The Healthcare Contrarian Podcast

The Healthcare Contrarian Podcast
Podcast Description
It's time to challenge the conventional wisdom and sacred cows in healthcare. ankoors.substack.com
Podcast Insights
Content Themes
Explores topics at the intersection of AI, philosophy, and human innovation, featuring episodes that cover the role of AI in healthcare, free will vs. determinism, and critiques on current practices in generative AI, with specific examples such as the impact of Judea Pearl's work on causality in AI and Peter Thiel's insights on innovation

It’s time to challenge the conventional wisdom and sacred cows in healthcare.
After I wrote Why Primary Care is a Product No One Wants, Dr. Paulius Mui – a leading voice in primary care innovation – was happy to let me know where I got it wrong.
In our conversation, we dive into why primary care is both an investment and a broken business model, the misalignment between what doctors and patients actually want, and whether throwing more money at the problem will fix anything.
We also explore the rise of Direct Primary Care (DPC), the evolving role of AI in clinical decision-making, and what the future of primary care looks like in a world of corporate medicine, policy constraints, and shifting workforce dynamics.
Dr. Mui shares why technology is like fire – it can cook a meal or burn down the house – and how we should be thinking about empowering clinicians and patients alike, rather than just optimizing for efficiency.
It’s a candid, thought-provoking conversation about the past, present, and future of primary care. Give it a listen and let me know what you think!
Conversation Companion Guide – Appendix
Dr. Mui mentions a few concepts and books in our talk. Below is a quick reference for you if needed. FYI this list was made with the help of an LLM.
📚 Concepts and Books Referenced
* Nicholas Carr – The Glass Cage
* Explores automation’s effects on industries like aviation, healthcare, and manufacturing, warning about the risks of over-reliance on technology.
* Highlights the paradox of automation: while technology makes tasks easier, it can also deskill professionals, making them dependent on the very systems meant to assist them.
* G. Gayle Stephens – The Intellectual Basis of Family Medicine
* Positions family medicine as a countercultural movement resisting the fragmentation of care caused by the rise of medical specialization.
* Discusses how primary care’s holistic approach fosters long-term patient relationships, which is often undervalued in fee-for-service models.
* Clayton Christensen – The Innovator’s Prescription
* A blueprint for disruptive innovation in healthcare, proposing models like retail clinics, technology-driven diagnostics, and a stronger role for primary care.
* Introduces the concept that what was once specialized medical knowledge is now being democratized, first to primary care physicians and ultimately to patients through technology.
* Rebecca Etz – PCPCM Measure (Patient-Centered Primary Care Measure)
* A validated tool designed to measure the strength of patient-provider relationships and assess primary care’s comprehensiveness.
* Suggests that strong patient-provider continuity leads to better health outcomes, yet current healthcare reimbursement models fail to prioritize it.
* Barbara Starfield – Four C’s of Primary Care
* Defines the essential functions of primary care: Care Coordination, Continuity, Comprehensiveness, and First Contact access.
* Advocates that strengthening primary care leads to better health outcomes, lower costs, and reduced disparities, yet U.S. policy and payment structures undermine these core principles.
* Direct Primary Care (DPC)
* A membership-based healthcare model where patients pay a flat monthly fee for primary care services, bypassing insurance and reducing administrative burdens.
* Seen as a potential solution to improve physician satisfaction and patient care by allowing for longer visits, better continuity, and cost transparency. However, concerns exist about its scalability and impact on access for lower-income populations.
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