Quality of routine data related to facility-based maternal mortality measurement in Kampala City, Uganda

Author:

Birabwa Catherine1,Banke-Thomas Aduragbemi2,Semaan Aline3,Olmen Josefien van4,Kananura Rornald Muhumuza5,Arinaitwe Emma Sam6,Waiswa Peter7,Beňová Lenka3

Affiliation:

1. Makerere University School of Public Health, Kampala, Uganda. Institute of Tropical Medicine, Antwerp, Belgium. University of Antwerp, Antwerp, Belgium

2. London School of Hygiene and Tropical Medicine, London, United Kingdom

3. Institute of Tropical Medicine, Antwerp, Belgium

4. University of Antwerp, Antwerp, Belgium

5. Makerere University School of Public Health, Kampala, Uganda

6. Ministry of Health, Kampala, Uganda

7. Makerere University School of Public Health, Kampala, Uganda. Karolinska Institute, Stockholm, Sweden. Busoga Health Forum, Jinja, Uganda

Abstract

Abstract Background Routine health facility data are an important source of health information. Regular quality assessments are necessary to improve the reliability of routine data for different purposes, including estimating facility-based maternal mortality. The objective of this study was to assess the quality of routine data on deliveries, livebirths and maternal deaths in Kampala City, Uganda. Methods We reviewed routine data reported by health facilities through the district health information system (DHIS2) from 2016 to 2021. This time period included an upgrade of the DHIS2 resulting in two datasets (2016–2019 and 2020–2021) that were managed separately. We analysed data for all facilities that reported at least one delivery in any of the six years, and for a subset of facilities designated to provide emergency obstetric care (EmOC). We used the World Health Organization data quality review framework to assess completeness and internal consistency of the three data elements, using 2019 and 2021 as reference years. Primary data was collected to verify the accuracy of reporting in four purposively selected EmOC facilities. Descriptive statistics, including frequencies and percentages, were computed using STATA (v14) and Microsoft Excel. Results We included 255 facilities from 2016–2019 and 247 from 2020–2021; of which 30% were EmOC facilities. The overall completeness of data for deliveries and livebirths ranged between 53% and 55%, and was < 2% for maternal deaths (98% of monthly values were zero). Among EmOC facilities, completeness was higher for deliveries and livebirths at 80%; and was < 6% for maternal deaths. For the whole sample, the prevalence of outliers for all three data elements was < 2%. Inconsistencies over time were mostly observed for maternal deaths, and underreporting of maternal deaths was noted in one of the EmOC facilities verified. Conclusion Routine data from facilities providing childbirth services in Kampala were generally suboptimal, but of acceptable quality in EmOC facilities. However, given likely underreporting of maternal deaths, further efforts to verify and count all maternal deaths in health facilities are essential to accurately estimate facility-based maternal mortality. There is still a need to improve facility reporting, especially in non-EmOC facilities.

Publisher

Research Square Platform LLC

Reference48 articles.

1. Sheikh K, Abimbola S. Strong health systems are learning health systems. PLOS Global Public Health [Internet]. 2022;2(3):e0000229-. Available from: https://doi.org/10.1371/journal.pgph.0000229

2. World Health Organization. Monitoring the building blocks of health systems: A handbook of indicators and their measurement strategies. Geneva; 2010.

3. The Health System Dynamics Framework: The introduction of an analytical model for health system analysis and its application to two case-studies;Olmen J;Health, Culture and Society,2012

4. Mallick L, Gheda T, Sorrel N, Trinadh D, Wenjuan W. Using Health Management Information Systems Data to Contextualize Survey-Based Estimates of Fertility, Mortality, and Wasting. DHS Occasional Paper No. 12 [Internet]. Rockville, Maryland, USA; 2020 [cited 2023 Mar 7]. Available from: https://dhsprogram.com/pubs/pdf/OP12/OP12.pdf

5. Mgawadere F, Kana T, Van Den Broek N. Measuring maternal mortality: A systematic review of methods used to obtain estimates of the Maternal Mortality Ratio (MMR) in low- and middle-income countries. Vol. 121, British Medical Bulletin. Oxford University Press; 2017. p. 121–34.

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