Quality of routine health data at the onset of the COVID-19 pandemic in Ethiopia, Haiti, Laos, Nepal, and South Africa.

IF 3.2 2区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH Population Health Metrics Pub Date : 2023-05-20 DOI:10.1186/s12963-023-00306-w
Wondimu Ayele, Anna Gage, Neena R Kapoor, Solomon Kassahun Gelaw, Dilipkumar Hensman, Anagaw Derseh Mebratie, Adiam Nega, Daisuke Asai, Gebeyaw Molla, Suresh Mehata, Londiwe Mthethwa, Nompumelelo Gloria Mfeka-Nkabinde, Jean Paul Joseph, Daniella Myriam Pierre, Roody Thermidor, Catherine Arsenault
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Abstract

Background: During the COVID-19 pandemic, governments and researchers have used routine health data to estimate potential declines in the delivery and uptake of essential health services. This research relies on the data being high quality and, crucially, on the data quality not changing because of the pandemic. In this paper, we investigated those assumptions and assessed data quality before and during COVID-19.

Methods: We obtained routine health data from the DHIS2 platforms in Ethiopia, Haiti, Lao People's Democratic Republic, Nepal, and South Africa (KwaZulu-Natal province) for a range of 40 indicators on essential health services and institutional deaths. We extracted data over 24 months (January 2019-December 2020) including pre-pandemic data and the first 9 months of the pandemic. We assessed four dimensions of data quality: reporting completeness, presence of outliers, internal consistency, and external consistency.

Results: We found high reporting completeness across countries and services and few declines in reporting at the onset of the pandemic. Positive outliers represented fewer than 1% of facility-month observations across services. Assessment of internal consistency across vaccine indicators found similar reporting of vaccines in all countries. Comparing cesarean section rates in the HMIS to those from population-representative surveys, we found high external consistency in all countries analyzed.

Conclusions: While efforts remain to improve the quality of these data, our results show that several indicators in the HMIS can be reliably used to monitor service provision over time in these five countries.

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在埃塞俄比亚、海地、老挝、尼泊尔和南非,COVID-19大流行发生时常规卫生数据的质量。
背景:在2019冠状病毒病大流行期间,各国政府和研究人员利用常规卫生数据来估计基本卫生服务的提供和利用可能出现的下降。这项研究依赖于高质量的数据,而且至关重要的是,数据质量不会因为大流行而改变。在本文中,我们调查了这些假设,并评估了COVID-19之前和期间的数据质量。方法:我们从埃塞俄比亚、海地、老挝人民民主共和国、尼泊尔和南非(夸祖鲁-纳塔尔省)的DHIS2平台获取了关于基本卫生服务和机构死亡的40项指标的常规健康数据。我们提取了24个月(2019年1月至2020年12月)的数据,包括大流行前和大流行前9个月的数据。我们评估了数据质量的四个维度:报告完整性、异常值的存在、内部一致性和外部一致性。结果:我们发现各国和各服务机构报告的完整性很高,在大流行开始时报告的数量几乎没有下降。正异常值在所有服务的设施月观察值中只占不到1%。对疫苗指标内部一致性的评估发现,所有国家的疫苗报告情况相似。将HMIS中的剖宫产率与人口代表性调查中的剖宫产率进行比较,我们发现在所分析的所有国家中,外部一致性都很高。结论:虽然仍需努力提高这些数据的质量,但我们的结果表明,HMIS中的几个指标可以可靠地用于监测这五个国家的长期服务提供情况。
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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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