Autonomous Telephone Follow-up After Cataract Surgery

Overview

This project will apply AI technology to meet the gap between increasing demand and limited capacity of high- volume healthcare services. The project will develop evidence that will support the safe deployment of Ufonia's automated telemedicine platform to deliver calls to cataract surgery patients at two large NHS hospital trusts. The proposed study will implement DORA in addition to the current standard of care for a cohort of patients at Imperial College Healthcare Trust and Oxford University Hospitals NHS Foundation Trust. The study will evaluate the agreement of DORA's decision with an expert clinician. In addition it will test the acceptability of the solution for patients and clinicians; the sensitivity and specificity of the system in deciding if a patient requires additional review; and the health economic benefits of the solution to patients (reduced time and travel) and the local healthcare system. If successful, a proposal will be developed to roll the solution out to all patients at each site in anticipation of an application to a late phase award for wider NHS deployment.

Background Due to an ageing population and increased expectation, the demand for many services is exceeding the capacity of the clinical workforce. As a result, staff are facing a crisis of burnout from being pressured to deliver high- volume workloads, driving increasing costs for providers. Artificial intelligence, in the form of conversational agents, presents a possible opportunity to enable efficiencies in the delivery of care. Aims and Objectives This study aims to evaluate the effectiveness, usability and acceptability of DORA - an AI-enabled autonomous telemedicine call - for detection of post-operative cataract surgery patients who require further assessment. The study's objectives are: to establish efficacy of DORA's decision making in comparison to an expert human clinician; baseline sensitivity and specificity for detection of true complications; evaluation of patient acceptability; evidence for cost-effectiveness; and to capture data that may support further studies. Project plan and methods used Based on implementation science, the interdisciplinary study will be a mixed-methods phase one pilot establishing inter-observer reliability; as well as usability and acceptability. Timelines for delivery The study will last eighteen months: seven months of evaluation and intervention refinement, nine months of implementation and follow-up, and two months of post-evaluation analysis and write-up. Anticipated Impact and Dissemination The project's key contributions will be evidence on artificial intelligence voice conversational agent effectiveness, and associated usability and acceptability. Results will be disseminated in peer-reviewed journals and at international medical sciences and engineering conferences.