Healthcare data science platform provider ClosedLoop has partnered with Booz Allen Hamilton to bring stronger predictive analytics capabilities to federal government health organizations and the firm’s other clients.
The new strategic partners recently competed against each other as part of the Centers for Medicare and Medicaid Services’ (CMS) AI Health Outcomes Challenge launched back in 2019, ClosedLoop CEO Andrew Eye told Fierce Healthcare.
Booz Allen Hamilton’s team had been named to the top 25 of more than 300 participants but was knocked out by the final stage of seven, Eye said. At that point, the two groups collaborated for the competition’s final round and, in May, secured the top spot and its cash prize of up to $1 million.
The weeks since have found the companies navigating through the early stages of their strategic partnership. Eye said that ClosedLoop is just beginning to train the IT consulting firm’s team on the startup’s data science technology and that his group is looking forward to the business benefits of working with the federal government’s single largest provider of AI services.
“Booz Allen, at the end of the day, they’re a system integrator, they’re a consulting firm. Their business is providing talent and resources—not exclusively to the public sector but that’s a large, large portion of their business,” Eye said. “For us, we look at it as we’re a technology vendor and a software vendor. We need partners like Booz Allen that can take that software, implement it, integrate it, deploy it, configure it and so forth for large enterprises and, particularly, for the federal government.”
The Austin, Texas-based startup’s machine learning algorithms help provider and payer customers identify areas in which they can avoid costs, optimize operations and generate new revenue.
These offerings can take the form of an off-the-shelf offering that ClosedLoop can fine-tune for health organizations with limited analytics expertise or capacity. For others that already have data scientists on hand, Eye said the startup’s platform can help those teams build, deploy and monitor effective predictive models quicker and cheaper.
“Our goal is to support our client’s missions at speed so they can make the quickest and highest impact for their constituents so from a software perspective, ClosedLoop’s platform, which is purpose-built for healthcare, proves valuable in quickly getting our health-focused analytics teams up and running,” Matt Keating, principal at Booz Allen Hamilton, told Fierce Healthcare in an email statement. “ClosedLoop’s out-of-the-box capabilities for connecting, normalizing, cleaning and engineering features from health data sets greatly reduces the time our team would otherwise spend wrangling data or creating features, which means quick impact for our clients and their stakeholders.”
While CMS’ competition helped the startup increase its name recognition within the healthcare industry, Eye said that it also provided an opportunity to demonstrate ClosedLoop’s ability to present its data insights in a way that doctors and other decision-makers can trust.
The AI Health Outcomes Challenge graded competitors on the accuracy of their models as well as their ability to explain that prediction to a clinician. Judges reviewed the platform’s interface to grade ClosedLoop and its competitors on its transparency, communication and overall trustworthiness in regard to a live clinical decision.
“The reason that’s so important [is that] different industries have different applications of AI. … If I’m predicting the stock market and I get it right more often than not and I get a financial edge, who cares how I made those predictions?” Eye said. “When it comes to healthcare, there’s a decision-maker between your prediction and the impact on the world—a doctor. If that physician doesn’t trust the prediction, then it’s never going to have an impact.”
There’s little shortage of opportunities for predictive analytics to benefit healthcare. On the smaller scale, Eye said his company’s platform has spotted numerous opportunities for organizations to deliver proactive care—for instance, by flagging a teen previously admitted for attempted suicide for proactive mental health interventions.
More broadly, both partners stressed that high costs and inefficiencies driven by the country’s complex web of payers, providers, policymakers, regulators, researchers and other actors could be cut down by insightful and actionable analytics.
“The rising cost of healthcare, coupled with an expansion of data—from institutional medical devices, to wearables, to genomics—creates both an opportunity and an imperative to harness the power of data to improve outcomes while curbing the cost of care,” Keating said. “Big picture, Booz Allen sees AI as being a force multiplier for performing comparative effectiveness research across our healthcare system, enabling actors at all levels to make more informed decisions to improve individual and population health.”