X-on Health
Overview: X-on Health’s Surgery Assist AI tool and AOS helped Tudor Lodge Health Centre optimise its telephony, resulting in 50 percent reduced call waiting times and a 65 percent reduction in missed calls. Applied nationally, surgeries could see a reduction of 9.1m calls received each month, alongside a 2.3m drop in missed calls.
Why? Tudor Lodge Health Centre, a GP surgery in London serving 11,000 patients, faced rising demand for appointments and overwhelming telephone traffic during peak hours, particularly the ‘8am rush.’ Demand was outstripping capacity, and the ‘8am rush’ led to a poor patient experience and put a strain on limited staffing resources.
What happened? X-on Health carried out a 12-month Access Optimisation Service (AOS) and applied its Surgery Assist (formerly EDATT) AI software, providing unparalleled insights, automation, and optimisation opportunities. X-on undertook a full telephony call flow audit and data-driven assessment which included call data, online consultation submissions, NHS App uptake, patient survey outcomes, and patient access routes. X-on also carried out a multilingual patient survey at the surgery, with feedback showing 53 percent had never used an online booking solution, and 68 percent found it difficult to book an appointment. Following the audit and survey, X-on implemented a number of changes in collaboration with Tudor Lodge: expanding self-referral pathways and the adoption of digital tools, including X-on’s Surgery Assist AI software. Introducing a streamlined closed-loop call flows (including an out-of-hours service), improving digital literacy of staff through specific training, implementing personalised call flow and messaging for patients, and promoting patient self-service via the NHS App and AccuRx. Improvements included a decrease of 21 percent in the number of inbound calls, a 65 percent reduction in the number of missed calls, and a 48 percent reduction in calls for appointments. The number of online prescriptions placed increased by 66 percent (from 222 to 368 per month), whilst the average call queue time reduced by 50 percent, (from 180 to 90 seconds).
Looking ahead. The approach has already been successfully replicated in several other primary care settings, and X-on has projected that by applying Surgery Assist and the AOS model across GP practices in England, the NHS could see a reduction of 9.1 million monthly calls received, alongside a 2.3 million drop in missed calls.
Dyad Artificial Intelligence Limited
Overview: BetterLetter streamlines GP practice workflows by using AI to automate document processing. Each document is coded with full clinical context for the patient, improving data accuracy and safety while reducing administrative burden.
Why? GP practices receive hundreds of letters each day containing critical information such as new diagnoses, medication changes, referrals, and follow-up tasks. Yet, in many practices, this process remains manual and time-consuming. Coding a single complex document can take up to 10 minutes for an experienced coder.
What happened? BetterLetter was created to address these challenges through a semi-automated approach to clinical documentation. The system harnesses AI to interpret incoming letters, extract clinical information (such as diagnoses, medications, and investigations), and match these details to the appropriate SNOMED codes. A coder then reviews the AI-generated suggestions, approving or refining them with a single click. By analysing each letter in the context of the patient’s existing record, BetterLetter also flags potential safeguarding concerns, detects contradictions in medications, and highlights urgent updates for immediate action. Over 100 GP practices and Primary Care Networks across England now rely on BetterLetter, collectively processing more than half a million documents to date. The impact has been substantial across time savings, with complex letters completed in 3-4 minutes; data quality, with BetterLetter’s contextual awareness preventing duplicate coding and ensuring new information is accurately linked to existing problems; improved workflow, as once coded, documents are automatically routed to the relevant staff member for follow-up tasks; and enhanced patient safety, as urgent clinical details, medication conflicts, and safeguarding risks are surfaced quickly. Additionally, BetterLetter supports coder training and onboarding with in-app guides, instant chat support, and real-time feedback.
Looking ahead. BetterLetter’s roadmap includes deeper integration with secondary care systems and community-based services. By bridging data gaps across the healthcare ecosystem, the platform could further reduce duplicate tasks and ensure that critical patient information flows seamlessly between clinicians.
Lilli
Overview: Lilli’s home monitoring technology provides care teams with AI-driven insights generating efficiencies across health & care. By using Lilli, carers can: generate additional carer hours through right-sizing support; spot health decline early to enable early intervention; accelerate waiting lists for care assessments & discharge times from hospital.
Why? To help people live safely and independently at home for longer, generating significant efficiencies across both the health and social care systems.
What happened? Through small, unobtrusive sensors in a person’s home, Lilli tracks everyday activities like moving around, eating, sleeping, and using the bathroom. Our AI learns each person’s normal routine and spots unusual changes, alerting carers so they can step in quickly when needed. Additionally, our system continuously monitors patterns of behaviour to determine someone’s level of independence and provide a detailed, AI-driven care assessment. This helps carers not only intervene early to avoid emergencies but understand care needs at the front-door and adjust care packages over time based on each person’s evolving needs. This is leading to better outcomes and significant resource efficiencies and cost savings. By having Lilli in place, carers are able to clearly evidence based on data where care is most needed so their stretched resources can be allocated effectively and waiting times for assessments can be accelerated. North Tyneside Council deployed Lilli across various pathways, including frailty, hospital discharge and reablement, to understand people’s care needs.
Looking ahead. Economic analysis suggests that by 2035, our AI’s benefits could be equivalent to employing 9,700 full-time carers in the UK and could save 2.3 million bed days for the NHS over the next 10 years.
Eolas Medical
Overview: Eolas Medical is an AI knowledge management platform, used at the point of care to streamline access to the information clinicians need to make clinical decisions. It has over 200,000 healthcare professionals registered on the platform in the UK, Ireland and the US. Within the UK, we’re used by over 80 percent of NHS trusts.
Why? Clinicians face a constant challenge in accessing the most current and relevant medical knowledge needed for informed decision-making, the entry noted.
What happened? Eolas Medical was designed and developed by physicians to streamline access to the information you need in seconds, on mobile or desktop. This includes a content management system, allowing streamlining of local content such as guidelines, pathways, education and much more. We reduce the time searching for information for HCPs, using our AI based search, allowing greater efficiency and improve compliance to clinical guideline utilisation, ensuring consistent and safe care. By providing instant access to critical information, Eolas Medical empowers healthcare professionals to make faster, more informed decisions. Eolas Medical significantly reduces the time clinicians spend searching for information (80 percent reduction in time spent searching). The physician-designed platform’s intuitive interface, coupled with its robust content management system, allows for the seamless integration of both global medical knowledge and local guidelines. This unique combination empowers healthcare organisations to deliver consistent, evidence-based care tailored to their specific needs.
Looking ahead. Eolas Medical hopes to continue the platform’s success in scaling across three markets (UK, Ireland, and US), working to address the universal challenge of knowledge management in healthcare.
