评估新兴大健康数据平台的影响:逻辑模型和q -方法学方法

Justin Connolly, A. Staines, R. Connolly, A. Boilson, P. Davis, D. Weston, N. Bloodworth
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引用次数: 3

摘要

尽管技术和医学科学取得了进步,但由于许多因素,现代基于健康的项目容易出现系统性失败。这些问题包括it开发人员缺乏对最终用户需求的认识,有关各方之间沟通不畅,以及对新兴系统的测试不适当或不充分。其他问题可能是外部问题(例如政治和法律问题),例如共享患者数据和有关同意的问题。本文的目标是采用当前发展中的一个主要的基于健康的欧洲模式,并探讨它如何满足四个不同国家的四个机构的需求,以及它将如何满足各自的需求。评估是在逻辑模型中设计的,并使用框架方法和q -方法论来评估影响和评估。在项目的每个阶段,将通过与主要利益相关者和开发人员进行纵向半结构化访谈和q评分来收集数据。这种方法,反复与项目中相同的关键参与者进行访谈,将有助于确保在it开发人员和系统的最终用户之间存在相互理解。最后一个系统旨在为决策者提供有效的基于卫生的决策支持系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluating Impact of an Emerging Big Health Data Platform: A Logic Model and Q-Methodology Approach
Despite advances in technology and medical science, modern health-based projects are open to systemic failure due to many factors. These include I.T. developer’s lack of awareness with regard to end-user needs, poor communication amongst all parties concerned and inappropriate or inadequate tests of the emerging system. Other issues may be external (e.g. political and legal) such as sharing of patient data and issues surrounding consent. The goal of this paper is to take a major health-based European model in current development and explore how it addresses the needs of four institutions in four different countries, and how it will meet their respective needs. The evaluation was designed within a Logic Model, and uses the Framework approach, and Q-Methodology to assess both impact and evaluation. Data will be collected through longitudinal semi-structured interviews and Q-scoring with principal stakeholders and developers at each stage of the project. This approach, recurring interviews with the same key players in the project, will help ensure that there is mutual understanding between I.T. developers and end-users of the system. The final system is meant to provide effective health-based decision support systems for policy makers.
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