Can routine health facility data be used to monitor subnational coverage of maternal, newborn and child health services in Uganda?

BMC Health Services Research

Christine Tashobya¹  Geraldine Agiraembabazi¹  Rornald Muhumuza Kananura²  Peter Waiswa³  Ties Boerma⁴  Jimmy Ogwal⁵ 

[1]Department of health policy planning and Management, Makerere University School of Public Health, Mulago New-Complex, Kampala, Uganda

[2]Department of health policy planning and Management, Makerere University School of Public Health, Mulago New-Complex, Kampala, Uganda

[3]Makerere University Centre of Excellence for Maternal, Newborn and Child Health, Mulago New-Complex, Kampala, Uganda

[4]Department of International Development, London School of Economics and Political Science, London, UK

[5]Department of health policy planning and Management, Makerere University School of Public Health, Mulago New-Complex, Kampala, Uganda

[6]Makerere University Centre of Excellence for Maternal, Newborn and Child Health, Mulago New-Complex, Kampala, Uganda

[7]Global Health Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden

[8]Institute for Global Public Health, University of Manitoba, Winnipeg, Canada

[9]Ministry of Health, Kampala, Uganda

关键词: Health facility data;    District health information system;    Data quality;    Maternal health;    Child health;    Uganda;   

DOI  :  10.1186/s12913-021-06554-6

来源: Springer

【 摘 要 】

BackgroundRoutine health facility data are a critical source of local monitoring of progress and performance at the subnational level. Uganda has been using district health statistics from facility data for many years. We aimed to systematically assess data quality and examine different methods to obtain plausible subnational estimates of coverage for maternal, newborn and child health interventions.MethodsAnnual data from the Uganda routine health facility information system 2015–2019 for all 135 districts were used, as well as national surveys for external comparison and the identification of near-universal coverage interventions. The quality of reported data on antenatal and delivery care and child immunization was assessed through completeness of facility reporting, presence of extreme outliers and internal data consistencies. Adjustments were made when necessary. The denominators for the coverage indicators were derived from population projections and health facility data on near-universal coverage interventions. The coverage results with different denominators were compared with the results from household surveys.ResultsUganda’s completeness of reporting by facilities was near 100% and extreme outliers were rare. Inconsistencies in reported events, measured by annual fluctuations and between intervention consistency, were common and more among the 135 districts than the 15 subregions. The reported numbers of vaccinations were improbably high compared to the projected population of births or first antenatal visits – and especially so in 2015–2016. There were also inconsistencies between the population projections and the expected target population based on reported numbers of antenatal visits or immunizations. An alternative approach with denominators derived from facility data gave results that were more plausible and more consistent with survey results than based on population projections, although inconsistent results remained for substantive number of subregions and districts.ConclusionOur systematic assessment of the quality of routine reports of key events and denominators shows that computation of district health statistics is possible with transparent adjustments and methods, providing a general idea of levels and trends for most districts and subregions, but that improvements in data quality are essential to obtain more accurate monitoring.

【 授权许可】

CC BY