Chekol Afework, Ketemaw Asmamaw, Endale Addisu, Aschale Abiot, Endalew Bekalu, Asemahagn Mulusew Andualem
Department of Nursing, Bahir Dar Health Sciences College, Bahir Dar, Ethiopia.
School of Public Health, College of Medicine and Health Sciences, Bahir Dar University, Bahir Dar, Ethiopia.
Front Health Serv. 2023 Mar 24;3:1059611. doi: 10.3389/frhs.2023.1059611. eCollection 2023.
Data quality is a multidimensional term that includes accuracy, precision, completeness, timeliness, integrity, and confidentiality. The quality of data generated by a routine health information system (RHIS) is still very poor in low- and middle-income countries. There is a paucity of studies as to what determines data quality in health facilities in the study area. Therefore, the aim of the present study was to assess the magnitude of the quality of routine health information system data and its determinants among health centers.
A facility-based quantitative study design triangulated by the qualitative method was conducted. A total of 314 health professionals from 32 health centers were selected using a simple random sampling procedure. Data were gathered using a standardized checklist, interviewer-administered questionnaires, and key informant interview guidelines. Descriptive statistics were used to describe variables and binary logistic regression was used to identify factors associated with data quality using STATA version 14. Variables with -value <0.25 in the bivariate analysis were entered to a multivariable logistic regression analysis. -values <0.05 at 95% confidence intervals (CI) were taken to be statistically significant. A manual analysis was conducted for the qualitative data collected from purposively selected key informants.
The study found that the overall data quality at the health centers of West Gojjam Zone was 74% (95% CI 68-78). The complexity of the routine health information system format [adjusted odds ratio (AOR) 3.8; 95% CI 1.7-8.5], problem-solving skills for RHIS tasks (AOR 2.8; 95% CI 1.2-6.4), and knowing duties, roles, and responsibilities were significantly associated with data quality (AOR 12; 95% CI 5.6-25.8), and lack of human resources, poor feedback mechanisms, delay in completing data records, lack of data use, and inadequate training on health information systems were barriers affecting data quality.
The level of data quality among public health centers in the Amhara region was lower than expected at the national level.
数据质量是一个多维度的概念,包括准确性、精确性、完整性、及时性、完整性和保密性。在低收入和中等收入国家,常规卫生信息系统(RHIS)产生的数据质量仍然很差。关于研究区域内卫生设施中决定数据质量的因素,相关研究较少。因此,本研究的目的是评估卫生中心常规卫生信息系统数据的质量及其决定因素。
采用基于设施的定量研究设计,并通过定性方法进行三角验证。使用简单随机抽样程序从32个卫生中心共选取了314名卫生专业人员。通过标准化清单、访谈员管理的问卷和关键信息提供者访谈指南收集数据。使用描述性统计来描述变量,并使用二元逻辑回归分析,通过STATA 14版本来确定与数据质量相关的因素。在双变量分析中,P值<0.25的变量被纳入多变量逻辑回归分析。在95%置信区间(CI)下,P值<0.05被认为具有统计学意义。对从有目的地选择的关键信息提供者收集的定性数据进行了人工分析。
研究发现,西戈贾姆地区卫生中心的总体数据质量为74%(95%CI 68 - 78)。常规卫生信息系统格式的复杂性[调整后的优势比(AOR)3.8;95%CI 1.7 - 8.5]、RHIS任务的解决问题能力(AOR 2.8;95%CI 1.2 - 6.4)以及对职责、角色和责任的了解与数据质量显著相关(AOR 12;95%CI 5.6 - 25.8),而人力资源短缺、反馈机制不佳、数据记录完成延迟、缺乏数据使用以及卫生信息系统培训不足是影响数据质量的障碍。
阿姆哈拉地区公共卫生中心的数据质量水平低于国家层面的预期。