Uwera Thaoussi, Frøen J Frederik, Papadopoulou Eleni, Rukundo Enock, Sibomana Hassan, Muhire Andrew, Tumusiime David K, Venkateswaran Mahima
Regional Center of Excellence in Biomedical Engineering and e-Health, University of Rwanda, KG 11 Ave Gasabo, Kigali, Rwanda.
Center for Intervention Science in Maternal and Child Health (CISMAC), University of Bergen, Bergen, Norway.
Arch Public Health. 2025 Apr 9;83(1):97. doi: 10.1186/s13690-025-01583-7.
Documentation and reporting of routine data by health workers is the backbone of the childhood immunization program. Immunization data from health management information systems (HMIS) in low-and middle-income countries (LMICs) are often incomplete and unreliable. In Rwanda, the immunization e-Tracker, an individual-level health management information system (HMIS) built on DHIS2 open-source software, has been implemented and scaled nationwide since 2019. The aim of this study was to assess the quality of the routine HMIS immunization data over time.
Data were derived from four HMIS sources for January to December 2020 from 24 health facilities from four districts: health facility registers (paper-based), district aggregated reports (paper-based), national HMIS reports (electronic), and e-Tracker reports (electronic). We then obtained e-Tracker reports and national HMIS reports from 2022 for the same facilities and assessed changes over time. Data quality assessments were conducted for four selected childhood immunization indicators: Bacille Calmette-Guérin (BCG), Pentavalent 3 (Penta 3) and Measles & Rubella 1 (MR1). We calculated frequencies and percentage differences. Accuracy ratios were computed for HMIS reports against facility registers for 2020 and e-Tracker for 2022.
In 2020, varying degrees of inconsistencies between facility registers and HMIS reports were observed, ranging from - 2.57 to 0.67% for BCG, -13.85% to -1.45% for Penta3, and - 8.30-2.00% for MR1. Only BCG data were entered in the e-Tracker in 2020. By 2022, e-Tracker completeness of Penta3 and MR1 had also increased substantially.
Data quality in the paper based HMIS was variable across districts and health facilities. Improvements in quality of e-Tracker data over time demonstrate increased uptake of e-Tracker use by health workers, possibly explained by the removal of paper documentation and reporting. Further improvements in data quality can be achieved by purposefully designed implementation strategies to support health workers with digital data entry.
卫生工作者对常规数据的记录和报告是儿童免疫规划的支柱。低收入和中等收入国家（LMICs）卫生管理信息系统（HMIS）的免疫数据往往不完整且不可靠。在卢旺达，自2019年以来，基于DHIS2开源软件构建的个人层面卫生管理信息系统（HMIS）——免疫电子追踪器已在全国实施并推广。本研究的目的是评估常规HMIS免疫数据随时间的质量。
数据来源于2020年1月至12月来自四个区的24个卫生机构的四个HMIS来源：卫生机构登记册（纸质）、区汇总报告（纸质）、国家HMIS报告（电子）和电子追踪器报告（电子）。然后，我们获取了同一机构2022年的电子追踪器报告和国家HMIS报告，并评估了随时间的变化。对四个选定的儿童免疫指标进行了数据质量评估：卡介苗（BCG）、五价疫苗3（Penta 3）和麻疹风疹1（MR1）。我们计算了频率和百分比差异。计算了2020年HMIS报告与机构登记册以及2022年电子追踪器的准确率。
2020年，观察到机构登记册与HMIS报告之间存在不同程度的不一致，卡介苗的不一致率在-2.57%至0.67%之间，五价疫苗3为-13.85%至-1.45%，麻疹风疹1为-8.30%至2.00%。2020年电子追踪器中仅录入了卡介苗数据。到2022年，五价疫苗3和麻疹风疹1的电子追踪器完整性也大幅提高。
基于纸质的HMIS中的数据质量在不同区和卫生机构之间存在差异。随着时间的推移，电子追踪器数据质量的提高表明卫生工作者对电子追踪器的使用增加，这可能是由于纸质文件记录和报告的取消。通过有针对性地设计实施策略以支持卫生工作者进行数字数据录入，可以进一步提高数据质量。
