The quality of routine data for measuring facility-based maternal mortality in public and private health facilities in Kampala City, Uganda.

IF 3.2 2区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH Population Health Metrics Pub Date : 2024-08-23 DOI:10.1186/s12963-024-00343-z
Catherine Birabwa, Aduragbemi Banke-Thomas, Aline Semaan, Josefien van Olmen, Rornald Muhumuza Kananura, Emma Sam Arinaitwe, Peter Waiswa, Lenka Beňová
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Abstract

Background: Routine health facility data are an important source of health information in resource-limited settings. Regular quality assessments are necessary to improve the reliability of routine data for different purposes, including estimating facility-based maternal mortality. This study aimed to assess the quality of routine data on deliveries, livebirths and maternal deaths in Kampala City, Uganda.

Methods: We reviewed routine health facility data from the district health information system (DHIS2) for 2016 to 2021. This time period included an upgrade of 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 adapted 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 were collected to verify reporting accuracy in four purposively selected EmOC facilities. Data were disaggregated by facility level and ownership.

Results: We included 255 facilities from 2016 to 2019 and 247 from 2020 to 2021; of which 30% were EmOC facilities. The overall completeness of data for deliveries and livebirths ranged between 53% and 55%, while it 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, with the highest difference of 96% occurring in 2021.

Conclusions: Routine data from childbirth facilities in Kampala were generally suboptimal, but the quality was better in EmOC facilities. Given likely underreporting of maternal deaths, further efforts to verify and count all facility-related maternal deaths are essential to accurately estimate facility-based maternal mortality. Data reliability could be enhanced by improving reporting practices in EmOC facilities and streamlining reporting processes in private-for-profit facilities. Further qualitative studies should identify critical points where data are compromised, and data quality assessments should consider service delivery standards.

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乌干达坎帕拉市公立和私立医疗机构用于衡量设施内孕产妇死亡率的常规数据质量。
背景:在资源有限的环境中,常规卫生设施数据是重要的卫生信息来源。有必要定期进行质量评估,以提高用于不同目的的常规数据的可靠性,包括估算基于医疗机构的孕产妇死亡率。本研究旨在评估乌干达坎帕拉市分娩、活产和孕产妇死亡常规数据的质量:我们审查了地区卫生信息系统(DHIS2)中 2016 年至 2021 年的常规医疗机构数据。这一时期包括 DHIS2 的升级,因此产生了两个数据集(2016-2019 年和 2020-2021 年),分别进行管理。我们分析了在这六年中任何一年至少报告过一次分娩的所有机构的数据,以及指定提供产科急诊(EmOC)的机构子集的数据。我们采用了世界卫生组织的数据质量审查框架,以 2019 年和 2021 年为参照年,评估三个数据元素的完整性和内部一致性。为了验证报告的准确性,我们收集了四家特意选定的 EmOC 机构的原始数据。数据按设施级别和所有权分列:我们纳入了 2016 年至 2019 年的 255 家设施和 2020 年至 2021 年的 247 家设施,其中 30% 为 EmOC 设施。分娩和活产数据的总体完整度介于 53% 和 55% 之间,而结论是:分娩和活产数据的完整度介于 53% 和 55% 之间,而结论是:分娩和活产数据的完整度介于 53% 和 55% 之间:坎帕拉分娩机构的常规数据普遍不理想,但 EmOC 机构的数据质量较好。鉴于可能存在孕产妇死亡漏报的情况,因此必须进一步努力核实和统计所有与医疗机构相关的孕产妇死亡人数,以准确估算医疗机构的孕产妇死亡率。可以通过改进 EmOC 机构的报告方法和简化私营营利机构的报告流程来提高数据的可靠性。进一步的定性研究应确定数据受损的关键点,数据质量评估应考虑服务提供标准。
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来源期刊
Population Health Metrics
Population Health Metrics PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
CiteScore
6.50
自引率
0.00%
发文量
21
审稿时长
29 weeks
期刊介绍: Population Health Metrics aims to advance the science of population health assessment, and welcomes papers relating to concepts, methods, ethics, applications, and summary measures of population health. The journal provides a unique platform for population health researchers to share their findings with the global community. We seek research that addresses the communication of population health measures and policy implications to stakeholders; this includes papers related to burden estimation and risk assessment, and research addressing population health across the full range of development. Population Health Metrics covers a broad range of topics encompassing health state measurement and valuation, summary measures of population health, descriptive epidemiology at the population level, burden of disease and injury analysis, disease and risk factor modeling for populations, and comparative assessment of risks to health at the population level. The journal is also interested in how to use and communicate indicators of population health to reduce disease burden, and the approaches for translating from indicators of population health to health-advancing actions. As a cross-cutting topic of importance, we are particularly interested in inequalities in population health and their measurement.
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