AI-identified clinical coaching in urgent and emergency care

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Background

There is an extraordinary amount of pressure on urgent and emergency care services both in London and across England, and the situation is getting worse.

UCLPartners, North East London Integrated Care System, and Health Navigator are currently delivering the AI for Urgent and Emergency Care programme, which aims to support patients before they reach crisis points, helping them live healthier lives and easing pressure on A&E services.

The programme uses routinely collected local hospital data to create advanced AI screening technology to identify people who are likely to seek emergency or urgent healthcare services without appointments in the next six months. They are offered support via targeted, phone-based clinical coaching with trained healthcare professionals (clinical coaches). Clinical coaches support patients to self-manage their condition, and reduce their chances of unplanned hospital visits, admission, and extended hospital inpatient spells.

THIS Institute is carrying out an evaluation of the project, along with LCP Health Analytics, to gather evidence that will support its wider adoption and help shape future policies for effective proactive care.

Approach

We will be working with LCP Health Analytics to independently and objectively assess the impact, effectiveness and delivery of the AI for urgent and emergency care programme. We will do this by designing and delivering an effective real world evidence evaluation approach, which involves using data collected from real-life settings, rather than controlled clinical trials.

Jointly with UCLPartners, we will produce data for regular ongoing learning, and insights to improve the impact and effectiveness of the programme. The work will be carried out across four workstreams.

In Workstream 1, we will look at whether the AI-identified clinical coaching intervention reduces unplanned hospital admissions, use of healthcare resources and clinical outcomes, such as new acute or long-term health conditions. This will be done through a matched cohort study – a study comparing two groups of people, designed to mimic the setup of a clinical trial. It will use a target trial emulation approach (a framework for designing and analysing observational studies that estimate the causal effect of interventions) and electronic health record data.
In Workstream 2, we will look at how well the coaching intervention is used, accepted, and put into practice. We will look at routinely collected information from people who were identified for the clinical coaching. We will also interview patients, carers, and healthcare professionals about their experiences. We will compare different groups of people (for example, by age, gender, ethnicity and disability) to see which groups are more likely to take part, how helpful the coaching is, and whether it works better for some groups than others.
In Workstream 3, we will evaluate whether clinical coaching improves patients’ knowledge, skills and confidence to manage their own health, along with their quality of life. We will ask patients who have been offered the coaching (‘intervention’ group) and patients who were not offered the coaching (‘comparator’ group) to take part. Patients will be asked to complete four surveys over 12 months, where we will ask them about their health, self-management and quality of life. You can learn more about how we invite patients and use their data in Workstream 3 on our ‘Clinical coaching and your information’ page.
In Workstream 4, we will conduct a health economic evaluation, aligned with HM Treasury Green Book guidelines, to understand the cost-benefit and budget-impact at system and national level of AI-identified clinical coaching.

Project team