Lumiata raises $14 million to predict health care costs and outcomes with AI

Lumiata, a company providing AI-powered predictive analytics for managing health care costs, has raised $14 million. The company says it’ll use the funds to scale its platform and invest in customer acquisition ahead of the opening of an office in Guadalajara, Mexico in 2021.

As many as 3.5 million hospital stays among adults in 2017 were considered potentially preventable, costing nearly $34 billion, according to the Agency for Healthcare Research and Quality. The preventable stays represented nearly 13% of all hospital stays and almost 9% of all costs, excluding obstetrics.

Lumiata’s apps and data science tools ostensibly solve this by enabling a partnership with payers, providers, and digital health companies to address underwriting, actuarial, care management, and pharmacological analytics challenges. The platform combines health care datasets from standardized codes to handwritten notes into a single dataset; patients’ data is ingested, cleansed, and organized into a unified record and enriched with annotations that make it ready for machine learning.

To deliver insights, Lumiata claims to draw from healthcare data, medical knowledge, and clinical intellectual property from 120 million patient records, 35,000 thousand physician-curated hours, lab results, medical billing codes, insurance claims, and 50 million articles from the free biomedical research search engine PubMed. The platform can identify patients likely to develop one of over 20 diseases within 12 months, stratify and predict which patients are candidates for remote care or intervention, and anticipate which patients are at risk of hospitalization, admission, and readmission. Beyond this, Lumiata can calculate healthcare resource needs and associated costs as well as disease spread by region, community hospital system..

Lumiata

Above: Lumiata’s AI-powered risk matrix.

Image Credit: Lumiata

Lumiata, whose platform integrates with existing systems and informs physicians of patients’ comorbidities, prior hospitalizations, and more, says it performs autonomous quality checks on the datasets in its platform to ensure they remain up to date. Moreover, the company claims its over 100 pretrained trained machine learned models are 5%-35% more accurate than leading prediction models.

“In many instances, Lumiata has identified hundreds of millions of dollars in risks on their customers’ books that they were previously unaware they had,” a spokesperson told VenutreBeat via email. “Customers are also able to reduce costs and provide more responsible and responsive healthcare to their members. Deploying Lumiata is a low- to no-code process. It is cloud-based, fully scalable, and integrates with existing systems through APIs.”

Defy.vc led Lumiata’s series B round announced today. AllegisNL Capital, Khosla Ventures, and Blue Venture Fund also participated, bringing the company’s total venture capital raised to date to over $45 million.

Lumiata competes with a number of companies in the health care predictive analytics space, which is expected to be worth $19.5 billion by 2025, according to a report from Grand View Research. ClosedLoop.ai, a health care data science startup specializing in AI and automation, recently raised $11 million. There’s also KenSci, which aims to help health care practitioners cut costs by algorithmically identifying contributing clinical and financial factors. Cardinal Analytx Solutions develops predictive analytics software for health care payers and providers. For its part, LeanTaaS taps data science to improve health care provider performance in the area of resource utilization. And Medopad employs a combination of machine learning and big data analyses to help predict and manage chronic diseases,

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