Assessment of neonatal mortalities and stillbirths data quality in Offinso North District of Ghana
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Published:2022-01-12
Issue:01
Volume:10
Page:508-518
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ISSN:2321-3418
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Container-title:International Journal of Scientific Research and Management
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language:
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Short-container-title:int.jour.sci.res.mana.
Author:
Nsiah RichmondORCID, Takramah Wisdom, Anum-Doku Solomon, Avagu Richard, Nyarko Dominic
Abstract
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.
Publisher
Valley International
Subject
Environmental Engineering
Reference21 articles.
1. 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 2. 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 3. Badimsuguru, A. B. (2014). Determinants of stillbirths in the Tamale Metropolitan area. University of Ghana, Legon. 4. 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 5. 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
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