BMJ Global Health (Sep 2019)
Generating statistics from health facility data: the state of routine health information systems in Eastern and Southern Africa
- Martin Kavao Mutua,
- Gershim Asiki,
- Candy Day,
- Kathleen L Strong,
- Kavitha Viswanathan,
- Kathryn Patricia O’Neill,
- Bob S Pond,
- Jean Marie Ntibazomumpa,
- Joël Nibogora,
- Prosper Niyongabo,
- Amanuel Kifle,
- Sibusiso Charles Mamba,
- Wubegzier Mekonnen Ayele,
- Espoir Bwenge Malembaka,
- Robert Banywesize,
- Anne Khasakhala,
- Anthony Ngugi,
- Helen Kiarie,
- Valeria Makory,
- Leonard Cosmas,
- Lebohang Rantsatsi,
- Simeon Yosefe,
- Golden Chanansi,
- Kondwani Chavula,
- Monica Patricia Malata,
- Gerito Augusto,
- Cesarino Tivane,
- Catarina Barrula,
- Cláudio Muianga,
- Ezekiel Muyenga,
- Matheus Shiindi,
- Pacifique Mukashema,
- Ntawuyirusha Emmanuel,
- Innocent Maposa,
- Mamothena Carol Mothupi,
- Augustino Ting Mayai,
- Victor Misaka,
- Edward Ladu,
- Josephine Shabani,
- Dhamira Mongi,
- Prisca Jackson,
- David Edward Lenga,
- Daudi Simba,
- Geraldine Agiraembabazi,
- Paul Mubiri,
- Jimmy Ogwal,
- Stephen Akena Bwoye,
- Elizabeth Mwauluka,
- Mbonyiwe Jojo,
- Choolwe Jacobs,
- Rugare Abigail Kangwende,
- Lloyd Machacha,
- Vasco Chikwasha,
- Mooketsi M Molefi,
- Judith Letebele,
- Balekane Sitibi
Affiliations
- Martin Kavao Mutua
- Department of Research, African Population and Health Research Center, Nairobi, Kenya
- Gershim Asiki
- Health and Systems for Health, African Population and Health Research Center, Nairobi, Kenya
- Candy Day
- Health System Trust, Westville, South Africa
- Kathleen L Strong
- 1 Maternal, Newborn, Child and Adolescent Health and Ageing, World Health Organization, Geneva, Switzerland
- Kavitha Viswanathan
- Information Evidence and Research, World Health Organization, Geneva, Switzerland
- Kathryn Patricia O’Neill
- Information Evidence and Research, World Health Organization, Geneva, Switzerland
- Bob S Pond
- Independent Consultant, Portland, Oregon, USA
- Jean Marie Ntibazomumpa
- Joël Nibogora
- Prosper Niyongabo
- Amanuel Kifle
- Sibusiso Charles Mamba
- Wubegzier Mekonnen Ayele
- Espoir Bwenge Malembaka
- Robert Banywesize
- Anne Khasakhala
- Anthony Ngugi
- Helen Kiarie
- Valeria Makory
- Leonard Cosmas
- Lebohang Rantsatsi
- Simeon Yosefe
- Golden Chanansi
- Kondwani Chavula
- Monica Patricia Malata
- Gerito Augusto
- Cesarino Tivane
- Catarina Barrula
- Cláudio Muianga
- Ezekiel Muyenga
- Matheus Shiindi
- Pacifique Mukashema
- Ntawuyirusha Emmanuel
- Innocent Maposa
- Division of Epidemiology and Biostatistics, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, Gauteng, South Africa
- Mamothena Carol Mothupi
- Augustino Ting Mayai
- Victor Misaka
- Edward Ladu
- Josephine Shabani
- Dhamira Mongi
- Prisca Jackson
- David Edward Lenga
- Daudi Simba
- Geraldine Agiraembabazi
- Paul Mubiri
- School of Public Health, Makerere University, College of Health Sciences, Kampala, Uganda
- Jimmy Ogwal
- Stephen Akena Bwoye
- Elizabeth Mwauluka
- Mbonyiwe Jojo
- Choolwe Jacobs
- Rugare Abigail Kangwende
- Lloyd Machacha
- Vasco Chikwasha
- Mooketsi M Molefi
- Judith Letebele
- Balekane Sitibi
- DOI
- https://doi.org/10.1136/bmjgh-2019-001849
- Journal volume & issue
-
Vol. 4,
no. 5
Abstract
Health facility data are a critical source of local and continuous health statistics. Countries have introduced web-based information systems that facilitate data management, analysis, use and visualisation of health facility data. Working with teams of Ministry of Health and country public health institutions analysts from 14 countries in Eastern and Southern Africa, we explored data quality using national-level and subnational-level (mostly district) data for the period 2013–2017. The focus was on endline analysis where reported health facility and other data are compiled, assessed and adjusted for data quality, primarily to inform planning and assessments of progress and performance. The analyses showed that although completeness of reporting was generally high, there were persistent data quality issues that were common across the 14 countries, especially at the subnational level. These included the presence of extreme outliers, lack of consistency of the reported data over time and between indicators (such as vaccination and antenatal care), and challenges related to projected target populations, which are used as denominators in the computation of coverage statistics. Continuous efforts to improve recording and reporting of events by health facilities, systematic examination and reporting of data quality issues, feedback and communication mechanisms between programme managers, care providers and data officers, and transparent corrections and adjustments will be critical to improve the quality of health statistics generated from health facility data.