[EBO] more than rose to the challenge. It felt like a true development partnership with staff from both EBO and BCU forming a cohesive team
Referral to Treatment
Say goodbye to Referral To Treatment (RTT) errors and inefficiencies and start optimising patient pathways today with Ali, EBO's RTT Virtual Assistant.
- Ensure accurate application of NHS referral-to-treatment rules
- Provide instant, AI-driven guidance for RTT decisions
- Minimise delays and ensure timely treatment
- Improve accessibility and staff experience
- Align with national access policies effortlessly
By March 2026, the Reforming Elective Care for Patients national policy, aims to ensure that 65% of patients wait less that 18 weeks for elective treatement. Achieving this ambitious goal requires the consistent application of national referral to treatment time rules.
However, admin teams often face challenges in applying these guidelines accurately, particularly when it comes to more complex cases. In fact, it is estimated that these rules are misaplied 10% of the time. So, how can we address these challenges? How can we equip staff to apply the right rules, at the right time?
Discover EBO’s RTT Virtual Assistant, named Ali. Powered by advanced AI, Ali makes RTT simple by ensuring staff can accurately apply National Referral to Treatment (RTT) rules and policies every single time. See it in action in the video below.
The Problem
65% target: patients waiting under 18 weeks
8-10% of cases involve misapplied RTT rules
Achieving the goals of the 2025 Elective Reform Plan—ensuring 65% of patients wait less than 18 weeks for elective treatment—requires the precise application of Referral to Treatment (RTT) rules. However, administrative teams often face challenges in interpreting and applying these national guidelines, leading to errors such as:
Incorrect Clock Starts
Referral clock starts at the wrong time.
Missed Clock Stops
Treatment starts or discharge dates are not recorded.
Patient-Initiated Delays Misunderstood
Failing to account for patient-driven changes.
The Impact
Without a consistent and accurate approach to RTT management:
Patients experience delays in treatment, affecting health outcomes.
Administrative teams struggle with complex and evolving rules, leading to inefficiencies.
Hospitals risk failing to meet national access targets, impacting funding and service quality.
The Solution
Meet EBO’s RTT Virtual Assistant, Ali - the AI technology that makes RTT rule application simple. Designed to eliminate errors, enhance efficiency, and ensure compliance with NHS Referral to Treatment (RTT) policies, Ali provides real-time AI-diven guidance to administrators and clinicians, enabling staff to make the right decisions instantly.
Tailored Guidance
Ali delivers case-specific recommendations, analysing each patient’s referral scenario to provide the right RTT rule application instantly—reducing misinterpretation and manual effort.
Behavioural Science for Smarter RTT Management
Ali leverages AI and behavioural science to help staff navigate RTT complexities with greater accuracy. Using closed-loop analysis, Ali continuously refines its responses, improving efficiency and reducing errors over time.
AI-Powered RTT Rule Application
Ali simplifies RTT management by automating rule application and ensuring accuracy at every step. It eliminates common errors like incorrect clock starts, missed stops, and misinterpreted delays, providing real-time, policy-driven guidance to keep patient pathways on track.
Multilingual & Sentiment-Aware Assistance
Ali enhances accessibility with real-time multilingual support, allowing staff to interact in their preferred language. It also recognises stress levels in conversations, providing empathetic, adaptive responses to reduce admin burden and improve user experience.
Two-Way Natural Conversation
Staff can ask Ali case-specific questions in natural language and receive immediate, policy-driven guidance, reducing confusion and delays.
AI-Generated Insights
Ali detects common RTT errors and provides real-time analytics, helping hospitals optimize workflows and enhance compliance. Its AI-driven adaptability ensures precise, context-aware guidance that continuously improves through real-world interactions.
How it Works
Here’s a step-by-step flow of how the EBO's RTT Virtual Assistant works:
Staff describes the patient case and queries related to the RTT rules. Such as, "When should I start the clock?"
Ali analyses the case and guides staff accordingly via two-way natural conversation.
Ali provides a real-time response and directs staff to relevant NHS RTT guidelines for further clarity.
Ensures the consistent and correct application of RTT rules, reducing misapplications which currently occur in 8-10% of cases.
Helps hospitals meet the 2025 Elective Reform Plan goal of 65% of patients waiting less than 18 weeks for elective treatment by March 2026.
Automates the application of complex RTT rules, saving time and reducing manual errors.
Guarantees adherence to national RTT guidelines, ensuring accurate tracking of patient pathways and reducing delays.
Ensures timely treatments, improving patient outcomes and contributing to the overall efficiency of healthcare systems.
The Result
EBO’s RTT Virtual Assistant streamlines administrative processes, ensuring faster, more accurate RTT rule application, while supporting staff with real-time AI-driven guidance. By recognising emotional cues, it enhances user experience, making complex tasks less stressful and more efficient.
Book a demo today to experience faster, error-free RTT processing with AI-driven precision.
Sounds compelling?
Contact us today and we'll take you through our AI-powered Referral to Treatment solution.
Winning Clients’ Trust
Here are a few words from our clients on their experience with our solution.
Danielle Edwards
- Head of Digital Transformation
- Betsi Cadwaladr University Health Board
If a solution like EBO is implemented across the NHS, it can revolutionise access to maternity care for the majority of service users. The point is to release capacity in Health systems by using innovation and technology that supports that.
Charlotte Clayton
- Clinical Academic Doctoral Midwife
- RM Princess Anne Hospital, University Hospital Southampton
The experience of working with EBO on our Virtual Assistant has been very positive. EBO and Servelec listened to our feedback and helped design AI solutions that benefit our patients by providing an alternative way they interact with the trust.
James Mariott
- Digital Change Manager
- Somerset NHS Foundation Trust
I think where we really found the stress is on the admin. A lot of our service users are calling us, which means that our lines are continuously busy and admins miss some of the calls, as they are on the phone with another service user at the time. It means that people are trying to get in contact till the late evening when the services are closed. It really opened up our eyes to see that there are other ways our clients can communicate with us and there are other ways that we can communicate with the clients. It actually works for them.
Shona Richards
- Digital Transformation Project Manager
- East London NHS Foundation Trust
EBO is a trusted partner of Microsoft, because a lot of what we see with thousands of customers that we work around the world is very much aligned with EBO’s mission and vision. They empower caregivers; they empower administrative staff, and they empower patients to have better access to information. 84% of Healthcare Executives believe that AI will revolutionise the way we obtain information.
Ruthy Kaidar
- Director, Healthcare Industry Sector
- Microsoft
We have a growing backlog and we have patients whose conditions are just getting worse as their appointments are delayed. We have people in the community who cannot even get their first appointment, they cannot get diagnosed and they cannot receive early treatment. Covid has accelerated our adoption of virtual appointments and remote patient monitoring, so there is some efficiency gained there.
Jenny Chong
- Associate Non-executive Director
- Medway NHS Foundation Trust
It is indeed a pleasure to work hand-in-hand with EBO in developing our AI profile and competence. Apart from providing excellent technical expertise, EBO has consistently supported, trained, and maintained a close relationship with all of our team whilst overseeing the development, deployment, and successful marketing of our AI platform. Such support is unique and provides us with the confidence and motivation to further develop this exciting Artificial Intelligence revolution together with EBO, and be able to provide a holistic and efficient experience to our clients.
Jean Claude Muscat
- CEO
- Saint James Hospital
Our booking officers absolutely love our Virtual Assistant Alex, since it does the legwork and they can focus on the patient. Over the last six months, Alex has helped save 24 hours of staff time every week. Our callers come from diverse cultural and linguistic backgrounds, so we worked with our communication to make sure Alex understands all our patients and the different ways they communicate.
Kim Hale
- Digital Change Lead
- Somerset NHS Foundation Trust
“Working with EBO is like ‘a breath of fresh air’. They have a deep-seated ‘can-do’ ethos to delivering successful solutions and our collaboration functions as a true partnership. The EBO Virtual Assistant is a new technology for us with great potential as it integrates directly with our Electronic Patient Record. We initiated a pilot with EBO on e-Consent and are already lined up for rolling out pre-assessment and appointment modules.¨
Andy l’Anson
- IT Programme Manager
- Shropshire Community Health NHS Trust
