Faculty of Health and Wellbeing, University of Central Lancashire, Preston, Lancashire, United Kingdom.
East Lancashire Hospitals NHS Trust, Blackburn, United Kingdom.
Phys Ther. 2021 May 4;101(5). doi: 10.1093/ptj/pzab040.
Predicting motor recovery after stroke is a key factor when planning and providing rehabilitation for individual patients. The Predict REcovery Potential (PREP2) prediction tool was developed to help clinicians predict upper limb functional outcome. In parallel to further model validation, the purpose of this study was to explore how PREP2 was implemented in clinical practice within the Auckland District Health Board (ADHB) in New Zealand.
In this case study design using semi-structured interviews, 19 interviews were conducted with clinicians involved in stroke care at ADHB. To explore factors influencing implementation, interview content was coded and analyzed using the consolidated framework for implementation research. Strategies identified by the Expert Recommendations for Implementing Change Project were used to describe how implementation was undertaken.
Implementation of PREP2 was initiated and driven by therapists. Key factors driving implementation were as follows: the support given to staff from the implementation team; the knowledge, beliefs, and self-efficacy of staff; and the perceived benefits of having PREP2 prediction information. Twenty-six Expert Recommendations for Implementing Change strategies were identified relating to 3 areas: implementation team, clinical/academic partnerships, and training.
The PREP2 prediction tool was successfully implemented in clinical practice at ADHB. Barriers and facilitators to implementation success were identified, and implementation strategies were described. Lessons learned can aid future development and implementation of prediction models in clinical practice.
Translating evidence-based interventions into clinical practice can be challenging and slow; however, shortly after its local validation, PREP2 was successfully implemented into clinical practice at the same site in New Zealand. In parallel to further model validation, organizations and practices can glean useful lessons to aid future implementation.
预测中风后运动功能的恢复情况是为个体患者规划和提供康复治疗的关键因素。Predict REcovery Potential（PREP2）预测工具旨在帮助临床医生预测上肢功能结局。除了进一步的模型验证外，本研究的目的还在于探讨 PREP2 在新西兰奥克兰地区卫生局（ADHB）的临床实践中是如何实施的。
采用半结构化访谈的病例研究设计，对 ADHB 参与中风治疗的临床医生进行了 19 次访谈。为了探讨影响实施的因素，对访谈内容进行了编码和分析，使用实施研究的综合框架。采用实施变革专家推荐项目确定的策略来描述实施的过程。
PREP2 的实施是由治疗师发起和推动的。推动实施的关键因素如下：实施团队给予员工的支持；员工的知识、信念和自我效能感；以及拥有 PREP2 预测信息的好处。确定了与 3 个领域相关的 26 项实施变革专家推荐策略：实施团队、临床/学术合作以及培训。
PREP2 预测工具在 ADHB 的临床实践中成功实施。确定了实施成功的障碍和促进因素，并描述了实施策略。所吸取的经验教训有助于未来在临床实践中开发和实施预测模型。
将循证干预措施转化为临床实践可能具有挑战性且进展缓慢；然而，在其进行了本地验证后不久，PREP2 就在新西兰的同一地点成功地应用于临床实践。除了进一步的模型验证外，组织和实践可以吸取有用的经验教训，以帮助未来的实施。
