Over the last few decades, Ghana has implemented health sector reforms to improve health care access in alignment with Sustainable Development Goal 3. However, Ghana’s health sector continues to face challenges alongside mounting healthcare needs and persistent overspending of the healthcare budget. These challenges are exacerbated by recent cuts in external aid to Ghana, illustrating the importance of effective health sector priority-setting (HSPS). HSPS describes the process of determining how to best allocate resources to maximize population health outcomes among various alternative, competing health needs and interventions. Although Ghana has a history of priority-setting initiatives, there is no authoritative source on the current landscape of HSPS in Ghana. This study sought to fill this gap by offering a detailed analysis of current HSPS processes at the national level in Ghana, focusing on the use of data and analytics in informing HSPS. The study uses data from key informant interviews and a literature review to provide information on the processes and institutions involved in HSPS in Ghana, data and analytics used in HSPS, and successes, challenges, and recommendations.

Findings show several good aspects of HSPS in Ghana, including demonstrated political commitment and attempts at a bottom-up approach. However, challenges remain, including political and development partner influences, lack of a nationally owned, unified national health information system (HIS) infrastructure, and a lack of capacity and demand for advanced analytics in decision-making. Recommendations include developing a sustainable, integrated HIS that is nationally owned, developing data and analytic capacity within the health sector, improving participation of communities and subnational governments in priority-setting, facilitating closer collaboration between wider sectoral and program-specific priority-setting, and committing to a long-term domestic financing plan for healthcare.

The authors have declared no competing interest.

This work was supported, in whole or in part, by the Gates Foundation [INV-061337]. The conclusions and opinions expressed in this work are those of the authors alone and shall not be attributed to the Foundation. Under the grant conditions of the Foundation, a Creative Commons Attribution 4.0 License has already been assigned to the Author Accepted Manuscript version that might arise from this submission. Please note works submitted as a preprint have not undergone a peer review process.

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