Patient-centered care from AI-centered efficiencies
University Hospitals Coventry and Warwickshire NHS Trust + IBM
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Targeted innovation

The National Health Service (NHS) in the UK is facing unprecedented demand. Despite its best efforts, NHS waiting lists for elective care are growing, leading providers to look for innovative ways to continue to serve UK citizens with the world-class healthcare they expect.

University Hospitals Coventry and Warwickshire (UHCW) NHS Trust has a particularly pioneering mindset and innovative approach to patient-centric care, having already built a tool that targets health inequalities in the communities it serves—the HEARTT tool. As part of its UHCW Improvement System (UHCWi) methodology, the trust was keen to pilot AI and other analytics to identify areas that could benefit from the use of technology to improve productivity and deliver improved health outcomes to patients.

>700 more patients seen weekly without added staff 6% drop in missed appointments for some patients
The IBM team has fully supported our patient-first approach that combines process research and process mining to establish areas of opportunity to improve the patient experience and outcomes. This has helped us to identify where we could pilot process changes and exciting new technologies to have an impact far more quickly than we would have before. Professor Andy Hardy Chief Executive Officer University Hospitals Coventry and Warwickshire NHS Trust
Unlocking new efficiencies with AI

UHCW NHS Trust, IBM Consulting® and Celonis SE formed a close-knit, blended team to analyze the trust’s outpatient services through the lens of patient experience and health outcomes. The approach combined the IBM Garage model, Celonis’ AI-powered process mining, UHCW NHS Trust’s leading data analytics practices and its ongoing operation improvement activities.

The blended team analyzed over half a million pseudonymized patient journeys through the trust’s operational data, as well as in-person research and interviews with staff at the center of the process. Pseudonymized demographic data was layered over this analysis, ensuring that findings and interventions did not exacerbate health inequalities. This unique approach led to improvement opportunities and interventions in a period of weeks as opposed to months.

One such improvement focused on UHCW NHS Trust’s approach to missed patient appointments—known as did not attends (DNAs)—which are more common among those with high deprivation scores. Having identified a spike in last-minute cancellations after two SMS reminders had been sent, an IBM Garage team was used to explore how to improve the likelihood of re-booking those appointment slots. They subsequently found that by adapting the timing of these text reminders—sending an earlier notice to patients 14 days in advance of their appointments and a follow-up four days before—the trust could increase timely cancellations in the cohort eligible for two text messages, allowing the potential for those appointment slots to be re-used.

As part of the project, IBM and UHCW NHS Trust also piloted IBM® watsonx.ai technology to train, tune and deploy machine learning models to support hospital staff in scheduling and validating patients on the elective backlog. And the solution uses generative AI (gen AI) capabilities to read clinical letters and aid in verifying patients’ waiting list statuses.

Having applied this approach to our outpatient and theatres processes, UHCW NHS Trust is now leading in the adoption of process mining on behalf of NHS England. We are excited to see the results of harnessing IBM’s watsonx generative AI platform to the identified areas of these processes, which we hope will accelerate improvements even further. Professor Andy Hardy Chief Executive Officer University Hospitals Coventry and Warwickshire NHS Trust
Incremental changes, fast results

As process improvements were deployed, UHCW NHS Trust began to realize near immediate results. For example, the adjustment to its SMS reminders reduced DNA rates from 10% to 4% among patients in the subset of outpatients who received two SMS reminders.

With patients now cancelling or rescheduling their appointments earlier, the trust now has the option to re-purpose these slots to boost clinic activity by up to 6%. This efficiency, in turn, helped support UHCW NHS Trust to see around 700 extra patients each week as part of its overall elective recovery interventions. Current projections conducted by the trust estimate that this extra activity could contribute to a 10%–15% reduction in the overall backlog.

Further, the IBM watsonx.ai pilot has demonstrated greater accuracy and speed than human reviewers. The solution was able to review outpatient clinic letters in just 18 hours, compared to the four years required for a human equivalent. And this pilot offers scope for UHCW NHS Trust to further improve patient classification, shortening its waiting lists as those who no longer required treatment can be removed.

NHS UHCW - NHS Trust logo
About University Hospitals Coventry and Warwickshire (UHCW) NHS Trust

Part of the National Health Service (NHS), UHCW NHS Trust (link resides outside of ibm.com) serves as one of the largest acute teaching hospitals in the country. The organization provides a broad range of specialized and emergency medical services to the local community and spans two campuses—the University Hospital in Coventry, UK and the Hospital of St. Cross in Rugby, UK.

About Celonis SE

An IBM strategic partner founded a little over a decade ago, Celonis (link resides outside of ibm.com) offers AI-driven software-as-a-service (SaaS) services, specializing in process mining solutions. The company is simultaneously headquartered in Munich, Germany and New York City with additional offices spread throughout the United States, Europe, India and Japan.

Take the next step

For more information on our work on Intelligent Automation across the NHS, please contact Kerman Jasavala.

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