Journal Article

P17 Specialist assessment using digital workflow automation prior to use of augmented intelligence – a proof of concept study

Briggs, Mark, Mace, Lesley, Prasad, Priyajit

2024

Overview

IntroductionNHS waiting lists are long due to limited specialists and long training times. Workflow automation and AI could be valuable tools to address these needs. As part of a scalable, digital transformation strategy to reduce waiting lists, optimising patient clinical history data augmented by intelligent machine learning prior to a consultation has significant benefits e.g. gathering more relevant data, reducing clinician documentation burden, improved risk stratification, the ability to develop well-governed digital-first clinical pathways and better utilisation of specialist capacity. Nonetheless, healthcare has slowly adopted automation due to poor user experience (UX), interoperability issues, and the challenges of personal health data. As the first phase of our study, we hypothesised that intelligent ‘Consultant-level’, pre-consultation specialist assessment (PCQ) using a digital platform could be acceptable as a scalable solution to improve specialist workflow that could then be improved in the future by AI.MethodsAs part of a proof-of-concept study prior to a real-world study involving 100 patients, we prospectively identified individuals to fill out a standardised, anonymised PCQ using a secure digital platform that mimicked a typical GI clinic new consultation. The aim was to gather data on the UX when providing high volume clinical data prior to a consultation. The consented adults were led through a series of 70–120 questions dynamically based on their responses. They documented their experiences, time taken, ease of process, expected benefits in a real-world specialist consultation, and the viability of this innovation to reduce waiting lists.ResultsThe average age group was 45 to 54 yrs. (range 18 to >55 yrs.), n=10. The overall experience was 4.5 (0 = very hard, 5 = excellent), overall ease of process was 2.3 (1 =easy, 5 = very hard), the ability to provide a sufficiently detailed history was 1.5 (1 = very easy, 5 = very hard) and this type of PCQ being helpful to a future consultation was 5 (1 = very unhelpful, 5 = very helpful). The average time to fill the PCQ was 12.5 mins (range 5 to > 20 mins). 100% agreed that this pre-consultation innovation would help clinicians be better prepared and be more efficient and 90% were very happy to fill out this type of PCQ if it helped reduce NHS waiting lists.ConclusionsOutpatient GI and hepatology services can benefit from rapidly emerging digital workflow automation technologies which are user friendly, provide detailed histories and could empower clinicians. Simply put, even a five-minute reduction per patient in specialist administrative burden during a 12-patient clinic generates an hour’s extra specialist capacity to help reduce clinic waiting lists or deliver endoscopy without increasing the actual hours of specialist time worked.

• Publisher: BMJ Publishing Group Ltd and British Society of Gastroenterology,BMJ Publishing Group LTD
• Subject: Automation / Computer platforms / Digital transformation / Endoscopy / Patients / Poster Presentations