Identification and classification of indicators for evaluating health information systems

IF 3.4 3区 医学 Q1 HEALTH POLICY & SERVICES
Habibeh Norouzi , Mohammad Hossein Mehrolhassani , Sadrieh Hajesmaeel-Gohari , Leila Ahmadian , Mohammad Mehdi Ghaemi , Mehdi Mohammadi , Reza Khajouei
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引用次数: 0

Abstract

Background

Several evaluation methods are used to determine the advantages and disadvantages of healthcare information systems and their contribution to attaining organizational goals. Despite the existence of many evaluation frameworks, there is no comprehensive set of indicators that evaluate different dimensions of information systems. This study aimed to develop a set of indicators for evaluating health information systems.

Methods

This research was conducted in three phases. First, based on a literature review of PubMed, Web of Science, Scopus, and Embase databases, studies using the health information system evaluation methods were extracted. Second, consecutive focus group meetings were held with scientific and executive experts to discuss the list of evaluation indicators extracted from the studies. In these meetings, the experts agreed on including, removing, adding, combining, and grouping the indicators. Third, the indicators were weighted using the Analytical Network Process (ANP) method, and the set of evaluation indicators was finalized.

Results

The review of 177 relevant articles resulted in the extraction of 360 indicators. During the focus group meetings, 174 overlapping and duplicate indicators were eliminated and 61 indicators were added to the model based on experts’ suggestions. The remaining 247 indicators were classified into a four-level hierarchy. The final set consisted of 4 dimensions, 16 criteria, 47 markers, and 180 indicators.

Conclusion

We developed a comprehensive general set of indicators that helps researchers, designers, and developers of health information systems to evaluate different dimensions of these systems. This set can also be used to improve the design of relevant systems.

确定卫生信息系统评估指标并进行分类
背景:有几种评估方法可用于确定医疗信息系统的优缺点及其对实现组织目标的贡献。尽管存在许多评估框架,但并没有一套全面的指标来评估信息系统的不同方面。本研究旨在制定一套用于评估医疗信息系统的指标:本研究分三个阶段进行。首先,在对 PubMed、Web of Science、Scopus 和 Embase 数据库进行文献综述的基础上,提取了使用卫生信息系统评价方法的研究。其次,与科学专家和执行专家连续召开焦点小组会议,讨论从研究中提取的评价指标清单。在这些会议上,专家们就指标的包含、删除、添加、合并和分组达成了一致意见。第三,使用分析网络过程(ANP)方法对指标进行加权,最终确定了评价指标集:通过对 177 篇相关文章的审查,提取了 360 个指标。在焦点小组会议上,剔除了 171 个重叠和重复的指标,并根据专家建议在模型中增加了 61 个指标。剩余的 250 个指标被分为四级。最终的指标集包括 4 个维度、16 个标准、47 个标记和 182 个指标:我们开发了一套全面的通用指标,可帮助医疗信息系统的研究人员、设计人员和开发人员对这些系统的不同维度进行评估。这套指标还可用于改进相关系统的设计。
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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来源期刊
Health Policy and Technology
Health Policy and Technology Medicine-Health Policy
CiteScore
9.20
自引率
3.30%
发文量
78
审稿时长
88 days
期刊介绍: Health Policy and Technology (HPT), is the official journal of the Fellowship of Postgraduate Medicine (FPM), a cross-disciplinary journal, which focuses on past, present and future health policy and the role of technology in clinical and non-clinical national and international health environments. HPT provides a further excellent way for the FPM to continue to make important national and international contributions to development of policy and practice within medicine and related disciplines. The aim of HPT is to publish relevant, timely and accessible articles and commentaries to support policy-makers, health professionals, health technology providers, patient groups and academia interested in health policy and technology. Topics covered by HPT will include: - Health technology, including drug discovery, diagnostics, medicines, devices, therapeutic delivery and eHealth systems - Cross-national comparisons on health policy using evidence-based approaches - National studies on health policy to determine the outcomes of technology-driven initiatives - Cross-border eHealth including health tourism - The digital divide in mobility, access and affordability of healthcare - Health technology assessment (HTA) methods and tools for evaluating the effectiveness of clinical and non-clinical health technologies - Health and eHealth indicators and benchmarks (measure/metrics) for understanding the adoption and diffusion of health technologies - Health and eHealth models and frameworks to support policy-makers and other stakeholders in decision-making - Stakeholder engagement with health technologies (clinical and patient/citizen buy-in) - Regulation and health economics
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