HISES Innovation PhD Fellowship – Lung Cancer
Theme Title: Digital Transformation and Artificial Intelligence in the Lung Cancer Diagnostic Pathway
Summary: In Scotland, lung cancer is the second most diagnosed cancer in both men and women, and the most common cause of death from all cancers. Only 11.1% of men and 16.3% of women survive 5 years following diagnosis. South East Scotland Cancer Network data in 2020 showed that by the point of case discussion at the Multidisciplinary team (MDT) 50% had incurable metastatic disease. Of all patients discussed at MDT less than half went on to receive cancer treatment and those that did often had options limited by the advanced stage of their disease and/or general health state. In order to identify fitter patients, that would most benefit from treatment, the pathway must be as efficient as possible to ensure that these patients receive prompt treatment. However, the current lung cancer diagnostic pathway requires multiple sequential, multimodality imaging and procedural tests prior to a treatment decision. There are potential delays at each step of the patient pathway from reporting and dissemination of the findings – patients can wait up to 3 weeks for a report of an abnormal chest x-ray when referred from primary care, with further delays waiting for cross sectional imaging and respiratory specialist review. Patients that go onto have a CT guided biopsy or bronchoscopy require a multitude of face-to-face consultations to convey information and organise the next steps. This results in the pathway taking several weeks to complete. We believe that nascent artificial intelligence (AI) and digital health technologies (DHTs) can be leveraged and deployed to address these issues and streamline the pathway, thereby significantly reducing the time taken to definitive treatment and ultimately improving patient outcomes and experiences.
Host Test Bed: Heath Innovation South East Scotland; Edinburgh Cancer Centre
Academic Lead Proposed HEI: University of Edinburgh
Test Bed Lead contact: Prof Tim Walsh: email@example.com
Innovation Lead contacts:
Dr Stephen Harrow, Consultant Clinical Oncologist, NRS Career Fellow, Clinical Lead Cancer Transformation & Innovation
Dr Rishi Ramaesh, Consultant Radiologist & NHS Scotland Innovation Fellow
Demand signalling priority area: Innovation in Cancer Pathways; Early Cancer Diagnostics; Integrated Planned Care
Problem Statement: Lung cancer remains the second most common cancer in the Scottish population and the deadliest. By the time patients are diagnosed their cancer is often too advanced and the patients’ health has deteriorated such that curative intent treatment is not possible. A strategy to increase the number of patients suitable for curative treatment is to improve early diagnosis and streamline treatment planning and initiation. Within the current diagnostic pathway there are processes that could be improved with AI and DHTs to realise this objective.
Proposed Area of Work: The PhD project will take a multifaceted approach to evaluation of DHTs and how they can address current barriers and challenges in the lung cancer pathway. Research will closely align with established industry partners, academic collaborators and healthcare professionals. Themes include:
· Evaluation of novel AI solutions for triages of abnormal chest x-rays, and deployment into the lung cancer pathway. Research into the efficacy, model safety and accuracy of the solution, via retrospective and prospective methodologies.
· A novel patient information and e-consent digital solutions to improve the patient experience and reduce the need for multiple face to face appointments with healthcare professionals. Investigating the feasibility, utility and acceptability of DHTs amongst patients, including in automated patient recall for appointments and assessing the value of digital media content in conveying patient information and the consent process compared to current resource and time intensive pathway
Training will potentially include: data science within healthcare; artificial intelligence tools for improving patient flow; care pathway design; patient and public engagement; working with industry; evaluation of digital healthcare, including the health economic and operational impact of these digital healthcare tools within NHS diagnostic pathways.
Opportunity: This PhD would be suitable for a Radiologist, Respiratory Physician or Oncologist interested in devising and implementing innovation strategies within cancer care to improve outcomes for patients. The work done as part of this project would contribute to the wider digital transformation of cancer pathways and play a key role in improving the patient experience and ultimately outcomes.