Uma (Veerappan) Nuggehalli of Flare Capital Partners thinks the healthcare AI startups that will come out on top will be companies that integrate seamlessly into workflows, build proprietary datasets and quickly determine how to sell their technology.
Katie Jacobs Stanton, founder of Moxxie Ventures, shared some details of how she and her team evaluate healthcare AI startups. She stressed the need for founders with deep industry expertise, differentiated products and realistic distribution strategies.
Veradigm examines key clinical trends, comorbidity profiles, and treatment trends across adolescence, reproductive years, and peri-/post-menopause. Download it today!
Healthcare AI startups are experimenting with pricing models that tie their costs to real-world results, such as completed tasks or improved patient outcomes. While investors see this as a way to prove value, many hospitals remain skeptical, preferring predictable pricing.
Investors, health systems and payers have grown more selective about AI startups in recent years, according to a panel of experts speaking at MedCity News’ INVEST Digital Health conference. Customers and investors alike are now demanding clear evidence of ROI before committing to deals or partnerships.
The clinical decision support market is evolving quickly. With heavy investor backing and competing strategies around specialization, data depth and distribution, the coming years will determine which companies emerge as lasting leaders at the point of care.
Chirag Shah, partner at Define Ventures, thinks the success of a healthcare AI startup often depends on its ability to move beyond a narrow point solution. By integrating AI into workflows and expanding from initial “wedges” into full platforms, startups can stand out from the competition, he said.
By reducing administrative burden and redesigning workflows around human needs, it creates space for what matters most: connection between clinicians and patients.