Accelerating the safe adoption of AI in health and care NHS AI Lab - An update Dom Cushnan, Head of AI Imaging August 2020
The AI Lab will be a focal point for accelerating the safe adoption of AI to the front line of health and care PROOF OF CONCEPT
The Lab Programmes The AI in Health and The AI Skunkworks The AI Regulation Ecosystem Care Award Tackling challenging issues that can help Enable a world leading safe and ethically Accelerate the testing and evaluation of speed up the adoption and use of AI in robust ecosystem for the development and the most promising AI technologies which health and care settings. deployment of AI technologies. meet the strategic aims of the NHS Long Term Plan. AI in Imaging The Accelerating Detection of Multiple long-term conditions Diseases Programme (multimorbidity) Supporting the development of imaging technology; from mechanisms Enabling the use of polygenetic tests and available data, to help screening used to safely collect and share data to Using AI to identify disease “clusters”, programmes identify patients most at risk validating AI imaging software. enabling research into the underlying of disease. causal pathways.
Buyer’s Guide to AI in Health and Care
COVID-19 presented an unprecedented opportunity for the uptake of innovative digital solutions at pace and scale. As a result, health and care organisations have been receiving What is the multiple proposals for AI applications that may improve the quality and ease the burden of their work. problem we are responding to? But they need to be assured that any AI technology they do buy meets the highest standards of safety and efficacy. How can we equip organisations to make well-informed AI buying decisions that result in safe and effective solutions?
T he Buyer’s Guide sets out the background knowledge and important questions that buyers need to consider to undertake robust AI procurement exercises. Tailored to health and care, it addresses four areas: 1. Problem identification 2. Product assessment 3. Implementation considerations 4. Procurement and delivery The Guide builds on an initial buyer’ checklist shared by NHSX in April, and will be published on the NHSX website shortly
What is NCCID and How it Works
What is the NCCID? The National COVID-19 Chest Imaging Database (NCCID) is a centralised UK database containing X-Ray, CT and MRI images from hospital patients across the country. This is to support a better understanding of the COVID-19 virus and develop technology which will enable the best care for patients. It is a joint initiative established by NHSX, the British Society of Thoracic Imaging (BSTI), Royal Surrey NHS Foundation Trust. Website link here.
Why was the NCCID set up? Before COVID-19 During COVID-19 Other datasets NCCID Technology advances These AI tools can During COVID-19, The AI tools may have NCCID will collect led to computer tools determine type / these AI tools are been developed and data from a wide that can examine extent / severity on being widely applied trained to recognise variety of COVID-19 medical images (e.g. medical images, and to evaluate images of disease in a different patients across the chest radiographs and identify additional COVID-19 patients to population to that seen UK. AI tools can computed tomography features to the help clinicians with the in the UK, for example therefore be trained (CT) scans) human eye - patient care pathway with different ethnic / and robustly validated potential for new gender balances on this data and insights applied for use on the UK population 9
AI Regulation programmes
Multi-agency advice service: a joint service between HRA, MHRA, NICE and CQC that offers support, information and guidance on regulation and evaluation of AI and digital health technologies Streamlined technology review : speed up the process of reviewing application for CAG and medical devices between HRA/MHRA Technology Vigilance (yellow card): enhanced Yellow Card Overview of system, spanning all incident types (including technology) and programmes provide research into novel AI signal detection techniques across medicines and devices Synthetic data: continue MHRA’s existing work (funded by the Regulators’ Pioneer Fund) to develop synthetic datasets that can be used to validate algorithms, including AI algorithms, in medical devices
AI Award in health and care Update
AI in Health and Care Award - Round 1 update The Award will accelerate the testing and evaluation of the most promising AI technologies which meet the strategic aims set out in the NHS Long Term Plan. It is run in collaboration with the Accelerated Access Collaborative (AAC) and NIHR in four phases across the spectrum of development: from initial feasibility to evaluation within the NHS and care. The first round was launched in January 2020 and focused on four key areas: screening, diagnosis, decision support and improving system efficiency. 531 applications were received 47 applications were received for Phase 4 which will facilitate initial system adoption and evaluation of AI technologies with market authorisation into the NHS. We expect to be able to announce the first technologies to be funded in the coming months and to announce a second call for applications in the Autumn.
Any questions? 14
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