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确定优化电子病历为辅助医疗专业人员提供服务的机会:概念映射研究。

Identifying opportunities to optimise the electronic medical record for allied health professionals: a concept mapping study.

机构信息

Allied Health, Metro South Hospital and Health Service, Qld, Australia.

Centre for Functioning and Health Research, Metro South Hospital and Health Service, Queensland Health, Qld, Australia; and School of Health and Rehabilitation Sciences, The University of Queensland, Brisbane, Qld, Australia.

出版信息

Aust Health Rev. 2023 Jun;47(3):369-378. doi: 10.1071/AH22288.

Abstract

Objective To utilise a concept mapping process to identify key opportunities for electronic medical record (EMR) optimisation for allied health professionals (AHPs). Methods A total of 26 participants (allied health managers, clinicians and healthcare consumers) completed the concept mapping process, which included generating statements, and then subsequently sorting all statements into groups, and also ranking each statement for importance and changeability (0 = not important/changeable, 4 extremely important/changeable). Multivariate analysis and multidimensional scaling were then used to identify core priorities for digital optimisation. Results Participants generated 98 discrete statements that were grouped into 13 conceptual clusters. Of these, 36 statements were subsequently determined to fall within the 'green zone' on the Go-Zone plot of importance and changeability (changeability ≥2.44, importance ≥2.79), and formed the set of key optimisation priorities. Clusters with the most items in the Go-Zone plot were 'training and business rules ' and 'service statistics .' Conclusion Concept mapping facilitated identification of 36 key optimisation priorities considered both changeable and important to assist EMR optimisation for AHPs. Addressing these priorities requires action related to end-user skills and training, EMR system capacity, and streamlining of governance and collaboration for the optimisation process.

摘要

目的

利用概念映射过程确定电子病历(EMR)优化的关键机会,以满足辅助医疗专业人员(AHPs)的需求。

方法

共有 26 名参与者(辅助医疗管理人员、临床医生和医疗保健消费者)完成了概念映射过程,包括生成陈述,然后将所有陈述分组,并对每个陈述的重要性和可变性进行排名(0=不重要/不可变,4=极其重要/可变)。然后使用多变量分析和多维尺度分析来确定数字优化的核心优先级。

结果

参与者生成了 98 个离散陈述,这些陈述被分为 13 个概念集群。其中,36 个陈述随后被确定为重要性和可变性的“绿色区域”(可变性≥2.44,重要性≥2.79),并形成了关键优化优先级的集合。在重要性和可变性的 Go-Zone 图中,具有最多项目的集群是“培训和业务规则”和“服务统计”。

结论

概念映射有助于确定 36 个关键优化优先级,这些优先级被认为既具有可变性又重要,有助于辅助医疗人员的 EMR 优化。解决这些优先级需要采取与最终用户技能和培训、EMR 系统容量以及优化过程的治理和协作简化相关的行动。

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