Why Do Digital Health Startups Keep Failing? With: Dr. Bernardo Perez-Villa
Dr. Bernardo Perez-Villa, Senior Innovations Engagement Partner at Cleveland Clinic, explains why so many digital health startups fail. The biggest reason is lack of validated clinical need and poor product-market fit—too many founders build solutions in search of problems. Perez-Villa emphasizes that successful startups must engage in primary and secondary market research, talking to clinicians and patients to confirm problems are real and worth solving. He also stresses that even with regulatory clearance, startups often struggle with revenue because the U.S. healthcare system is fee-for-service and reimbursement is tied to complex CPT codes, coverage, and payment structures. Without alignment on need, reimbursement, and cost, startups face what he calls the 'impossible triangle' of quality, cost, and time.
Episode Contents:
Key Takeaways
Most digital health startups fail due to lack of unmet clinical need and product-market fit. Revenue models depend on reimbursement pathways like CPT codes, not just FDA clearance. Startups must validate problems with clinicians and patients before building solutions.
Transcript Summary
Why do most health startups fail?
Lack of unmet clinical need and poor product-market fit.
How should startups validate problems?
Through primary market research—talking to clinicians and patients—and secondary research like literature and search data.
Why do revenue challenges persist?
Even with FDA clearance, reimbursement depends on complex CPT code approval and payment rates.
More Topics
- AI in Patient Care
- AI in the Healthcare Industry
- AI and Medical Innovation
- Healthcare Ethics and Policy
Keep Exploring
About the Series
AI and Healthcare—with Mika Newton and Dr. Sanjay Juneja is an engaging interview series featuring world-renowned leaders shaping the intersection of artificial intelligence and medicine.
Dr. Sanjay Juneja, a hematologist and medical oncologist widely recognized as “TheOncDoc,” is a trailblazer in healthcare innovation and a rising authority on the transformative role of AI in medicine.
Mika Newton is an expert in healthcare data management, with a focus on data completeness and universality. Mika is on the editorial board of AI in Precision Oncology and is no stranger to bringing transformative technologies to market and fostering innovation.