利用实施图谱为癌症康复电子前瞻性监测模型制定多方面的实施策略。

Christian J Lopez, Sarah E Neil-Sztramko, Mounir Tanyoas, Kristin L Campbell, Jackie L Bender, Gillian Strudwick, David M Langelier, Tony Reiman, Jonathan Greenland, Jennifer M Jones
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引用次数: 0

摘要

背景:电子前瞻性监测模型(ePSMs)可在癌症护理期间的预定时间点通过患者报告的结果远程监测癌症患者的康复需求,并提供支持,包括与自我管理教育和社区项目的链接,以及进一步临床筛查和康复转诊的建议。以往关于实施电子病历管理系统的指南对这些系统实施策略的选择方法缺乏足够详细的说明。本文旨在介绍我们如何为 REACH 制定实施计划,REACH 是为乳腺癌、结直肠癌、淋巴瘤和头颈部癌症设计的电子病历管理系统:方法:实施绘图指导了实施计划的制定过程。我们整合了我们团队进行的范围审查和定性研究的结果,以确定实施的决定因素、实施参与者和行动以及相关结果。我们使用实施研究综合框架 (CFIR) 对决定因素进行了分类,并以实施结果分类法为指导确定了结果。然后,使用 CFIR-ERIC 匹配工具将决定因素与实施变革专家建议(ERIC)的战略分类法进行映射。通过我们团队之间的讨论和知识用户的反馈,考虑到每种策略的可行性、通过Go-Zone图进行的重要性评级、可行性和对临床环境的适用性,以及在我们的范围综述中报告的其他ePSM中的使用情况,我们对所产生的策略列表进行了改进:结果:在 39 个 CFIR 结构中,有 22 个被确定为相关决定因素。诊所管理者、信息技术团队以及在患者教育中扮演重要角色的医疗服务提供者被认为是重要的参与者。通过 CFIR-ERIC 匹配工具,50 项策略获得了 1 级认可,13 项策略获得了 2 级认可。最终的策略清单包括:1)有目的地重新检查实施情况;2)量身定制策略;3)改变记录系统;4)召开教育会议;5)分发教育材料;6)对患者进行干预以提高其接受度和依从性;7)集中技术援助;8)利用咨询委员会和工作组:我们提出了一种可推广的方法,该方法结合了 "实施绘图 "的步骤,让各种知识使用者参与其中,并利用实施科学框架来促进实施战略的制定。目前正在利用实施成果框架对实施成功与否进行评估。
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Use of implementation mapping to develop a multifaceted implementation strategy for an electronic prospective surveillance model for cancer rehabilitation.

Background: Electronic Prospective Surveillance Models (ePSMs) remotely monitor the rehabilitation needs of people with cancer via patient-reported outcomes at pre-defined time points during cancer care and deliver support, including links to self-management education and community programs, and recommendations for further clinical screening and rehabilitation referrals. Previous guidance on implementing ePSMs lacks sufficient detail on approaches to select implementation strategies for these systems. The purpose of this article is to describe how we developed an implementation plan for REACH, an ePSM system designed for breast, colorectal, lymphoma, and head and neck cancers.

Methods: Implementation Mapping guided the process of developing the implementation plan. We integrated findings from a scoping review and qualitative study our team conducted to identify determinants to implementation, implementation actors and actions, and relevant outcomes. Determinants were categorized using the Consolidated Framework for Implementation Research (CFIR), and the implementation outcomes taxonomy guided the identification of outcomes. Next, determinants were mapped to the Expert Recommendations for Implementing Change (ERIC) taxonomy of strategies using the CFIR-ERIC Matching Tool. The list of strategies produced was refined through discussion amongst our team and feedback from knowledge users considering each strategy's feasibility and importance rating via the Go-Zone plot, feasibility and applicability to the clinical contexts, and use among other ePSMs reported in our scoping review.

Results: Of the 39 CFIR constructs, 22 were identified as relevant determinants. Clinic managers, information technology teams, and healthcare providers with key roles in patient education were identified as important actors. The CFIR-ERIC Matching Tool resulted in 50 strategies with Level 1 endorsement and 13 strategies with Level 2 endorsement. The final list of strategies included 1) purposefully re-examine the implementation, 2) tailor strategies, 3) change record systems, 4) conduct educational meetings, 5) distribute educational materials, 6) intervene with patients to enhance uptake and adherence, 7) centralize technical assistance, and 8) use advisory boards and workgroups.

Conclusion: We present a generalizable method that incorporates steps from Implementation Mapping, engages various knowledge users, and leverages implementation science frameworks to facilitate the development of an implementation strategy. An evaluation of implementation success using the implementation outcomes framework is underway.

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