Maternal and Child Health Program, Partners In Health/Inshuti Mu Buzima, Kigali, Rwanda.
Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, United States of America.
PLoS One. 2020 Jul 17;15(7):e0235823. doi: 10.1371/journal.pone.0235823. eCollection 2020.
INTRODUCTION: Reliable Health Management and Information System (HMIS) data can be used with minimal cost to identify areas for improvement and to measure impact of healthcare delivery. However, variable HMIS data quality in low- and middle-income countries limits its value in monitoring, evaluation and research. We aimed to review the quality of Rwandan HMIS data for maternal and newborn health (MNH) based on consistency of HMIS reports with facility source documents. METHODS: We conducted a cross-sectional study in 76 health facilities (HFs) in four Rwandan districts. For 14 MNH data elements, we compared HMIS data to facility register data recounted by study staff for a three-month period in 2017. A HF was excluded from a specific comparison if the service was not offered, source documents were unavailable or at least one HMIS report was missing for the study period. World Health Organization guidelines on HMIS data verification were used: a verification factor (VF) was defined as the ratio of register over HMIS data. A VF<0.90 or VF>1.10 indicated over- and under-reporting in HMIS, respectively. RESULTS: High proportions of HFs achieved acceptable VFs for data on the number of deliveries (98.7%;75/76), antenatal care (ANC1) new registrants (95.7%;66/69), live births (94.7%;72/76), and newborns who received first postnatal care within 24 hours (81.5%;53/65). This was slightly lower for the number of women who received iron/folic acid (78.3%;47/60) and tested for syphilis in ANC1 (67.6%;45/68) and was the lowest for the number of women with ANC1 standard visit (25.0%;17/68) and fourth standard visit (ANC4) (17.4%;12/69). The majority of HFs over-reported on ANC4 (76.8%;53/69) and ANC1 (64.7%;44/68) standard visits. CONCLUSION: There was variable HMIS data quality by data element, with some indicators with high quality and also consistency in reporting trends across districts. Over-reporting was observed for ANC-related data requiring more complex calculations, i.e., knowledge of gestational age, scheduling to determine ANC standard visits, as well as quality indicators in ANC. Ongoing data quality assessments and training to address gaps could help improve HMIS data quality.
简介：可靠的健康管理和信息系统（HMIS）数据可以以最低的成本使用，以确定改进的领域并衡量医疗保健提供的影响。然而，在中低收入国家，HMIS 数据质量的变化限制了其在监测、评估和研究方面的价值。我们旨在根据 HMIS 报告与医疗机构源文件的一致性，审查卢旺达母婴健康（MNH）的 HMIS 数据质量。
方法：我们在卢旺达四个地区的 76 个卫生设施（HFs）中进行了一项横断面研究。对于 14 个母婴健康数据要素，我们将 HMIS 数据与研究人员在 2017 年三个月期间记录的设施登记数据进行了比较。如果某项服务未提供、源文件不可用或研究期间至少缺少一份 HMIS 报告，则将 HF 排除在特定比较之外。我们使用了世界卫生组织关于 HMIS 数据验证的指南：验证因子（VF）定义为登记数据与 HMIS 数据的比值。VF<0.90 或 VF>1.10 分别表示 HMIS 报告中存在过度报告和漏报。
结果：大多数 HF 达到了可接受的交付数量（98.7%；75/76）、第一次产前护理（ANC1）新登记人数（95.7%；66/69）、活产数量（94.7%；72/76）和新生儿在 24 小时内接受第一次产后护理的比例（81.5%；53/65）。接受铁/叶酸（78.3%；47/60）和 ANC1 梅毒检测（67.6%；45/68）的妇女数量略低，接受 ANC1 标准检查（25.0%；17/68）和第四次标准检查（ANC4）的妇女数量最低（17.4%；12/69）。大多数 HF 对 ANC4（76.8%；53/69）和 ANC1（64.7%；44/68）标准检查进行了过度报告。
结论：数据元素的 HMIS 数据质量存在差异，一些指标的质量很高，而且各地区报告趋势也具有一致性。ANC 相关数据需要更复杂的计算，即对孕龄的了解、安排以确定 ANC 标准检查，以及 ANC 中的质量指标，存在过度报告。正在进行的数据质量评估和解决差距的培训可以帮助提高 HMIS 数据质量。
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