Department of health policy planning and Management, Makerere University School of Public Health, Mulago New-Complex, Kampala, Uganda.
Ministry of Health, Kampala, Uganda.
BMC Health Serv Res. 2021 Sep 13;21(Suppl 1):512. doi: 10.1186/s12913-021-06554-6.
Routine health facility data are a critical source of local monitoring of progress and performance at the subnational level. Uganda has been using district health statistics from facility data for many years. We aimed to systematically assess data quality and examine different methods to obtain plausible subnational estimates of coverage for maternal, newborn and child health interventions.
Annual data from the Uganda routine health facility information system 2015-2019 for all 135 districts were used, as well as national surveys for external comparison and the identification of near-universal coverage interventions. The quality of reported data on antenatal and delivery care and child immunization was assessed through completeness of facility reporting, presence of extreme outliers and internal data consistencies. Adjustments were made when necessary. The denominators for the coverage indicators were derived from population projections and health facility data on near-universal coverage interventions. The coverage results with different denominators were compared with the results from household surveys.
Uganda's completeness of reporting by facilities was near 100% and extreme outliers were rare. Inconsistencies in reported events, measured by annual fluctuations and between intervention consistency, were common and more among the 135 districts than the 15 subregions. The reported numbers of vaccinations were improbably high compared to the projected population of births or first antenatal visits - and especially so in 2015-2016. There were also inconsistencies between the population projections and the expected target population based on reported numbers of antenatal visits or immunizations. An alternative approach with denominators derived from facility data gave results that were more plausible and more consistent with survey results than based on population projections, although inconsistent results remained for substantive number of subregions and districts.
Our systematic assessment of the quality of routine reports of key events and denominators shows that computation of district health statistics is possible with transparent adjustments and methods, providing a general idea of levels and trends for most districts and subregions, but that improvements in data quality are essential to obtain more accurate monitoring.
常规卫生机构数据是在国家以下各级监测进展和绩效的重要信息来源。乌干达多年来一直使用来自卫生机构数据的地区卫生统计数据。我们旨在系统评估数据质量，并研究不同方法来获得孕产妇、新生儿和儿童健康干预措施的合理国家以下各级估计数。
使用了 2015-2019 年乌干达常规卫生机构信息系统的年度数据，这些数据来自全国 135 个地区，还使用了国家调查数据进行外部比较和确定接近普及的干预措施。通过机构报告的完整性、极端异常值的存在以及内部数据一致性来评估产前和分娩护理以及儿童免疫接种报告数据的质量。在必要时进行了调整。覆盖率指标的分母来自人口预测和接近普及的干预措施的卫生机构数据。使用不同分母的覆盖率结果与家庭调查结果进行了比较。
乌干达机构报告的完整性接近 100%，极端异常值很少。报告事件的不一致性，通过年度波动和干预一致性之间的差异来衡量，很常见，在 135 个地区比在 15 个分区中更为常见。与预测的出生人数或首次产前检查相比，报告的疫苗接种次数高得令人难以置信——尤其是在 2015-2016 年。人口预测与根据报告的产前检查或免疫接种次数计算出的预期目标人群之间也存在不一致。一种替代方法是使用来自机构数据的分母，结果更合理，与调查结果更一致，尽管在数量上仍有一些分区和地区存在不一致的情况。
我们对关键事件和分母的常规报告质量进行了系统评估，表明通过透明的调整和方法计算地区卫生统计数据是可行的，为大多数地区和分区提供了水平和趋势的大致了解，但要获得更准确的监测，数据质量的提高是必不可少的。
