Title: An Artificial Intelligence Algorithm for Diagnosing Attention Deficit Hyperactivity Disorder (ADHD) in Adults
Funder: Department of Health and Social Care

Abstract: Background Demand for ADHD assessments for adults has been growing due to increased awareness and children who have been diagnosed in growing numbers entering adulthood and requiring adult diagnosis. NHS Services are unable to address this demand due to financial pressures and lack of appropriately trained clinical experts, leading to unacceptable waiting times. The partnering institutions have jointly developed an AI solution for assisting ADHD diagnosis in adults. It inputs the same data recommended by NICE as sufficient to make a clinical diagnosis, and delivers a positive diagnosis, negative diagnosis or referral for further assessment by a clinical expert. Aims and Objectives The aim is to test the AI solution in a clinical setting to establish its overall feasibility as a clinical decision support tool. The objectives are to assess its accuracy; develop clinical pathways for deploying it; establish cost benefits and commercial feasibility; and engage with relevant NHS stakeholders. Project plan and methods used Work is organised around: Clinical feasibility, focusing on the AI's accuracy and its best use within clinical settings; Technical feasibility, refining the technology based on experience gained and new data; Commercial feasibility, establishing the cost benefits for the Trust and reaching out to NHS stakeholders. Timelines for delivery This is a 1-year project, with an interim assessment of feasibility scheduled for month 6 and a dissemination and stakeholder engagement workshop planned for month 12. Anticipated Impact and Dissemination Benefits to the NHS will be reduced waiting lists, improved outcomes in people with ADHD through quicker diagnosis and treatment, and reduced costs. Patients will benefit from quicker diagnosis and treatment, avoiding problems &ndash; in health, social life and employment &ndash; associated with untreated ADHD. Dissemination will be through direct engagement with NHS stakeholders, using the partnering Trust's networks, and a dedicated workshop with relevant NHS stakeholders.

Lay abstract: Demand for diagnostic assessments of adults with ADHD has been growing for the last 15 years. This is because there is more awareness amongst the population and health professionals about this condition. Because of this high demand, but also difficulties with recruitment and retention of health professionals in the NHS, the time people need to wait to receive an ADHD assessment is very long. We know that this delay to receive a diagnosis and treatment for ADHD is harmful to people. For example, untreated ADHD is linked to more mental health problems, relationship problems, employment problems and substance misuse. The new AI solution that we have developed and is the basis for this project will shorten the time people will need to wait because a broader range of health professionals will be able to complete the diagnostic assessments quicker. This is because, using clinical data as input, the AI will be able to guide health professionals about who requires extra assessment by whom, and who doesn't What we would like to do is check that the AI solution works well in an NHS Service and at the same time improve it. Also, we want to determine the financial benefits for the NHS. We will be comparing the AI solution's outcomes with actual diagnosis outcomes by clinical experts. We will also receive input by health professionals regarding its possible deployment in clinical settings. And as part of this evaluation, service users will play a role in providing feedback and advice helping to solve any problems that may come up. Once we have completed this evaluation, we will show and share our findings with the relevant NHS bodies that can help us spread its use further. We will start this process through a local workshop. The scientists developing this work are known leaders in their respective fields of artificial intelligence and ADHD. They have a good track record of working together and want to be able to also complete this work for the benefit of people with ADHD and the NHS.

Research activity codes: 7.3 MANAGEMENT AND DECISION MAKING;4.2 EVALUATION OF MARKERS AND TECHNOLOGIES
Health categories: MENTAL HEALTH