FREMONT, CA: Health at Scale is a startup that, with masterminds who possess both engineering and medical proficiency, wants to bring machine learning (ML) to healthcare treatment plans and generate outcomes with better results and less aftercare. The company has announced a $16 million Series A. Optum, to develop a precision delivery so that they can match patients to the right treatments, by the right providers, at the right time.
Today, when people look at treatment alternatives, they might search for particular surgeons or hospitals, or the insurance coverage, but they typically lack the data to make informed decisions—an alarming factor that causes concern across the healthcare system. Therefore, the company believes that the use of ML will help it generate better results.
The plan is to make treatment decisions more data-driven. Health at Scale has claimed that it possesses and information about patients with a given condition, their doctors, and the treatment facility. By going through the patient’s individual treatment needs and medical history, the company believes that it can do a better job of matching that person to the best doctor and hospital for the job.
From Health at Scale’s perspective, it is a win-win situation since it provides the best guidance that has the interest of the patient at heart. Even from the provider’s perspective, the lower complication rates lead to better outcomes that eventually lower the total cost of care in the long term.
The Health at Scale solution is popular among large hospital systems and insurer customers. Studies on the outcome of using ML models and software revealed extensive improvements. As a result, the company plans to utilize the funding to develop its sales and marketing further to bring the solution to a diverse customer base.
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