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Artificial Intelligence Evidence and Implementation - Pritesh Mistry.pptx
- 1. © The King's Fund 2022 Artificial Intelligence, Evidence, and Implementation Dr Pritesh Mistry
- 2. © The King's Fund 2022 Who am I?
- 3. © The King's Fund 2022 Who are The Kings Fund? Health and Care Think Tank 125 years Independent organisation • Research • Policy development • Convening • Leadership and organisational development • Thought leadership
- 4. © The King's Fund 2022 Digital Technologies Change what’s possible Not a magic bullet but one tool that can help address the challenges Beware the hype! Can’t do everything, can do lots and that’s constantly changing too – importance of evidence Bring the best of tech with people: • Automation to reduce workload burden, • improve patient safety, • use data, • improve overall inclusivity
- 5. © The King's Fund 2022 What is Artificial Intelligence? Human like cognition and capabilities At the same time it’s both here now and not here yet • Dictation • Medical image analysis • AI Doctor Foundational technology that feeds into genomics, screening, image analysis, robotics, automation
- 6. © The King's Fund 2022 Artificial Intelligence in healthcare FDA approved 523 AI powered medical devices -> 75% are for medical imaging Evidence generation on utility and risk Pilots in NHS • Falls monitors detecting sound and motion • 20% drop in hospital admissions, 75% reduction in unnecessary physical night time checks, freeing staff time (about £13,000 per staff member per year) • Waiting lists But remember • It affects staff • It’s a system!
- 7. © The King's Fund 2022 Generating evidence for Artificial Intelligence in healthcare Screening Genomics applied to identify people at risk of developing diseases – polygenic risk scores (Our Future Health) AI for mammography • AI technology for the 2nd screening frees up clinician time for patients, reduces number of radiologists and potentially screen more women quicker
- 8. © The King's Fund 2022 Generating evidence for Artificial Intelligence in public health NLP (natural language processing) analysis of free-text information in death certificates - identify potential drug overdose deaths months prior to traditional coding and data release NLP (natural language processing) on social media posts (1.8 million a day) to predict disease occurrence and identify potential outbreaks in real-time Chicago Department of Public Health software identifies children at high risk of lead poisoning and prioritises homes for lead inspections using historical blood lead level tests, home inspection data, child characteristics, property value assessments and census data Targeted public health campaigns focusing on those who may be most receptive using sentiment analysis and social media
- 9. © The King's Fund 2022 Where can AI improve data-led insight? Data Step change in data availability and with AI the usability improves too Novel streams of data for insight into social, behavioural, and environmental determinants of health. • social media, search engines, forums, news media, mobile devices and apps (social determinants) • Wearable devices have data on movements and physiological measures • Environmental sensors have data on air pollution, water quality, environmental noise, weather conditions, and green space Linkage to traditional health data, including that from administrative records, electronic health records, census and health survey data
- 10. © The King's Fund 2022 Artificial Intelligence implementation Relatively simple tools to date e.g. image segmentation, dictation, waiting lists Not adaptive algorithms, still have human in the loop, narrow Barriers to use remain • workflow, IG, legacy • liabilities and • ethical/bias (explainability)
- 11. © The King's Fund 2022 Generative Artificial Intelligence GenAI created a new frontier in Nov 2022 LLMs but also multi-modal Still early stage with evidence generation at the feasibility stage Bridging literacy barriers informed surgical consent
- 12. © The King's Fund 2022 Generative Artificial Intelligence Neuro-tech and Brain-computer interfaces BUT hallucinations and lack of reproducibility
- 13. © The King's Fund 2022 Multi-modal Artificial Intelligence Aug 2023 Google published research on Med- PaLM Multi-modal AI developed on medical data Current issues remain (black box, ethics and bias) + hallucinations & reproducibility Adaptive AI Several data types means challenges to regulatory processes Benchmarking for evaluation is a significant challenge with companies leading this
- 14. © The King's Fund 2022 Overview Published Mar 2023 Literature review Survey Semi-structured interviews with members of public Workshops with NHS, charities, social care, local authorities Lived experience advisory group 4 publications
- 15. © The King's Fund 2022 AI use on evidence for policy making Library team Lots of development for knowledge capture and use Search strategy, summarising information Potential for • Languages • Analysis of data • Augmentation • But… Hallucinations and reproducibility are significant barriers to use
- 16. © The King's Fund 2022 Literature review Literature focus: • Digital inclusion and exclusion Some findings: • Lots of research in this area • Demographics, clinical conditions, region • Simplifications are helpful but limited • Near 100% people online doesn’t mean nearly 100% digital inclusion
- 17. © The King's Fund 2022 Voices of the public Spoke with members of the public 8 people who’s stories show the range of expectations and experience The hopes often not met Frustration When it works it’s transformative
- 18. © The King's Fund 2022 Voices of the public
- 19. © The King's Fund 2022 Factors supporting digital inclusion Technology • Devices • Connectivity Skills & confidence • Digital, literacy Design of tech & services Support Privacy
- 20. © The King's Fund 2022 Practical solutions to improve inclusion Fixing the fundamentals Providing devices • Donation or loans • Managed but not limited Providing data • Donations and data banks • Cliff edge Building digital skills and confidence • VSCO collaboration • Befriending • YouTube
- 21. © The King's Fund 2022 Practical solutions to improve inclusion Structuring services around people’s needs and preferences one-size-fits-all or a rigid service without choice means the service is more likely to exclude people Identifying capability and preferences Services with different levels of digitalisation Work with communities to develop more inclusive services
- 22. © The King's Fund 2022 Practical solutions to improve inclusion Improving the quality and consistency of services Creating a centralised group of expertise • Collaboration across orgs • Partnership with communities • A network or hub to hold knowledge and help other orgs
- 23. © The King's Fund 2022 National recommendations Support digital-first or digital-only services to have physical and low tech alternatives Incentivise and support suppliers to provide technology that mitigates digital exclusion Through funding and support encourage the exploration and use of technology to narrow the gaps in inequalities Work with cross-government partners to tackle systemic barriers to access to digital services Support and enable ICSs to have necessary resources, capacity and capability to co-develop services
Editor's Notes
- Slide 2 – so a bit about me. I’m a physicist and engineer by background, so originally very technical. Worked in the NHS in hospitals and with GPs supporting entrepreneurs and innovation. Building collaborations to get mature research and innovation into the clinical setting. I now work at The Kings Fund researching developments in the NHS and social care and creating reports and recommendations on what’s working or not and how to make improvements
- Slide 7 – so what did we hear when we spoke with members of the public? We spoke with a few 10s of people across different ages, regions, backgrounds etc 8 people’s stories are told in one of our publications. In short people are hopeful and largely supportive of digitally enabled services but their expectations are not being met. This is creating frustration and confusion.. But when it does work it’s really transformative.
- Here’s some quotes of what we heard from people. There’s people who are forced to use digital channels, have not choice, avoid healthcare services and end up in hospital. Others are forced through digital channels, don’t have the skills and their carers end up taking control. There’s others who are very digitally able but the way services are designed they can’t set up their assistive devices or can’t have them in consultations so can’t benefit. A person we spoke to who was homeless and can’t read or write but uses her smartphone to do things like read out text and fill forms mentioned how difficult healthcare services are, incompatible with accessibility options and she relies on support staff which gives her no privacy. But it’s important to remember for some it does work, when a deaf lady we spoke with has the right configuration of services and technology it’s an incredible leap forward. For Bill the online consultations and remote monitoring have substantially changed his care. Especially when services are different from different providers in the same local area, so we heard a few times when a person being interviewed had very different digital services to a relation who they cared for.
- so the factors supporting inclusion are outlined here:
- as I mentioned we ran some workshops to understand what practical approaches can be taken to tackle digital exclusion. Firstly to fix the fundament barriers of devices, data and digital skills. Organisations across NHS, social care, local authorities and charities are often working in collaboration to source devices from companies or purchased through charitable donations. These devices are given out or loaned to people when loaned it’s a try before you buy kind of structure to help people try tech. The devices are often managed to mitigate cybersecurity issues but they are not locked for health use only. We learnt this is very important or risk the device becoming an expensive paperweight. Also streaming, messaging etc builds digital skills. Similarly for data, collaborations across organisations to provide people with data on SIM cards but this can create a cliff edge of concern as data runs out. Lastly is the digital skills and confidence where charities and volunteers are helping people in the community to use their devices. This might be setting up email and registering with the NHS app or accessing youtube where there’s lots of things including NHS videos. one of those elements fail, then attempts to improve the use of digital services and make them more inclusive are likely to fail. Device, connectivity and support are all equally important
- we heard how some areas are changing how services are structured to suit peoples needs and preferences. A practice has surveyed and contacted all their patients to grade their digital engagement levels outside of health. Then use this to help improve how they communicate and provide services. They’ve started to create 3 tiers of services, the first is no-tech : which is traditional second is low tech : where they’re putting digital touch points in NHS and community settings like libraries and pharmacies. Here there’s a member of staff or volunteer to help people use the tech. Third is high tech: where patients can use their tech at home Some NHS orgs are going one step further and co-developing the technology like apps and services with communities to ensure they work for people
- Finally there’s a need to ensure that the services are consistent and equally high quality. We found that creating a hub of expertise in a geographic region is really helpful to do this. This doesn’t mean you’ve a new organisation or location, it’s a group of people (a network) that have the best practice, skills and links to communities to co-develop and help providers develop digitally enabled services.
- We also created a policy brief, just 2 sides for recommendations on what can be done at a national level to reduce digital exclusion. The recommendations are listed here.