# Low use of data analytics for health sector priority-setting in Ghana: A case for strengthening analytical capacity

## TL;DR

This study finds that data analytics are underused in Ghana's health sector decision-making, and suggests ways to improve analytical capacity and coordination.

## Contribution

The paper provides a novel assessment of data analytics use in health sector priority-setting in Ghana through interviews and literature review.

## Key findings

- Ghana has some data systems and training programs but overall analytical capacity is low.
- Donor and political influences hinder effective data-driven health decisions.
- Interviewees recommend centralized coordination and training to improve data use.

## Abstract

Ghana has implemented health sector reforms to improve health care access in alignment with Sustainable Development Goal 3. However, Ghana’s health sector faces challenges including 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)—the process of determining how to allocate resources best to maximize population health outcomes among various alternative, competing health needs and interventions. Although Ghana has a history of HSPS initiatives, there is no authoritative source on the current landscape of HSPS in Ghana and on the use of data and analytics. Combining key informant interviews with an extensive literature review, this study aimed to provide an overview of current HSPS processes at the national level in Ghana, focusing on the use of data and analytics. Eight interviewees were selected from governmental health institutions, development partner organizations and academia through a combination of purposive and snowball sampling. Findings show some good practices regarding the use of data and analytics for HSPS in Ghana, including the existence of a routine health database for Ghana Health Service (GHS) facilities, existence of training programs on data collection for GHS staff and some use of subnational data for national-level decision making. However, many interviews showed that the use of data and analytics for HSPS was low mainly due to low analytical capacity within the GHS and MoH, donor and political influences on the process, and a fragmented health data system. Interviewees recommended the following to increase the use of data and analytics in HSPS: 1) increase training in data analytics and data-driven decision-making, particularly among senior-level staff in the GHS and Ministry of Health, 2) establish a centralized health research coordination agency, and 3) integrate and coordinate health databases.