource adaptation is taking place. However, challenges include data fragmentation across platforms and outdated population denominators, impacting accuracy. Insufficient capacity building and limited supervision hinder the effective use of data. The thesis offers contributions in four areas: (1) It adds to the literature on HMIS strengthening and data-driven decision-making in LMICs by providing valuable insights and empirical evidence from Rwanda HMIS. (2) This research helps advance the TEU by adapting it to a new context. Future researchers and practitioners can use this as a template to assess the effective use of an HMIS. (3) The findings help Rwanda further improve its already well-established HMIS practices by identifying the factors driving or hindering effective data use. (4) The thesis answers the HISP project call for action to document the routine use of DHIS2 data, providing real-world examples of data use practices and the challenges faced, direct feedback from interviewees, and a framework (TEU) that can be utilized in future research projects. Keywords: data use practices, HMIS strengthening, data-driven decision-making, Theory of Effective Use, Rwanda HMIS, DHIS2 | eng |