Users Perception and Factors Affecting Data Quality in Nyarugenge Public Health Facility, Rwanda

B. Habimana, E. Rutayisire
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Abstract

The study evaluated the users' opinions on data quality and related characteristics in ten public-health institutions of Nyarugenge district. A study used a cross-sectional design, data was collected through quantitative (n=150) methodology while qualitative data was obtained using interviews (n=20) and focus group talks (n=3). A checklist was utilized to examine the completeness, accuracy, and timeliness of data quality aspects. Collected quantitative data was analyzed through logistic regression by SPSS to examine the association of variables, while qualitative data was analyzed using the summative content analysis (SCA) to summarize the key themes. A 95 percent confidence level, Odds Ratio (AOR) were used to establish the strength of correlation among study variables, while a p-value of less than (p<0.05) was utilized to identify the variables which were statistically significant associated to HMIS data quality. The study finding showed that the majority (53.0%) was female while, 33 years was an average age, the majority of health practitioner (52.7%) had an A1 diploma. Approximately 90.6% of respondents have a positive perceptions on the system usage. Limited ability and a lack of relevant technology equipment such as computers and the internet have been cited as the challenges while using the system. Factors such as training AOR:2.62(95% CI:1.45, supervision AOR:1.81(95% CI:1.02, AOR:2.50(95% CI:0.85 for education background, works-experience AOR:1.60(95% CI:090 are factors associated with data quality. Maintaining, supportive supervision, regular training and refresher courses should be regularly offered to public health professionals to improve their knowledge in order to maximize the use of health information.
卢旺达尼亚鲁热格公共卫生设施的用户感知和影响数据质量的因素
本研究评价了尼亚若热格区10个公共卫生机构用户对数据质量及相关特征的意见。本研究采用横断面设计,通过定量(n=150)方法收集数据,通过访谈(n=20)和焦点小组谈话(n=3)获得定性数据。使用检查表检查数据质量方面的完整性、准确性和及时性。收集到的定量数据通过SPSS进行逻辑回归分析,检验变量之间的关联,而定性数据使用总结性内容分析(SCA)进行分析,总结关键主题。采用95%置信水平的优势比(Odds Ratio, AOR)来确定研究变量之间的相关性强度,而采用小于(p<0.05)的p值来确定与HMIS数据质量有统计学意义的变量。研究结果表明,大多数(53.0%)为女性,平均年龄为33岁,大多数(52.7%)卫生从业人员拥有A1文凭。约90.6%的受访者对系统的使用持正面看法。有限的能力和缺乏相关的技术设备,如电脑和互联网被认为是使用该系统的挑战。培训AOR:2.62(95% CI:1.45)、监督AOR:1.81(95% CI:1.02)、AOR:2.50(95% CI:0.85)、工作经验AOR:1.60(95% CI:090)等因素是与数据质量相关的因素。应定期向公共卫生专业人员提供维护、支持性监督、定期培训和进修课程,以提高他们的知识,最大限度地利用卫生信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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