One investor believes that the key to the success of healthcare AI
Chirag Shah, partner at Define Ventures, said AI in healthcare is hopeful, but still insufficient.
Last month, the venture capital firm published an AI paper that argued that the healthcare industry must start to move beyond narrow use case AI and adopt more workflow-integrated platforms to achieve lasting impact. The convergence of factors – Continuous funding issues, rapid technological advancements and growing healthcare client preparation are giving way to the defined “moment in a generation” in which the best workflow integrated AI startups can change how to deliver, paid, paid and experienced care.
Define uses “medical houses” as a framework for understanding medical innovation. This includes the front door, where patients first interact with the system; the foundation consists of data and infrastructure; and the room, representing nursing services.
When it comes to the front door, AI can make outreach and engagement more personalized by combining clinical and personal data. Shah explains that the foundation’s innovation history is centered on digitalization and aggregation – with AI, healthcare organizations turn data into insights.
As for the room, AI has started uninstalling administrative tasks such as charts, documents and messaging, so providers can focus more on patients, he said.
Shah said the defined portfolio companies span across all areas of the house. One of these startups is Luminai, which uses AI to automate routine tasks such as patient intake, qualification examinations, and documentation, freeing up healthcare workers to focus on direct patient care. Another is Layer Health, which sells AI engines to quickly abstract and organize clinical data from charts.
Shah points out that it is exciting that people are still in the early stages of showing its full potential in terms of the future of AI in the field.
As innovation continues, he believes the most successful AI startups will be startups that can quickly integrate into providers, payers and pharmaceutical workflows without any additional burden.
Shah added that while it is easier than ever to build a point solution, it is wiser to scale with customers to second, third and fourth use cases to develop their tools from the wedge into platforms. As he has seen, only one narrow pain point risk displaced companies can be addressed.
Portfolio Company Cohere Health is a great example of a startup that expands its AI capabilities. Shah explained that the company began with prior authorization for musculoskeletal care and then expanded to oncology, cardiology, medication and software-based models.
“In the world of AI, when other people can move faster, even faster than you, one of the mistakes we see is that people don't have enough time to understand what's going to happen next with the work the customer finds. What else will happen after that wedge. What else your customers will need after the wedge, what you want is what you want, the competition you want is the only important product you have. It's really accelerated now, especially compared to previous years,” he said.
From his perspective as a digital health investor, Shah believes that the key to healthcare AI success is not just developing powerful products—startups need to scale beyond initial use cases and move faster than competition.
Photo: z_wei, Getty Images
