ASSESSMENT OF THE AVAILABILITY OF NEONATAL MORTALITY AND STILLBIRTH RECORDS IN ROUTINE HEALTH INFORMATION SYSTEMS AT HO TEACHING HOSPITAL, VOLTA REGION, GHANA
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Abstract
Neonatal mortality and stillbirth remain major public health concerns in low- and middle-income countries, where routine health information systems often face documentation and archival challenges. This study assessed the availability of neonatal mortality and stillbirth data elements within routine health facility records at Ho Teaching Hospital in the Volta Region of Ghana from January 2019 to December 2021. A descriptive cross-sectional retrospective design was used. Data were obtained from delivery registers, admission and discharge registers, monthly midwives’ summary reports (Form A), and the District Health Information Management System II (DHIMS-II). Data availability was defined as the presence and accessibility of neonatal mortality and stillbirth data elements in source documents and reporting forms for each reporting month. A total of 108 expected records were assessed (36 months × 3 reporting sources). Overall data availability was 88.2%, with annual rates of 88.9% in 2019, 91.7% in 2020, and 88.9% in 2021. Missing registers in selected months limited full verification of reported data. Neonatal mortality and stillbirth data are largely available at Ho Teaching Hospital; however, strengthening register management, archival systems, and routine data validation processes is necessary to improve data reliability.
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Ahanhanzo, Y. G., Ouendo, E. M., & Kpozèhouen, A. (2014). Data quality assessment in health information systems. BMC Health Services Research, 14, 1–8.
Amoakoh-Coleman, M., Agyepong, I. A., Kayode, G. A., Grobbee, D. E., Klipstein-Grobusch, K., & Ansah, E. K. (2015). Completeness and accuracy of routine maternal health data in Ghana. BMC Research Notes, 8, 1–9.
Braa, J., Hanseth, O., Heywood, A., Mohammed, W., & Shaw, V. (2007). Developing health information systems in developing countries: The flexible standards strategy. MIS Quarterly, 31(2), 381–402.
Chen, H., Hailey, D., Wang, N., & Yu, P. (2014). Data quality assessment methods. International Journal of Environmental Research and Public Health, 11, 5170–5207.
Ghana Health Service (GHS). (2019). Annual reproductive and child health report. Accra, Ghana.
Ghana Statistical Service (GSS), Ghana Health Service (GHS), & ICF. (2015). Ghana demographic and health survey 2014. Rockville, MD: ICF.
Kayode, G. A., Grobbee, D. E., Amoakoh-Coleman, M., Adeleke, I. T., Ansah, E. K., & Klipstein-Grobusch, K. (2014). The birth weight accuracy of routine health facility data in Ghana. PLoS ONE, 9(5), e97338.
Lawn, J. E., Blencowe, H., Waiswa, P., Amouzou, A., Mathers, C., Hogan, D., Flenady, V., Frøen, J. F., Qureshi, Z. U., Calderwood, C., Shiekh, S., Jassir, F. B., You, D., McClure, E. M., Mathai, M., Cousens, S., & Lancet Ending Preventable Stillbirths Series Study Group. (2016). Stillbirths: Rates, risk factors, and acceleration towards 2030. The Lancet, 387, 587–603.
Lippeveld, T., Sauerborn, R., & Bodart, C. (2000). Design and implementation of health information systems. Geneva, Switzerland: World Health Organization.
McClure, E. M., Saleem, S., Pasha, O., & Goldenberg, R. L. (2009). Stillbirth in developing countries: A review of causes, risk factors, and prevention strategies. Journal of Maternal-Fetal & Neonatal Medicine, 22, 183–190.
Mphatswe, W., Mate, K. S., Bennett, B., Ngidi, H., Reddy, J., Barker, P., & Rollins, N. (2012). Improving public health information: A data quality intervention in South Africa. Bulletin of the World Health Organization, 90, 176–182.
Nutley, T., Gattiker, J., & Kahn, J. (2020). Utilization of health information systems for decision-making. BMC Health Services Research, 20, 514.
Serpe, L., Lang, K., & White, R. (2014). Data completeness in healthcare reporting systems. Health Informatics Journal, 20, 112–120.
Sychareun, V., et al. (2014). Data verification in routine health systems. BMC Health Services Research, 14, 1–10.
United Nations. (2016). Sustainable development goals report. New York, NY: United Nations.
United Nations Inter-Agency Group for Child Mortality Estimation (UN IGME). (2022). Levels and trends in child mortality. New York, NY: United Nations.
World Health Organization (WHO). (2012). Data quality review toolkit. Geneva, Switzerland: WHO.
World Health Organization (WHO). (2014). Every newborn action plan. Geneva, Switzerland: WHO.
World Health Organization (WHO). (2020). Newborn mortality fact sheet. Geneva, Switzerland: WHO.
World Health Organization (WHO). (2021). Global strategy on digital health 2020–2025. Geneva, Switzerland: WHO.