Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Central Monitoring and Evaluation Division, Ministry of Health, Lilongwe, Malawi.
Glob Health Sci Pract. 2017 Sep 28;5(3):367-381. doi: 10.9745/GHSP-D-17-00177. Print 2017 Sep 27.
Routine health data can guide health systems improvements, but poor quality of these data hinders use. To address concerns about data quality in Malawi, the Ministry of Health and National Statistical Office conducted a data quality assessment (DQA) in July 2016 to identify systems-level factors that could be improved.
We used 2-stage stratified random sampling methods to select health centers and hospitals under Ministry of Health auspices, included those managed by faith-based entities, for this DQA. Dispensaries, village clinics, police and military facilities, tertiary-level hospitals, and private facilities were excluded. We reviewed client registers and monthly reports to verify availability, completeness, and accuracy of data in 4 service areas: antenatal care (ANC), family planning, HIV testing and counseling, and acute respiratory infection (ARI). We also conducted interviews with facility and district personnel to assess health management information system (HMIS) functioning and systems-level factors that may be associated with data quality. We compared systems and quality factors by facility characteristics using 2-sample tests with Welch's approximation, and calculated verification ratios comparing total entries in registers to totals from summarized reports.
We selected 16 hospitals (of 113 total in Malawi), 90 health centers (of 466), and 16 district health offices (of 28) in 16 of Malawi's 28 districts. Nearly all registers were available and complete in health centers and district hospitals, but data quality varied across service areas; median verification ratios comparing register and report totals at health centers ranged from 0.78 (interquartile range [IQR]: 0.25, 1.07) for ARI and 0.99 (IQR: 0.82, 1.36) for family planning to 1.00 (IQR: 0.96, 1.00) for HIV testing and counseling and 1.00 (IQR: 0.80, 1.23) for ANC. More than half (60%) of facilities reported receiving a documented supervisory visit for HMIS in the prior 6 months. A recent supervision visit was associated with better availability of data (=.05), but regular district- or central-level supervision was not. Use of data by the facility to track performance toward targets was associated with both improved availability (=.04) and completeness of data (=.02). Half of facilities had a full-time statistical clerk, but their presence did not improve the availability or completeness of data (=.39 and =.69, respectively).
Findings indicate both strengths and weaknesses in Malawi's HMIS performance, with key weaknesses including infrequent data quality checks and unreliable supervision. Efforts to strengthen HMIS in low- and middle-income countries should be informed by similar assessments.
常规健康数据可以指导卫生系统的改进，但数据质量差会阻碍数据的使用。为了解决马拉维对数据质量的担忧，卫生部和国家统计局于 2016 年 7 月进行了一次数据质量评估（DQA），以确定可能需要改进的系统层面因素。
我们使用 2 阶段分层随机抽样方法选择卫生部管理下的卫生中心和医院，包括由信仰实体管理的卫生中心，对这些机构进行 DQA。不包括诊所以及村庄诊所、警察和军事设施、三级医院和私人设施。我们审查了客户登记簿和每月报告，以验证 4 个服务领域（产前护理、计划生育、艾滋病毒检测和咨询、急性呼吸道感染）的数据可用性、完整性和准确性。我们还对设施和地区人员进行了访谈，以评估健康管理信息系统（HMIS）的运作情况以及可能与数据质量相关的系统层面因素。我们使用 2 样本 t 检验（带 Welch 近似值）比较了设施特征的系统和质量因素，并计算了将登记簿中的总条目与汇总报告中的总数进行比较的验证比率。
我们在马拉维的 28 个区中的 16 个区选择了 16 家医院（共 113 家）、90 家卫生中心（共 466 家）和 16 家区卫生办公室（共 28 家）。卫生中心和地区医院的几乎所有登记簿都可用且完整，但各服务领域的数据质量存在差异；卫生中心登记簿和报告总数比较的中位数验证比率范围从急性呼吸道感染的 0.78（四分位距 [IQR]：0.25，1.07）到计划生育的 0.99（IQR：0.82，1.36）到艾滋病毒检测和咨询的 1.00（IQR：0.96，1.00）和产前护理的 1.00（IQR：0.80，1.23）。超过一半（60%）的机构报告称，在过去 6 个月内收到了 HMIS 的书面监督访问。最近的监督访问与数据可用性的提高有关（=.05），但定期的地区或中央一级的监督并没有。设施使用数据来跟踪实现目标的绩效与数据的可用性（=.04）和完整性（=.02）均呈正相关。一半的机构都有一名全职统计员，但他们的存在并没有提高数据的可用性或完整性（=.39 和 =.69）。
调查结果表明，马拉维的 HMIS 性能既有优势也有劣势，主要弱点包括数据质量检查不频繁和监督不可靠。在中低收入国家加强 HMIS 应根据类似的评估进行。
