Assessment of neonatal mortalities and stillbirths data quality in Offinso North District of Ghana

Richmond Nsiah,Richard Avagu,Solomon Anum-Doku,Dominic Nyarko,Wisdom Takramah

doi:10.18535/ijsrm/v10i01.mp01

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.

Highlights

Data is the primary foundation in operational, tactical and decisions making activities
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 District Health Information Management System 2 (DHIMS 2) (13.5%)
Data accuracy of stillbirth and neonatal mortalities Stillbirth This study revealed 100% stillbirth data accuracy by Facility C when source registers were verify with monthly aggregated reports whilst Facility B recorded the lowest score (60%) for the same verification factor as depicted on Table 1

Summary

Introduction

Data is the primary foundation in operational, tactical and decisions making activities. Data are crucial resources and its quality is critical for managers and operating processes to identify related performance issues (Sidi et al, 2013). In this era, all the technical and strategic decision are data driven. Many West African countries with disproportionately high perinatal mortality rates often have weak data management and health systems, resulting in a paucity of perinatal morbidity and mortality information and Richmond Nsiah, IJSRM Volume 10 Issue 01 January 2022 [www.ijsrm.in]. Stillbirths and neonatal deaths when poorly documented or collated, negatively affect the quality of decision and interventions born out of these data. This study sought to assess the quality of routine neonatal mortalities and stillbirth records in health facilities and propose interventions to improve data quality gaps

Methods

Results

Conclusion