Making Data Work For Africa’s Population And Health Sector

Via APHRC

For decades, data has been the buzzword in research communities across different disciplines- its rationale, means of collection and analysis and eventually what it means for the particular study objective and/or the field in general. In recent years, however, there has been a data revolution in many parts of the world driven by advances in information technology and a need for research that responds to complex developmental agenda in contemporary contexts. As part of the drive towards a post-2015 development agenda, the United Nations and its partners called for greater evidence-based decision-making at all levels.

African countries are also experiencing the data revolution, especially within in the Population and Health Sector, in terms of volume, types, sources, frequency and speed of data production. This revolution is allowing African governments, civil society, researchers, and citizens to drive action and monitor progress, with real-time, dynamic, and disaggregated data. This has meant that now more than ever, there is more population and health information available in the public domain. For example, over 60 countries across the globe use the District Health Information System, an open source platform for reporting, analysis, and dissemination of data at all levels of government.

For instance, most countries that use the DHS system are required conduct regular national health program reviews every two to three years to improve performance and quality, with the aim of achieving better results for the health and wellbeing of their citizens. Program reviews typically use information from country-specific Monitoring and Evaluation (M&E) frameworks, and from various other sources to establish whether the program as a whole or its components are producing the desired results consistent with the pre-defined National Health Strategic Plans or Strategies. In addition to supporting such program reviews for health, countries undertake epidemiological and impact assessments through frequent analysis of available data at national, sub-national and local levels. The in-country dialogue and action planning following such reviews is critical to ensure that bottlenecks in implementation are addressed.

One of the key challenges that beguile the African health sector in the context of data, is the coordination of multiple sources of data. Whereas most countries in Sub-Saharan Africa have taken major steps and made significant progress towards improving availability, access, analysis and use of health data, there still exists a need for more coordinated and collaborative efforts of all stakeholders in order to fully exploit the rich potential of their health information systems. For most countries in the region, there exist multiple sources of health data most of which are geographically referenced. Facilitating mechanisms to bridge this gap and increase discovery and usage of geospatial data by health managers is therefore important.

Another perpetual challenge is data quality. Key dimensions of data quality are accuracy, timeliness, relevance, being validated and machine-readable, and free and open to access.  although country-specific health data management systems in African countries have continued to improve, information collected still remains limited. Health data, most especially the routinely collected service data (RCD) are often beset with data quality issues such as missing values and errors in data entry and computation. Errors related to inaccurate entries, incompleteness, and inconsistencies in data mean inaccurate results, faulty conclusions, and recommendations that miss the mark. Good quality data are essential for proper planning, budgeting and implementation of development activities, particularly those in the essential services sector such as public health. In the absence of quality data, investments of limited public resources are often based on little more than guessing. Without basic metrics, it is not possible to get an accurate picture of how a population is developing or how to target health investments to meet the real needs of the people.

In a world that is already moving onto the use of Artificial Intelligence and Big Data as the next frontier, low and middle-income countries (LMICs) are still grappling with institutionalizing ‘small data’. Data collection, handling, archival and analysis is still an expensive affair in terms of capacity, logistics and financial implications for most LMICs in Sub-Saharan Africa. National statistical offices do not have the necessary and sufficient technological, financial and human resource capacities to collect, process and disseminate the data required for the pursuit of the Sustainable Development Goals, the African Union’s Agenda 2063 and National Development Plans. Countries often have to weigh donor priorities against their own national concerns, with scales tilting in favor of donors at the expense of the other.

As African countries continue to fulfill their promises to leave no one behind, it is critical that the issues around data are addressed. Governments at all levels need to invest in relevant, timely and accurate data for decision-making at all levels – including human resources. Data for development and decision-making needs to be empirically sound, right from conceptualization of the problem, through the design of the research methodology, to the data collection, handling, analysis, and dissemination.

The African Population and Health Research Center (APHRC) is committed to contributing to the improvement of data availability, data quality and data use at the national, local and community level through coordinated investments in national data systems and advocacy for open data. For instance, all APHRC’s data since 2002 are publicly available on a Microdata Portal for external researchers and policymakers.

While energies are already being spent in extolling the virtues of quality data, governments across the continent need to continue these investments by availing the necessary resources needed to fulfill their commitments to citizens on the provision of quality and affordable healthcare for all. According to the Data for African Development Working Group, this would be through domestic resource mobilization (for health financing), standardization of data indicators (for collection, analysis, and reporting) and strengthening of national bodies in charge of statistics. Whereas the commitment may be the first step on the journey towards affordable healthcare, a lot more is yet to be done to harness the great power of data for public health.

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