The use of digital solutions in alleviating the burden of IAPT’s waiting times

Abstract

BACKGROUND: 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). OBJECTIVE: This study aimed to explore both causes and potential solutions to alleviate the burden of these waits. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Using Conversational AI to Facilitate Mental Health Assessments and Improve Clinical Efficiency Within Psychotherapy Services: Real-World Observational Study

“…Notably, against the backdrop of rising referrals, the needs of patients are unlikely to be addressed through an increase in the clinical workforce; in fact, there exists a national shortage of qualified staff [ 13 ]. To remedy this precarious situation, it has been repeatedly suggested that digital tools might represent a viable opportunity to improve the efficiency and quality of service delivery, as well as to enhance patient outcomes and experience [ 14 - 17 ].…”

Closing the accessibility gap to mental health treatment with a personalized self-referral chatbot

“…Digital technologies and Artificial Intelligence (AI) have been proposed as potential solutions to these challenges [Rudd and Beidas, 2020, Taylor et al, 2020, Kola et al, 2021. While such technology has been shown to reduce the workload of the mental health staff and make services more efficient [Jayaraajan et al, 2022, Koutsouleris et al, 2022, Rollwage et al, 2022, less is known about the marginal impact of AI technologies in supporting individuals of differing demographics seeking help. Excitingly, digital solutions might be especially well-positioned to help individuals who are seeking support to overcome barriers, for example by offering more flexibility and reducing stigma [Rodríguez-Rivas et al, 2022].…”

Conversational AI facilitates mental health assessments and is associated with improved recovery rates

“…Unfortunately, supply-demand imbalance improvements in mental healthcare are not to be expected in the near future 10. Therefore, to mitigate this imbalance, digital and artificial intelligence (AI) solutions have been put forward, as means to reduce the burden on staff and to facilitate assessment and treatment,11–14 particularly solutions that need little-to-no input from mental health professionals 15 16. Indeed, well-designed AI has the potential to augment and support human practitioners.…”

“…To mitigate the supply-demand imbalance in mental healthcare, digital and AI solutions have been put forward as means to reduce the burden on staff and to facilitate assessment and treatment [Jayaraajan et al, 2022, Rudd and Beidas, 2020. Of those, AI solutions that need little-to-no input from mental health professionals are particularly suited to address the workforce crisis (in contrast to online therapy, for example, which remains labour intensive) [D'Alfonso, 2020[D'Alfonso, , Ćosić et al, 2020.…”