Gary Monk on DTx and Common Sense in Analysing Wellness Data From Apps and Wearables

In this episode Gary Monk, independent consultant with over 25 years in the pharma and healthcare sectors where he worked in roles from R&D to business IT and strategic marketing, talks about the current state of digital therapeutics, remote patient monitoring, the potential of AI in healthcare, and the challenges with data integration. He also shares his personal insights on the use of wearables and their impact on health anxiety.

Key Discussion Points:

Digital Therapeutics and Integration Challenges

Fragmentation in the Space: Many digital therapeutics are siloed, with individual apps that do not integrate well with each other or broader healthcare systems.

Potential for Holistic Solutions: apps and digital therapeutics need to be more connected, for example, integrating with wearables or offering treatments.

Uncertain Future: While optimistic in the long term, Gary is cautious about short-term setbacks, noting that companies in this space may struggle without proper evidence and reimbursement models in place.

Remote Patient Monitoring and Virtual Care

Excitement Around Remote Monitoring: there are benefits of remote monitoring, especially for elderly and chronically ill patients, allowing them to stay home longer and safer.

Expanding Beyond Monitoring: Discussion expands on using technology not just for monitoring but also for providing interventions, such as reminders, voice support, and even predictive capabilities like fall prevention.

Wearables and Real-World Data

The Importance of Continuous Data: long-term, imperfect data may be more valuable than short-term, highly accurate clinical data in certain cases, such as tracking motor function.

Personal Experience with Wearables: Despite his enthusiasm for digital health, Gary admits he no longer uses wearables due to anxiety caused by over-monitoring and lack of actionable insights.

AI in Healthcare

Cautious Optimism: While excited about AI’s potential, AI needs to be integrated thoughtfully into healthcare workflows. He points out that many current AI solutions are useful but not yet integrated into clinical practice.

Ethical Questions Around AI: The conversation touches on whether AI should be used to predict diseases, especially if no treatment is available. This is particularly relevant in areas like Alzheimer’s research.

Integration as a Key Barrier

The Real Challenge: Both speakers agree that integration is one of the biggest hurdles in digital health today. As various apps and AI tools proliferate, getting them to work within existing systems, like clinical workflows, remains difficult.

Example from Clinical Trials

Even in areas like remote clinical trials, which are technically feasible, organizations are struggling to keep up due to complex internal processes and outdated systems.

www.facesofdigitalhealth.com

https://fodh.substack.com/p/ai-digital-health-pharma