Assessment of neonatal mortalities and stillbirths data quality in Offinso North District of Ghana
Downloads
Background: Stillbirths and neonatal deaths when poorly documented or collated, negatively affect the quality of decision and interventions. This study sought to assess the quality of routine neonatal mortalities and stillbirth records in health facilities and propose interventions to improve the data quality gaps.
Method: Descriptive cross-sectional study was employed. This study was carried out at three (3) purposively selected health facilities in Offinso North district. Stillbirths and neonatal deaths recorded in registers from 2015 to 2017, were recounted and compared with monthly aggregated data and District Health Information Management System 2 (DHIMS 2) data using a self-developed Excel Data Quality Assessment Tool (DQS). An observational checklist was used to collect primary data on completeness and availability. Accuracy ratio (verification factor), discrepancy rate, percentage availability and completeness of stillbirths and neonatal mortality data were computed using the DQS tool.
Findings: The results showed high discrepancy rate of stillbirth data recorded in registers compared with monthly aggregated reports (12.5%), and monthly aggregated reports compared with DHIMS 2 (13.5%). Neonatal mortalities data were under-reported in monthly aggregated reports, but over-reported in DHIMS 2. Overall data completeness was about 84.6%, but only 68.5% of submitted reports were supervised by facility in-charges. Delivery and admission registers availability were 100% and 83.3% respectively.
Conclusion: Quality of stillbirths and neonatal mortality data in the district is generally encouraging, but are not reliable for decision-making. Routine data quality audit is needed to reduce high discrepancies in stillbirth and neonatal mortality data in the district.
Downloads
Adamki, M., Asamoah, D., & Riverson, K. (2015). Informatics Assessment of Data Quality on Expanded Programme on Immunization in Ghana : The Case of New Juaben Municipality. Health & Medical Informatics, 6(4), 1–9. https://doi.org/10.4172/2157-7420.1000196
Amoakoh-coleman, M., Kayode, G. A., Brown-davies, C., Agyepong, I. A., Grobbee, D. E., Klipstein-grobusch, K., & Ansah, E. K. (2015). Completeness and accuracy of data transfer of routine maternal health services data in the greater Accra region. BioMedical Central, 1–9. https://doi.org/10.1186/s13104-015-1058-3
Badimsuguru, A. B. (2014). Determinants of stillbirths in the Tamale Metropolitan area. University of Ghana, Legon.
Blencowe, H., Cousens, S., Jassir, F. B., Say, L., Chou, D., Mathers, C., Hogan, D., Shiekh, S., & Qureshi, Z. U. (2015). National , regional , and worldwide estimates of stillbirth rates in 2015 , with trends from 2000 : a systematic analysis. The Lancet Global Health, 4(2), 98–108. https://doi.org/10.1016/S2214-109X(15)00275-2
Davies-tuck, M. L., Davey, M., & Wallace, E. M. (2017). Maternal region of birth and stillbirth in Victoria , Australia 2000 – 2011 :A retrospective cohort study of Victorian perinatal data. PLoS ONE, 12(6), 1–14. https://doi.org/10.1371/journal.pone.0178727
Engmann, C., Walega, P., Aborigo, R. A., Adongo, P., Moyer, C. A., Lavasani, L., Williams, J., Bose, C., Binka, F., & Hodgson, A. (2012). Stillbirths and early neonatal mortality in rural Northern Ghana. Tropical Medicine and International Health Volume, 17(3), 272–282. https://doi.org/10.1111/j.1365-3156.2011.02931.x
Ghana Health Service. (2017). Offinso North DHIMS Malaria Indicators.
Ghana Health Service. (2019). Offinso North Health Directorate Annual Report.
Gimbel, S., Micek, M., Lambdin, B., Lara, J., Karagianis, M., Cuembelo, F., Gloyd, S. S., Pfeiffer, J., & Sherr, K. (2011). An assessment of routine primary care health information system data quality in Sofala Province , Mozambique. Population Health Metrics, 9(1), 12. https://doi.org/10.1186/1478-7954-9-12
Hure, A. J., Chojenta, C. L., Powers, J. R., Byles, J. E., & Loxton, D. (2015). Validity and Reliability of Stillbirth Data Using Linked Self-Reported and Administrative Datasets. J Epidemiol, 25(1), 30–37. https://doi.org/10.2188/jea.JE20140032
Kusre, G., & Baruah, J. (2016). Missing stillbirth data : A hospital based study. International Journal of Community Medicine and Public Health |, 3(10), 2949–2952. https://doi.org/10.18203/2394-6040.ijcmph20163389
Lindtj, B., Mitike, D., Zidda, Z., & Yaya, Y. (2018). Reducing stillbirths in Ethiopia :Results of an intervention programme. PLoS ONE, 13(5), 1–11. https://doi.org/10.1371/journal.pone.0197708
Mouroutis, S. (2015). Data Management: Evaluation of an aspect of Data. Research Gate, February, 1–8.
Ogbuoji, O., Olapeju, B., Makinde, O. A., & Babalola, S. (2016). Trends in the completeness of birth registration in Nigeria : 2002 –2010. Demographic Research, 35(12), 315–338. https://doi.org/10.4054/DemRes.2016.35.12
Patel, J. (2015). Data Quality Management - Tools and Techniques. C S Journalss, 7, 198–201.
Pipino, L. L., Lee, Y. W., & Wang, R. Y. (2002). Data Quality Assessment. Communications of the ACM, 45(4), 211–218.
Sidi, F., Hassany, P., Panahy, S., Affendey, L. S., Jabar, M. A., & Ibrahim, H. (2013). Data quality : A survey of data quality dimensions. Research Gate. https://doi.org/10.1109/InfRKM.2012.6204995
The Lancet. (2011, April). Stillbirths: An Executive Summary for The Lancet’s Series. The Lancet, 1–8.
World Health Organization. (2012a). Assessment of health facility data quality Data quality report card:Data quality report card Cambodia.
World Health Organization. (2012b). Guide to the health facility: Data quality report card.
World Health Organization (WHO). (2016). Making Every Baby Count Audit and review of stillbirths and neonatal deaths (pp. 1–136). World Health Organization Publications
Copyright (c) 2022 International Journal of Scientific Research and Management
This work is licensed under a Creative Commons Attribution 4.0 International License.
