Epidemiology and Biostatistics Department, Public Health Regional Institute, University of Abomey-Calavi, Abomey-Calavi, Benin ; Center of research in Epidemiology, Biostatistics and Clinical Research, School of Public Health, Université Libre de Bruxelles, Bruxelles, Belgium.
Epidemiology and Biostatistics Department, Public Health Regional Institute, University of Abomey-Calavi, Abomey-Calavi, Benin.
Arch Public Health. 2014 Jul 28;72(1):25. doi: 10.1186/2049-3258-72-25. eCollection 2014.
Routine health information systems (RHIS) are crucial to the acquisition of data for health sector planning. In developing countries, the insufficient quality of the data produced by these systems limits their usefulness in regards to decision-making. The aim of this study was to identify the factors associated with poor data quality in the RHIS in Benin.
This cross-sectional descriptive and analytical study included health workers who were responsible for data collection in public and private health centers. The technique and tools used were an interview with a self-administered questionnaire. The dependent variable was the quality of the data. The independent variables were socio-demographic and work-related characteristics, personal and work-related resources, and the perception of the technical factors. The quality of the data was assessed using the Lot Quality Assurance Sampling method. We used survival analysis with univariate proportional hazards (PH) Cox models to derive hazards ratios (HR) and their 95% confidence intervals (95% CI). Focus group data were evaluated with a content analysis.
A significant link was found between data quality and level of responsibility (p = 0.011), sector of employment (p = 0.007), RHIS training (p = 0.026), level of work engagement (p < 0.001), and the level of perceived self-efficacy (p = 0.03). The focus groups confirmed a positive relationship with organizational factors such as the availability of resources, supervision, and the perceived complexity of the technical factors.
This exploratory study identified several factors associated with the quality of the data in the RHIS in Benin. The results could provide strategic decision support in improving the system's performance.
常规卫生信息系统（RHIS）对于获取卫生部门规划数据至关重要。在发展中国家，这些系统产生的数据质量不足限制了其在决策方面的有用性。本研究旨在确定贝宁 RHIS 数据质量差的相关因素。
这是一项横断面描述性和分析性研究，包括负责公共和私人卫生中心数据收集的卫生工作者。使用的技术和工具是对自我管理问卷进行访谈。因变量是数据质量。自变量是社会人口学和工作相关特征、个人和工作相关资源以及对技术因素的看法。使用 Lot Quality Assurance Sampling 方法评估数据质量。我们使用单变量比例风险（PH）Cox 模型进行生存分析，得出风险比（HR）及其 95%置信区间（95%CI）。使用内容分析法评估焦点小组数据。
数据质量与责任级别（p=0.011）、就业部门（p=0.007）、RHIS 培训（p=0.026）、工作投入程度（p<0.001）和自我效能感水平（p=0.03）之间存在显著关联。焦点小组证实了与组织因素的积极关系，例如资源的可用性、监督以及对技术因素的感知复杂性。
这项探索性研究确定了与贝宁 RHIS 数据质量相关的几个因素。研究结果可为改善系统性能提供战略决策支持。
