Suppr超能文献

在新冠疫情期间,英国养老院中数字版新冠症状追踪器的实施、采用及使用情况:一项混合方法、多地点的案例研究

Implementation, uptake and use of a digital COVID-19 symptom tracker in English care homes in the coronavirus pandemic: a mixed-methods, multi-locality case study.

作者信息

Nelson Pauline A, Bradley Fay, Ullah Akbar, Whittaker Will, Brunton Lisa, Calovski Vid, Money Annemarie, Dowding Dawn, Cullum Nicky, Wilson Paul

机构信息

Division of Nursing, Midwifery & Social Work, School of Health Sciences, Faculty of Biology Medicine and Health, The University of Manchester, Room 6.312, Jean McFarlane Building, Oxford Road, Manchester, M13 9PL, UK.

Manchester Centre for Health Economics, Faculty of Biology Medicine and Health, The University of Manchester, Jean McFarlane Building, Oxford Road, Manchester, M13 9PL, UK.

出版信息

Implement Sci Commun. 2023 Jan 17;4(1):7. doi: 10.1186/s43058-022-00387-y.

Abstract

BACKGROUND

COVID-19 spread rapidly in UK care homes for older people in the early pandemic. National infection control recommendations included remote resident assessment. A region in North-West England introduced a digital COVID-19 symptom tracker for homes to identify early signs of resident deterioration to facilitate care responses. We examined the implementation, uptake and use of the tracker in care homes across four geographical case study localities in the first year of the pandemic.

METHODS

This was a rapid, mixed-methods, multi-locality case study. Tracker uptake was calculated using the number of care homes taking up the tracker as a proportion of the total number of care homes in a locality. Mean tracker use was summarised at locality level and compared. Semi-structured interviews were conducted with professionals involved in tracker implementation and used to explore implementation factors across localities. Template Analysis with the Consolidated Framework for Implementation Research (CFIR) guided the interpretation of qualitative data.

RESULTS

Uptake varied across the four case study localities ranging between 13.8 and 77.8%. Tracker use decreased in all localities over time at different rates, with average use ranging between 18 and 58%. The implementation context differed between localities and the process of implementation deviated over time from the initially planned strategy, for stakeholder engagement and care homes' training. Four interpretative themes reflected the most influential factors appearing to affect tracker uptake and use: (1) the process of implementation, (2) implementation readiness, (3) clarity of purpose/perceived value and (4) relative priority in the context of wider system pressures.

CONCLUSIONS

Our study findings resonate with the digital solutions evidence base prior to the COVID-19 pandemic, suggesting three key factors that can inform future development and implementation of rapid digital responses in care home settings even in times of crisis: an incremental approach to implementation with testing of organisational readiness and attention to implementation climate, particularly the innovation's fit with local contexts (i.e. systems, infrastructure, work processes and practices); involvement of end-users in innovation design and development; and enabling users' easy access to sustained, high-quality, appropriate training and support to enable staff to adapt to digital solutions.

摘要

背景

在疫情初期,新冠病毒在英国的老年人护理院中迅速传播。国家感染控制建议包括对住院老人进行远程评估。英格兰西北部的一个地区为护理院引入了一个数字化的新冠症状追踪器,以识别住院老人病情恶化的早期迹象,从而促进护理应对措施。我们研究了在疫情第一年,该追踪器在四个地理案例研究地区的护理院中的实施、采用和使用情况。

方法

这是一项快速的、混合方法的、多地区案例研究。追踪器的采用率通过采用该追踪器的护理院数量占当地护理院总数的比例来计算。追踪器的平均使用情况在地区层面进行总结并比较。对参与追踪器实施的专业人员进行了半结构化访谈,并用于探索不同地区的实施因素。使用实施研究综合框架(CFIR)进行模板分析来指导定性数据的解释。

结果

在四个案例研究地区,采用率各不相同,介于13.8%至77.8%之间。随着时间的推移,所有地区的追踪器使用率都以不同的速率下降,平均使用率介于18%至58%之间。不同地区的实施背景不同,并且随着时间的推移,实施过程与最初计划的利益相关者参与和护理院培训策略有所偏差。四个解释性主题反映了似乎影响追踪器采用和使用的最具影响力的因素:(1)实施过程,(2)实施准备情况,(3)目的清晰度/感知价值,以及(4)在更广泛的系统压力背景下的相对优先级。

结论

我们的研究结果与新冠疫情大流行之前的数字解决方案证据基础相呼应,表明了三个关键因素,即使在危机时期,也可为未来护理院环境中快速数字应对措施的开发和实施提供参考:一种渐进的实施方法,测试组织准备情况并关注实施氛围,特别是创新与当地环境(即系统、基础设施、工作流程和实践)的契合度;终端用户参与创新设计和开发;以及让用户能够轻松获得持续、高质量、适当的培训和支持,以使工作人员能够适应数字解决方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ceb2/9843982/fd6482c6b6ef/43058_2022_387_Fig1_HTML.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