Imperial College Business School, London, UK.
Faculty of Medicine, Imperial College London, London, UK.
Int J Risk Saf Med. 2022;33(S1):S103-S110. doi: 10.3233/JRS-227033.
Previous reports have shown that there are long waiting times to commence therapy in the community-based mental health programme, IAPT (Improving Access to Psychological Therapies).
This study aimed to explore both causes and potential solutions to alleviate the burden of these waits.
A Systematic Literature Review (SLR) and Semi-Structured Interviews (SSIs) were conducted to identify causes and effects of these waits. Consequently, meaningful recommendations were made and tested with the aim of improving IAPT's waiting times.
SLR and SSIs revealed high 'Did Not Attend' (DNA) rates and a lack of support between initial appointments as being both a cause and effect of long waits. The identified issues were tackled with the development of an app design. Expert interviews and a mass survey fuelled the iterative process leading to a final prototype. Notable features included: therapist profile page, smart appointment reminders and patient timeline. Positive feedback was received from university students and ICS Digital, with scope to trial the app within Manchester CCG.
In the long run, the app aims to indirectly shorten waiting times by addressing treatment expectations and serving as an IAPT companion along the patient journey, thus reducing anxiety and consequently DNAs.
先前的报告显示，在基于社区的心理健康计划 IAPT（改善心理治疗途径）中，开始治疗的等待时间很长。
本研究旨在探讨减轻这些等待负担的原因和潜在解决方案。
进行了系统文献综述（SLR）和半结构化访谈（SSIs），以确定这些等待的原因和影响。随后提出了有意义的建议，并进行了测试，以改善 IAPT 的等待时间。
SLR 和 SSIs 显示，高“未出席”（DNA）率和初始预约之间缺乏支持既是长等待的原因也是结果。通过开发应用程序设计来解决这些问题。专家访谈和大规模调查推动了迭代过程，最终形成了一个原型。显著特点包括：治疗师简介页面、智能预约提醒和患者时间表。收到了来自大学生和 ICS Digital 的积极反馈，有在曼彻斯特 CCG 试用该应用程序的机会。
从长远来看，该应用程序旨在通过满足治疗期望并作为患者治疗过程中的 IAPT 伴侣，间接缩短等待时间，从而减轻焦虑并减少 DNA。
