Lumiata’s suite of AI-powered predictive analytics tools helps users better manage care and finances…

 

“We have a supply and demand problem,” says AI entrepreneur Ash Damle. “We have an influx in the US of 80 million baby boomers. But we also have about a 10-20% shortage of general practitioners. Worldwide, it’s a 30-50% shortage. At the same time, we’re collecting 100 times more data than ever before. The data itself is providing an opportunity.”

Damle was saying the above in an interview, ten years ago. But even then, he realized there were numerous interactions between the patient and the care infrastructure and there was a trend towards hyper-personalization.

However, there was practically nothing to make sense of the ever-growing amount of information coming into the healthcare system. There was no way to tell what’s going on with a patient experiencing fever and asthma. There was no tool to predict when someone will become diabetic and the kind of care they should opt for as the cost of care heightens. All this got Damle thinking and led him to founding MEDgle in 2013. An abbreviation for “medical Google”, MEDgle was an analytics platform, assisting clinicians in diagnoses and understanding how illnesses correlate with age, lifestyle, and gender.

MEDgle was relaunched in 2018 as Lumiata, under the leadership of the new President and CEO, Dilawar Syed, who has a mission to democratize AI to reduce the cost of care and improve outcomes. Syed has spent most of his career in technology and the customer management software space. His exposure to healthcare was more on the civic side, but that was when he got to see firsthand, the challenges, particularly the cost of care that was presented to the country.

“The healthcare industry was complex, people are trying to move it forward amid fierce competitions from many stakeholders, and the conversation around reforms continues today,” says Syed. “So, one day, I said to myself, if I have a chance, I want to be able to deploy the high-tech products that I built as a leader in the tech space, to the healthcare sector. I don’t want to see healthcare as a business, but a public challenge that’s affecting all of us.”

Indeed, according to the Agency for Healthcare Research and Quality, there were as many as 3.5 million adult hospital stays in the US in 2017, accumulating nearly $34 billion in healthcare costs. Nonetheless, close to 13% of these hospital stays (9% of the cost) are preventable. “There’s a huge need for us to improve the public policy, delivery of our care and the way we manage. I believe AI and data can help with all of them,” Syed adds.

Lumiata’s suite of AI-powered predictive analytics tools was designed for better management of healthcare costs by enabling a partnership with payers, care providers, and digital health companies to address financing, reimbursement, care, and pharmacological challenges. They were built from healthcare information, medical knowledge, and clinical intellectual property of 120 million patient records, 35,000 physician-curated hours, lab results, medical billing codes, insurance claims, and 50 million articles from the free biomedical study search engine, PubMed.

The company claim its solutions can identify the likelihood of patients developing one of over 20 diseases within 12 months; stratify and predict which patients are candidates for remote care or intervention and forewarn patients who may be at risk of hospitalization and readmission. The analytics tools also calculate health care resource needs, related costs, and disease spread by region and community hospital system and can be readily integrated into existing healthcare systems and conduct quality checks, ensuring the information it leverages is up to date.

Specifically, Lumiata’s predictive applications for healthcare business teams manage clinical costs and risks to improve decision support, transparency, and patient centricity. Its machine learning toolkit facilitates healthcare data scientists to conjure and deploy predictive models. The Lumiata platform also has automated data management, pre-built models, and AutoML capabilities offering low or even no-code options for healthcare organizations with limited data science expertise to benefit from the technology.

In January, Lumiata raised $14 million Series B funding to scale its platform and invest in customer acquisition ahead of the opening of an office in Mexico later this year. Syed believes the COVID-19 pandemic has created urgent needs in the market for unique solutions like the ones offered by Lumiata. “The pandemic has brought once-in-a-century challenges to insurance underwriters when they had to predict patient risk for 2021 in the summer of 2020,” he says. “They are in the business of managing risk but the scale of these risks they haven’t seen.”

Nevertheless, Syed believes helping the healthcare industry during the pandemic is just the beginning for Lumiata. “If there was one time for AI to be deployed to manage such a massive, unforeseen phenomenon, that time is now. This is just the very first step for us to address the incredible need that is out there, improve our healthcare and deliver a hopefully societal benefit in a very challenging time.”