识别和优化影响快速医疗互操作性资源加速器实施的因素:使用实施研究的统一框架的定性研究-实施变革方法的专家建议。

IF 3.1 3区 医学 Q2 MEDICAL INFORMATICS
Jane Li, Emma Maddock, Michael Hosking, Kate Ebrill, Jeremy Sullivan, Kylynn Loi, Danielle Tavares-Rixon, Rajiv Jayasena, Grahame Grieve, Alana Delaforce
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引用次数: 0

摘要

背景:众所周知,零碎的卫生信息共享会对患者护理和结果产生负面影响。为了支持系统之间的健康信息共享,快速医疗保健互操作性资源(FHIR)已成为健康信息交换的全球互操作性标准。为了加快采用过程,已经成立了各种FHIR加速小组。FHIR加速器,如澳大利亚的“火花”项目,使社区和协作团体能够制定高质量的FHIR标准,用于医疗保健信息交换,并鼓励广泛采用。然而,关于FHIR加速器计划的开发、交付和实施的研究有限。目的:本研究采用定性方法确定了火花FHIR加速器的关键组成部分,哪些因素影响实施,哪些策略可能有助于提高其交付。方法:在项目的早期阶段与被激发的利益相关者进行半结构化访谈。使用标准化报告清单(干预描述和复制模板)描述了火花FHIR加速器干预组件。采用实施研究综合框架(CFIR) 2.0分析影响实施的因素。在累积多数分析的基础上,确定了最常提到的影响实施的因素。然后将这些因素映射到实施变革的专家建议(ERIC)工具中,以确定加强实施火花计划的策略。结果:总共采访了17位参与者,包括项目负责人、联合主席、软件行业实现者代表、临床医生和消费者。总共确定了8个关键的CFIR影响因素:参与、创新设计、评估需求、当地条件、获取知识和信息、伙伴关系和联系、能力和工作基础设施。在将CFIR的主要影响因素映射到ERIC工具后,确定了5个策略集群:适应和定制上下文,发展利益相关者之间的关系,支持参与者,培训和教育利益相关者,以及使用评估和迭代策略。结论:本研究确定了火花FHIR加速器的核心组件,并确定了对计划实施影响最大的因素。使用cfr - eric方法有助于生成专家建议,以改进该工具的实施,但需要研究人员的建议来补充该工具。这项研究为决策者和实施者提供了有价值的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identifying and Optimizing Factors Influencing the Implementation of a Fast Healthcare Interoperability Resources Accelerator: Qualitative Study Using the Consolidated Framework for Implementation Research-Expert Recommendations for Implementing Change Approach.

Background: Fragmented sharing of health information is known to negatively impact patient care and outcomes. To support the sharing of health information between systems, Fast Healthcare Interoperability Resources (FHIR) has emerged as the global interoperability standard for health information exchange. To speed up the process of adoption, various FHIR accelerator groups have been formed. FHIR accelerators such as the Sparked program in Australia enable communities and collaborative groups to develop high-quality FHIR standards for health care information exchange and encourage widespread uptake. However, limited research exists on the development, delivery, and implementation of FHIR accelerator programs.

Objective: This study used qualitative methods to identify the key components of the Sparked FHIR accelerator, what factors influence implementation, and which strategies may help enhance its delivery.

Methods: Semistructured interviews were conducted with Sparked stakeholders in the early stage of the program. The Sparked FHIR accelerator intervention components were described using a standardized reporting checklist (Template for Intervention Description and Replication). The Consolidated Framework for Implementation Research (CFIR) 2.0 was used to analyze factors influencing implementation. On the basis of a cumulative majority analysis, the most mentioned factors influencing implementation were identified. These factors were then mapped to the Expert Recommendations for Implementing Change (ERIC) tool to identify strategies for enhancing the implementation of the Sparked program.

Results: A total of 17 participants were interviewed, including program leads, cochairs, representatives of software industry implementers, clinicians, and consumers. In total, 8 key CFIR influencing factors were identified: engaging, innovation design, assessing needs, local conditions, access to knowledge and information, partnerships and connections, capability, and work infrastructure. After mapping the top CFIR influencing factors to the ERIC tool, 5 strategy clusters were identified: adapt and tailor to context, develop stakeholder interrelations, support participants, train and educate stakeholders, and use evaluative and iterative strategies.

Conclusions: This study enabled the core components of the Sparked FHIR accelerator to be defined and identified the factors that have the strongest influence on program implementation. Using the CFIR-ERIC approach facilitated the generation of expert-informed recommendations for improving the implementation of Sparked, but researcher recommendations were needed to supplement the tool. This research offers valuable insights for decision makers and implementers.

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来源期刊
JMIR Medical Informatics
JMIR Medical Informatics Medicine-Health Informatics
CiteScore
7.90
自引率
3.10%
发文量
173
审稿时长
12 weeks
期刊介绍: JMIR Medical Informatics (JMI, ISSN 2291-9694) is a top-rated, tier A journal which focuses on clinical informatics, big data in health and health care, decision support for health professionals, electronic health records, ehealth infrastructures and implementation. It has a focus on applied, translational research, with a broad readership including clinicians, CIOs, engineers, industry and health informatics professionals. Published by JMIR Publications, publisher of the Journal of Medical Internet Research (JMIR), the leading eHealth/mHealth journal (Impact Factor 2016: 5.175), JMIR Med Inform has a slightly different scope (emphasizing more on applications for clinicians and health professionals rather than consumers/citizens, which is the focus of JMIR), publishes even faster, and also allows papers which are more technical or more formative than what would be published in the Journal of Medical Internet Research.
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