AI excels at making sense of data. Health Data Analytics Institute (HDAI) is a case in point — its AI-powered platform analyzes over a billion patient encounters to improve health care outcomes. After several years of operating quietly under the radar, the company today revealed that it has raised $16 million, which it will use to launch an API that widens access to its clinical prediction service.
HDAI founder and CEO Nassib Chamoun says the company is already collaborating with organizations to measure the impact of its soon-to-be-expanded platform. HDAI recently received funding from the Robert Wood Johnson Foundation to support a project that will analyze demand for long-term care. Separately, it’s working with New England Baptist Hospital to study the effectiveness of surgical and nonsurgical options for spinal procedures. It’s also partnering with the Cleveland Clinic to match patients with the appropriate level of presurgical support, using AI. And HDAI plans to team up with Houston Methodist to test clinical applications that would use its risk predictors.
“Our goal is to democratize access to artificial intelligence (AI) in health care, to make it available and as easy to use for as many organizations and individuals as possible,” said Chamoun, previously executive vice president at health care products startup Covidien, which was acquired by Medtronic in 2015. “Over the last year, health care providers have dramatically increased their investment in deploying AI. We’re focused on helping these organizations scale quickly without taking on unnecessary work.”
HDAI’s product — which has its roots in academic studies dating back to 2002 — offers predictors for a range of clinical and financial outcomes, from in-hospital complications and mortality risk to total cost of care and risks of developing chronic conditions. The company says it can apply its predictive model, which was trained on data from over 100 million people in the U.S. and over 20 years of follow-up records, to patient data from both paper charts and electronic health records. Furthermore, it says the model can generalize across geographies and populations and can capture new information as individuals and populations age.
Beyond its health system pilots and studies, HDAI works with carriers to identify insurance products for individual customers and their families. It also furnishes pharmaceutical clients with information about which drugs might work, how well, and for which patients.
HDAI’s work in predictive medicine is on-trend — the global AI in medicine market was valued at $719 million in 2017, according to Allied Markets Research. Spring Health has raised $22 million to expand its AI service that matches users with a mental health treatment plan. Clew Medical launched a predictive analytics platform to help prevent life-threatening complications for patients. Charlotte, North Carolina- and Santa Clara-based LeanTaaS snagged $40 million for AI-imbued products that ostensibly optimize health clinic operations. And KenSci nabbed $22 million for its AI-driven prediction platform that helps practitioners cut costs intelligently by identifying contributing clinical and financial factors.
But Invus managing director Philippe Amouyal says what’s compelling about HDAI is its “pragmatic” focus on applying AI to help improve clinical practice today, not in the distant future. “Our involvement with HDAI stems from our belief that their platform has the potential to become a fundamental analytics layer that improves care,” he added. “[It provides] a rigorous quantification of patient risk to inform clinical judgment.”
HDAI is based in Dedham, Massachusetts and has about 25 employees. Current and previous investors include Invus and QuantRes founder Harald McPike.
Author: Kyle Wiggers.
Source: Venturebeat
