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影响南非常规收集数据质量的人为因素。

Human factors affecting the quality of routinely collected data in South Africa.

作者信息

Nicol Edward, Bradshaw Debbie, Phillips Tamsin, Dudley Lilian

机构信息

Burden of Disease Research Unit, South African Medical Research Council.

出版信息

Stud Health Technol Inform. 2013;192:788-92.

Abstract

Evaluations that have looked at the people aspect of the health information system in South Africa have only focused on the availability of human resources and not on competence or other behavioural factors. Using the Performance of Routine Information System Management (PRISM) tool that assumes relationships between technical, behavioural and organizational determinants of the routine information processes and performance, this paper highlights some behavioural factors affecting the quality of routinely collected data in South Africa. In the context of monitoring maternal and child health programmes, data were collected from 161 health information personnel in 58 health facilities and 2 district offices from 2 conveniently sampled health districts. A self-administered questionnaire was used to assess confidence and competence levels of routine health information system (RHIS) tasks, problem solving anddata quality checking skills, and motivation. The findings suggest that 64% of the respondents have poor numerical skills and limited statistical and data quality checking skills. While the average confidence levels at performing RHIS tasks is 69%, only 22% actually displayed competence above 50%. Personnel appear to be reasonably motivated but there is considerable deficiency in their competency to interpret and use data. This may undermine the quality and utility of the RHIS.

摘要

南非针对卫生信息系统中人员方面的评估仅关注人力资源的可用性,而未关注能力或其他行为因素。本文使用常规信息系统管理绩效(PRISM)工具,该工具假定常规信息流程和绩效的技术、行为和组织决定因素之间存在关联,着重介绍了一些影响南非常规收集数据质量的行为因素。在监测母婴健康项目的背景下,从两个方便抽样的卫生区的58个卫生设施和2个地区办事处的161名卫生信息人员处收集了数据。使用一份自填式问卷来评估常规卫生信息系统(RHIS)任务的信心和能力水平、解决问题和数据质量检查技能以及积极性。研究结果表明,64%的受访者数字技能较差,统计和数据质量检查技能有限。虽然执行RHIS任务的平均信心水平为69%,但实际能力超过50%的受访者仅占22%。人员似乎有合理的积极性,但他们解释和使用数据的能力存在相当大的不足。这可能会损害RHIS的质量和效用。

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