Suppr超能文献

数字化医患沟通干预措施(InvolveMe):基于已确定的促进因素和障碍的实施准备情况的定性研究。

A Digital Patient-Provider Communication Intervention (InvolveMe): Qualitative Study on the Implementation Preparation Based on Identified Facilitators and Barriers.

机构信息

Department of Digital Health Research, Division of Medicine, Oslo University Hospital, Oslo, Norway.

Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway.

出版信息

J Med Internet Res. 2021 Apr 8;23(4):e22399. doi: 10.2196/22399.

Abstract

BACKGROUND

Chronic health conditions are affecting an increasing number of individuals, who experience various symptoms that decrease their quality of life. Digital communication interventions that enable patients to report their symptoms have been shown to positively impact chronic disease management by improving access to care, patient-provider communication, clinical outcomes, and health-related quality of life. These interventions have the potential to prepare patients and health care providers (HCPs) before visits and improve patient-provider communication. Despite the recent rapid development and increasing number of digital communication interventions that have shown positive research results, barriers to realizing the benefits offered through these types of interventions still exist.

OBJECTIVE

The aim of this study is to prepare for the implementation of a digital patient-provider communication intervention in the daily workflow at 2 outpatient clinics by identifying potential determinants of implementation using the Consolidated Framework for Implementation Research (CFIR) to tailor the use of digital communication intervention to the intended context and identify key aspects for an implementation plan.

METHODS

A combination of focus groups, workshops, and project steering committee meetings was conducted with HCPs (n=14) and patients (n=2) from 2 outpatient clinics at a university hospital. The CFIR was used to guide data collection and analysis. Transcripts, written minutes, and notes were analyzed and coded into 5 CFIR domains using thematic analysis.

RESULTS

Data were examined and analyzed into 18 CFIR constructs relevant to the study purpose. On the basis of the identified determinants, important intervention tailoring includes adjustments to the digital features and adjustments to fit the clinical workflow and a decision to conduct a future pilot study. Furthermore, it was decided to provide the intervention to patients as early as possible in their disease trajectory, with tailored information about its use. Key aspects for the implementation plan encompassed maintaining the identified engagement and positive attitude, involving key stakeholders in the implementation process, and providing the needed support and training.

CONCLUSIONS

This study offers insight into the involvement of stakeholders in the tailoring and implementation planning of a digital communication intervention in clinical practice. Stakeholder involvement in the identification of implementation facilitators and barriers can contribute to the tailoring of digital communication interventions and how they are used and can also inform systematic and targeted implementation planning.

摘要

背景

慢性健康状况影响着越来越多的人,他们经历着各种降低生活质量的症状。已经证明,能够让患者报告症状的数字通信干预措施通过改善获得医疗服务的机会、医患沟通、临床结果和与健康相关的生活质量,对慢性病管理产生积极影响。这些干预措施有可能在就诊前让患者和医疗保健提供者(HCP)做好准备,并改善医患沟通。尽管最近数字通信干预措施迅速发展并不断增加,并显示出积极的研究结果,但要实现这些类型的干预措施所带来的好处仍然存在障碍。

目的

本研究旨在通过使用整合实施研究框架(CFIR)确定潜在的实施决定因素,为在 2 家门诊诊所的日常工作中实施数字医患通信干预措施做准备,根据预期情况调整数字通信干预措施的使用,并确定实施计划的关键方面。

方法

在一家大学医院的 2 家门诊诊所中,对 HCP(n=14)和患者(n=2)进行了焦点小组、研讨会和项目指导委员会会议的组合。使用 CFIR 指导数据收集和分析。使用主题分析方法对记录、书面记录和笔记进行分析和编码为 5 个 CFIR 领域。

结果

根据确定的决定因素,对数据进行了检查和分析,确定了 18 个与研究目的相关的 CFIR 结构。在此基础上,对数字功能进行了重要的调整,并对其进行了调整,以适应临床工作流程,并决定进行未来的试点研究。此外,决定尽早在患者疾病进程中向患者提供干预措施,并提供有关其使用的个性化信息。实施计划的关键方面包括保持已确定的参与度和积极态度、让关键利益相关者参与实施过程以及提供必要的支持和培训。

结论

本研究深入了解了利益相关者在临床实践中数字通信干预措施的调整和实施计划中的参与。利益相关者参与确定实施促进因素和障碍,可以促进数字通信干预措施的调整以及如何使用这些措施,并为系统和有针对性的实施计划提供信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed8c/8294341/cffc447c2fda/jmir_v23i4e22399_fig1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验