Title: Evaluation of the DEONTICS AI platform for personalised, evidence-based treatment planning in multidisciplinary cancer care: Increasing compliance with national standards of care and streamlining MDTs in prostate cancer
Funder: Department of Health and Social Care

Abstract: Background: Around 375,000 cancers are diagnosed in the UK annually and this figure is expected to reach 500,000 by 2035. Treating cancer quickly and correctly saves lives. As the number of different cancer treatment options and our scientific understanding continue to grow rapidly, it can be difficult for clinicians to keep up-to-date with best practice, causing unjustified variations in the quality of care and clinical outcomes for patients. This project: Recently, Deontics a CE marked &ldquo;Clinical decision support system&rdquo; which uses artificial intelligence (AI) to integrate individual patient data and preferences with evidence-based clinical guidelines, to dynamically and transparently generate best-practice, individualised, treatment recommendations can help determine treatment. For this project, a highly experienced, multi-disciplinary team has come together to capture the clinical effectiveness and potential cost-savings that Deontics may have in the clinic. With almost 1.4 million patient discussions taking place in MDTMs in England, and the number increasing annually by 20%, stretching the service to breaking point and making dangerously error prone. Deontics may assist clinicians and MDTMs in treatment decisions for patients with prostate cancer. Deliverables: Real world data supporting the integration and utilisation of Deontics in the prostate cancer pathway in the NHS.

Lay abstract: Around 375,000 cancers are diagnosed in the UK annually and this figure is expected to reach 500,000 by 2035. Treating cancer quickly and correctly saves lives. As the number of different cancer treatment options and our scientific understanding continue to grow rapidly, it can be difficult for clinicians to keep up-to-date with best practice, causing unjustified variations in the quality of care and in survival outcomes for patients. Multidisciplinary Team Meetings (MDTMs), were introduced in the NHS in 1995 to reduce these variations in cancer care. Cancer MDTMs consist of a room full of medical experts including Surgeons, cancer, imaging and diagnosis specialists, and Nurses. They discuss each patient and make treatment decisions. However, the number of patients discussed in MDT meetings has grown exponentially. In 2014 alone, around 1.4 million patient discussions took place in MDTMs in England, and the number is increasing annually by 20%, stretching the service to breaking point and making dangerously error prone. Currently patients are left out of the MDTMs, with little representation of their views. We believe there is an opportunity to augment cancer MDTMs with the power of AI to substantially increase their efficiency and effectiveness. Deontics is a CE marked &ldquo;Clinical decision support system&rdquo; which uses artificial intelligence (AI) to integrate individual patient data and preferences with evidence-based clinical guidelines e.g. NICE, to dynamically and transparently generate best-practice, individualised, treatment recommendations. The aim of this work is to: Demonstrate integration of Deontics MDTM decision support services within the prostate cancer pathway, with trust information systems and national cancer databases; Evaluate Deontics ability to triage localised and locally advanced prostate cancer cases aged under 75 straight to the treating clinician; Evaluate Deontics impact on compliance with best-practice and national guidelines and standards of care; Evaluate Deontics' impact on the cost effectiveness of the prostate cancer pathway. Evaluate Deontics' ability to support shared decision-making and the acceptability of the technology to patients Our work plan will include both retrospective and prospective clinical evaluations. We will apply modern data science methods to identify the patients most suitable for triage straight to treatment. This will shorten wait times for patients proceeding to treatment and reduce the number of cases who need to be discussed in full MDTMs. The system will be tested clinically by integrating Deontics with the hospital record and Somerset Cancer Register to support clinical decision-making for more complex patients. We will engage patients and wider public in this new way of working throughout the study. Findings will be disseminated through patient forums, newsletters and cancer support groups. The prostate cancer MDTM is a representative complex cancer pathway. If successful, a phase 4 proposal will be prepared involving multiple hospitals and other cancers.

Research activity codes: 7.3 MANAGEMENT AND DECISION MAKING
Health categories: CANCER AND NEOPLASMS