Advanced Computing in the Age of AI | Monday, April 19, 2021

Healthcare Investors Target Enterprise Analytics, AI-Based Care Coordination 

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The uneven application of AI technology within the healthcare sector appears to be smoothing out as investors increasingly target analytics and AI-based systems for applications like coordinated patient care.

Those applications could soon join established AI-based use cases such as medical imaging as market drivers, analysts say.

A pair of funding announcements this week underscore how machine learning-based analytics and AI-based “intelligent care” platforms are making inroads as healthcare data is commoditized.

Clarify Health Solutions, an enterprise analytics vendor, announced a $115 million Series C funding round this week led by new investor Insight Partners. The funds will be used to scale the San Francisco-based startup’s self-service healthcare analytics cloud and other business applications. The healthcare startup has so far raised $178 million, according to the website Crunchbase.com.

Elsewhere, “care coordination” specialist Viz.ai announced a $71 million Series C round also led by Insight Partners along with Scale Venture Partners. Kleiner Perkins was among a group of new Viz.ai investors, pushing its funding total to more than $151 million.

Viz.ai’s platform has been clinically validated for stroke victims. The new funding would be used to expand beyond stroke to cardiology, pulmonary, trauma and other acute care applications, the startup said Wednesday (March 17).

Clarify Health focuses primarily on healthcare analytics via a platform that uses machine learning to “sequence” healthcare data in the cloud. Viz.ai offers AI-based products for coordinating patient care with tools that organize treatments, then share clinical information with healthcare providers and health insurers.

Proponents of the AI-based approach note that care coordination platforms address time-critical healthcare scenarios such as treating stroke victims, thereby improving healthcare outcomes while reducing costs.

According to the Agency for Healthcare Research and Quality, “Well designed, targeted care coordination that is delivered to the right people can improve outcomes for everyone: patients, providers, and payers.” The agency is a unit of the U.S. Department of Health and Human Services.

Meanwhile, Clarify’s healthcare analytics platform seeks to improved clinical decision-making by replacing the analysis of raw data using manual tools. That approach promises to “maximize the intersection of patient, clinical and financial outcomes,” Hillary Gosher, a managing director at Insight Partners, said in a statement.

Other medical AI startups note the market’s evolution away from “top-down” approaches such as IBM Watson’s that have alienated key segments of the healthcare sector. That has spawned deep-pocketed companies like Clarify and Viz.ai seeking to transform healthcare from the inside.

“We’ve found that working closely with health systems to understand their goals, adapting our AI interfaces to fit their existing workflows, and having clinician champions who can foster trust and understanding among their peers is the key to a successful AI implementation,” said Dr. John Frownfelter, chief medical officer at Jvion, the prescriptive analytics startup.

About the author: George Leopold

George Leopold has written about science and technology for more than 30 years, focusing on electronics and aerospace technology. He previously served as executive editor of Electronic Engineering Times. Leopold is the author of "Calculated Risk: The Supersonic Life and Times of Gus Grissom" (Purdue University Press, 2016).

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