Digital Health Podcast- Royal Society of Medicine

This episode features a conversation with Dr. Bob Wachter, a prominent physician and academic known for his significant contributions to the field of healthcare and technology. Dr Wachter has authored several influential books including the brilliant "The Digital Doctor: Hope, Hype, and Harm at the Dawn of Medicine's Computer Age" (2015) In 2016, Dr. Robert Wachter was commissioned by the UK government to deliver Wachter Review aimed to assess the state of health information technology (IT) in the National Health Service (NHS) and provide recommendations for its improvement.  As we mark seven years since the Wachter Review, Dr Wachter joins me to reflect on the progress made, future potential, and address the persistent challenges facing the NHS. The conversation explores the journey that the NHS has come on since 2016 including the widespread introduction of electronic health records, patient health record access and development of NHS CCIOs. It also explores the future of AI enabled healthcare, the challenge of the so-called productivity paradox and whether AI is likely to result tin evolution or revolution of care delivery.

This episode features a conversation with Jeanette Kusel- Director for Scientific advice at NICE the national institute of health and care excellence, and addresses the role that NICE  has to play with regards to digital health technologies Discussion topics include: The difference between the evaluation required for regulatory approval (CE/UKCA marking) and NICE approval Innovative new approaches to assessing healthtech innovations including: The NICE META tool Early value assessments The AI and digital regulations service NICE Evidence Standards Framework What is involved in a NICE approval process for digital health technologies  Common mistakes that companies make when evaluating their products and how these can be avoided Links: META tool: https://meta.nice.org.uk/ Early value assessments: https://www.nice.org.uk/about/what-we-do/eva-for-medtech AI and digital regulations service: https://transform.england.nhs.uk/ai-lab/ai-lab-programmes/regulating-the-ai-ecosystem/the-ai-and-digital-regulations-service/ NICE evidence standards framework: https://www.nice.org.uk/about/what-we-do/our-programmes/evidence-standards-framework-for-digital-health-technologies NICE Real World Evidence framework: https://www.nice.org.uk/corporate/ecd9/chapter/overview

Max Jaderberg, Director of Machine learning at Isomorphic labs, shares the Isomorphic approach to drug discovery in one of their first interviews as they emerge from shadow mode. In 2020 Google DeepMind made history when they took on the grand challenge of biology- the protein folding problem- with their algorithm AlphaFold2.  Their success prompted the creation of a sister company, Isomorphic Labs. Our conversation topics include:   - The concept of “Digital Biology”- How AI can be used model the biological world  - Bottlenecks in the drug discovery process and how AI could circumvent them - How AI may unlock 'undraggable targets' to find treatments for incurable diseases  Links: Isomorphic labs website: https://www.isomorphiclabs.com/ AlphaMissence: https://www.deepmind.com/blog/alphamissense-catalogue-of-genetic-mutations-to-help-pinpoint-the-cause-of-diseases

This episode focuses on the topic of AI education and workforce transformation with Dr Hatim Abdulhussein, National Clinical Lead for AI and Digital Workforce at NHS England Key discussion topics include: - The NHS England strategy for AI education for the healthcare workforce - 5 healthcare workforce AI archetypes: Shapers, Drivers, Creators, Embedders and Users - The role of workforce transformation from AI MDT teams to the professionalisation of the digital and data professionals and the creation of new leadership roles in technology and AI.  Developing healthcare workers' confidence in AI: https://digital-transformation.hee.nhs.uk/building-a-digital-workforce/dart-ed/horizon-scanning/developing-healthcare-workers-confidence-in-ai Artificial Intelligence (AI) and Digital Healthcare Technologies Capability framework: https://digital-transformation.hee.nhs.uk/building-a-digital-workforce/dart-ed/horizon-scanning/ai-and-digital-healthcare-technologies?

This episode features a conversation with Eric Topol, a renowned cardiologist scientist, and author. He is the founder and director of the Scripps Research Translational Institute where he is a professor of Molecular Medicine . He is editor-in-chief of Medscape and He has published three bestselling books including the highly influential  Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again .  In 2019 he led the Topol review a report focussed on planning for the NHS future workforce, integrating genomics, digital medicine, and artificial intelligence. Our discussion topics include:  How LLMs could make doctors more empathetic The potential for ‘keyboard liberation’ using LLMs to repair the damage that EHRs have inflicted on the doctor-patient relationship The ‘silicon-vallydation’ issue and the need for high quality evidence generation for AI Hallucinations and the ‘frequently wrong never in doubt’ issue

This episode features a discussion with Mohammad AI-Ubaydli- CEO and Founder of Patients Know Best on personal health records. Key discussion points include - Do patients really know best? - How personal health records are driving clinicians to rethink the way they write their clinical notes - Changes that are needed within clinical training to better prepare the workforce for treating patients using personal health records

This episode focusses on the topic of confidence in healthcare AI technologies. My guest is Dr Mike Nix, Lead AI Clinical Scientist at Leeds NHS trust. Discussion topics include: How AI errors and human errors are fundamentally different, and why that’s so important in the context of healthcare AI  The concept of explainable AI and its potential limitations in the context of human cognitive biases and decision making  The role of regulation in supporting AI confidence  Link to reports on Healthcare workers' confidence in AI: https://digital-transformation.hee.nhs.uk/building-a-digital-workforce/dart-ed/horizon-scanning/understanding-healthcare-workers-confidence-in-ai https://digital-transformation.hee.nhs.uk/building-a-digital-workforce/dart-ed/horizon-scanning/developing-healthcare-workers-confidence-in-ai

This episode centres on the evaluation of digital health solutions. It features a conversation with Dr Saira Ghafur, Consultant in Respiratory medicine and co-founder of Prova Health. Discussion topics include - The different types of evidence required at different stages of product development - The use of innovative approaches such as simulation to produce evidence for digital health technologies - The importance of linking evidence and reimbursement and different international approaches that are being implemented to tackle this

This episode focusses on PIFU (patient initiated follow up) and how technology is helping to reimagine outpatient care pathways. It features a conversation with Tom Whicher, CEO and co-founder of DrDoctor Discussion topics include: - How technology enabled patient initiated follow up pathways are helping patients, clinicians and the healthcare system  - How data from appointment bookings is enabling a personalised approach to patient appointment booking and outpatient care  - How PIFU technology can help to even out the variability in care experienced in the NHS

In this episode Giuseppe Sollazzo shares his insights from the NHS AI lab skunkworks programme - an initiative to find new ways to use AI for driving forward the early adoption of technology in the NHS. Discussion topics include: - The value of an open-source approach to AI development in the public sector - The importance of being transparent about both successes and failures - The role of MDT AI teams in the NHS and upskilling the workforce in relation to AI More information about the skunkworks projects here: https://transform.england.nhs.uk/ai-lab/ai-lab-programmes/skunkworks/