Data systems for health services in Africa are developing quickly. To begin with these data systems were focused on the need to monitor programmes that deliver care, treatment, and services in health facilities. However, routine health information systems, which are being used to collect full-coverage records at all levels of many African health systems, are often overlooked for estimating the impact of these health services on patient health. While there have been concerns regarding completeness, timeliness, representativeness, and accuracy of these data, the advent of new analyses methods, give these data the potential for a greater role in understanding patient health.
Many African countries have relied on health data collected from nationally representative population and household surveys to develop policy and plan services. These surveys are costly and time consuming, and often overlook important sub-populations in the country. Routinely collected patient data can now be used to replace these expensive surveys and to provide accurate estimates of disease prevalence, evidence of treatment impact for successful programs, and help understand the quality of life for those served by the health services.
In order get the most out of routine health data, expert statisticians are needed. Many countries are now developing and implementing biostatistics training at undergraduate, masters, and PhD levels to supply the skills to data personnel and clinical staff. Through networks such as the sub-Saharan African consortium for advanced biostatistics (SSACAB) training, MSc courses are being developed, and future research leaders are being trained to analyse data in several African countries.
The aim of this Research Topic is to showcase the ways that routine data can be used in many settings in developing countries, and to provide the opportunity for new statisticians to publish their research. As a supplement to the journal Frontiers in Public Health’s Digital Health section, this will bring together existing data and new initiatives to create networks that span disciplines and countries. It will reinforce the importance of data to policy makers and planners in the respective Ministries of Health. It will enhance and build academic rigor for proper, high-quality analysis of routinely collected data, and create new opportunities for students and supervisors to explore new challenges in the analysis of routinely collected health data.
What are we looking for in this Research Topic? Firstly to address the finding that few research articles have utilized routinely collected health data. Secondly, to demonstrate how routine data have been used to estimate the prevalence of disease in different countries. Thirdly, to give prominence to new initiatives and statistical techniques being used to analyse routine data in Africa. Finally, to highlight that Ministry owned health data, combined with relevant Biostatistical methods, can change the way we study health and health systems. This will contribute to increased uptake and use of routine data for health policy and planning over time
The papers in this Research Topic can build on the ideas from across the world, but ultimately they will showcase the strong statistical, data, and systems skills being developed by hundreds of researchers across Africa.
Data systems for health services in Africa are developing quickly. To begin with these data systems were focused on the need to monitor programmes that deliver care, treatment, and services in health facilities. However, routine health information systems, which are being used to collect full-coverage records at all levels of many African health systems, are often overlooked for estimating the impact of these health services on patient health. While there have been concerns regarding completeness, timeliness, representativeness, and accuracy of these data, the advent of new analyses methods, give these data the potential for a greater role in understanding patient health.
Many African countries have relied on health data collected from nationally representative population and household surveys to develop policy and plan services. These surveys are costly and time consuming, and often overlook important sub-populations in the country. Routinely collected patient data can now be used to replace these expensive surveys and to provide accurate estimates of disease prevalence, evidence of treatment impact for successful programs, and help understand the quality of life for those served by the health services.
In order get the most out of routine health data, expert statisticians are needed. Many countries are now developing and implementing biostatistics training at undergraduate, masters, and PhD levels to supply the skills to data personnel and clinical staff. Through networks such as the sub-Saharan African consortium for advanced biostatistics (SSACAB) training, MSc courses are being developed, and future research leaders are being trained to analyse data in several African countries.
The aim of this Research Topic is to showcase the ways that routine data can be used in many settings in developing countries, and to provide the opportunity for new statisticians to publish their research. As a supplement to the journal Frontiers in Public Health’s Digital Health section, this will bring together existing data and new initiatives to create networks that span disciplines and countries. It will reinforce the importance of data to policy makers and planners in the respective Ministries of Health. It will enhance and build academic rigor for proper, high-quality analysis of routinely collected data, and create new opportunities for students and supervisors to explore new challenges in the analysis of routinely collected health data.
What are we looking for in this Research Topic? Firstly to address the finding that few research articles have utilized routinely collected health data. Secondly, to demonstrate how routine data have been used to estimate the prevalence of disease in different countries. Thirdly, to give prominence to new initiatives and statistical techniques being used to analyse routine data in Africa. Finally, to highlight that Ministry owned health data, combined with relevant Biostatistical methods, can change the way we study health and health systems. This will contribute to increased uptake and use of routine data for health policy and planning over time
The papers in this Research Topic can build on the ideas from across the world, but ultimately they will showcase the strong statistical, data, and systems skills being developed by hundreds of researchers across Africa.
