The Global Burden of Disease provides essential data for evidence-based health care, but can be improved by investment in health data systems in low- and middle-income countries
Reliable evidence is essential for health. Data are needed to formulate new health policies and strategies, to ensure quality and equity of health services and universal health coverage, to design effective health interventions, prioritize health challenges and mobilize resources, and to monitor the progress of national and sub-national level. Low- and middle-income countries often lack strong vital statistics, and health decisions are based on data from censuses, surveys, surveillance, and administrative data sources. Studies such as Global Burden of Disease (GBD), which quantifies health loss from hundreds of diseases, injuries and risk factors, are essential to complement local sources of evidence and to address evidence gaps. Ethiopia has strong cooperation with GBD, supported by grants from development partners, but this could be improved through greater cooperation and additional investment in the country.
Ethiopia established a collaboration between the Ethiopian Public Health Institute (EPHI), under the Ministry of Health, the Institute for Health Indicators and Evaluation (IHME) and an expert network of more than 800 GBD collaborators who jointly produce national and sub-national disease burden estimates. This evidence informs our health sector transformation plan and is used to revise essential health service packages, develop strategies for non-communicable diseases, estimate national health expenditure and mobilize resources, measure key health indicators and track progress. developing strategies to reduce disparities between sub-national states, and to respond to the COVID-19 pandemic.
Collaboration with IHME helped us to establish a National Center for Data Management and Analysis at EPHI. The center’s multidisciplinary team works to improve health data storage and management systems, advance health data analysis in the country, and generate quality scientific evidence and translate evidence into policy and decisions. We are establishing similar hubs at sub-national levels that help us understand our own health data landscape in Ethiopia, allowing us to identify future potential uses of health data, understand technical and data infrastructure constraints, and devise new strategies.
Our use of GBD data is not without challenges. Some findings have large uncertainties and may not be consistent between GBD iterations, which may be due to a lack of quality input or new methods used over time. But consistency of key health indicators is essential to measure progress and track differences between and within countries. The sophisticated methods used by the GBD can only be understood by trained experts, requiring significant investment in the country to understand the implications of the findings for health policy and strategy. There are also challenges in accessing already available data that are needed to improve assessments.
Data fuels the modern economy, and data-driven health policies can help drive development and economic growth in low- and middle-income countries. This would also help improve disease assessments such as those of GBD. A closer network of collaboration between GBD and leaders in low- and middle-income countries like Ethiopia would improve the reliability and consistency of assessments and help us establish national data management and analysis systems, build our technical capacity, and enabled us to generate higher quality data in the country, all of which will further strengthen national health policies and research. All countries should build data warehouses to archive existing and future health data, and invest in high-performance computing for data analysis and visualization, led by a multidisciplinary team that understands the evidence requirements of health systems.
Training on health indicators and data science in low- and middle-income countries is essential. This may include GBD methods, data processing, standardization of input data and methods, analysis and synthesis, modelling, evaluation review and experience in using evaluations for policy, strategy and decision making. Training should be provided for people working in ministries of health, research institutes, public health institutes, academia and other stakeholders who generate health data. This will allow countries to jointly analyze national and sub-national estimates of the burden of disease, process and analyze their own data locally and also ensure investment in the local health sector.
Low- and middle-income countries, in collaboration with GBD and funding organizations, should also increase their investment in primary data collection systems to improve assessments and fill their data gaps. Data collection may include population and demographics, causes of death, morbidity and disability, health risk factors, and social determinants of health.
The availability and accessibility of data in the country is important for local enhanced analysis and better global assessments. Data sharing needs to be improved both within and between countries through the development of national and sub-national data access strategies. Data interoperability can be achieved through a health data exchange that links data repositories and observatories, but must be supported by a framework of national regulations and data protocols so that data can be used safely and confidentially, for maximum impact. Advocacy will be needed to get the public to support this investment in health data, but the benefits will be transformative: a healthier population and an economic boost.