Singularity-Launched Startup Sentrian Raises $12 Million In Funding


San Diego-based digital health startup Sentrian announces that it has raised a $4 million seed round and a concurrent $8 million Series A round, led by Reed Elsevier Ventures, Frost Data Capital, and TELUS Ventures. The company traces its roots back to a Singularity University executive seminar that founder Jack Kreindler, MD, attended, discussing the need for new disruptive technologies that could address the cost of unnecessary hospitalizations. Kreindler came to the conference with some experience in this area, as the CEO of the Center for Health and Human Performance in London, UK. At CHHP, Kreindler built a private health network that pairs clinical specialists with preventative practitioners to reduce unnecessary hospitalizations as much as possible for his patients.

Now, two years after setting out to build the company, Sentrian launched on the main stage at Singularity during its Exponential Medicine Conference. CEO and co-founder Dean Sawyer said during the launch, "Millions of unnecessary hospitalizations that endanger patients and cost tens of billions of dollars every year could be avoided if we could spot deterioration in patients’ health earlier using remote patient monitoring analytics. Our platform leverages the exponential growth in biosensors and machine-learning and is intended to detect the subtle signs that warn of an impending problem before the patient becomes acute and requires hospitalization."  

While the description sounds complex, the technology behind the ideas are easy to understand. Sentrian’s platform evaluates claims data from a client’s total patient population to identify high risk patients: those that frequent the emergency department, and those with conditions that make them likely to need acute care services periodically. Once these patients are identified, Sentrian outfits them with remote patient monitoring devices that will wirelessly transmit biometric data back to the Sentrian platform. This high risk patient population then returns home and the Sentrian platform begins to consume data from their monitoring devices in real time. The next part is where Sentrian becomes truly innovative. The company hired a team of machine learning experts to build algorithms that allow the Sentrian platform to learn each patient’s normal physiological ranges, accounting for individual diseases and expected disease progression over time. At this point, the platform will use these patient-specific ranges as a basis to begin sending alerts to clinicians whenever their condition trends outside of an acceptable range for them. If a clinician receives an alert that they believe was unwarranted, this information is fed back into the system and the platform then reconciles that information with the patient’s profile so that false positives decrease over time and the system does not waste a clinicians valuable time. The result, Sentrian hopes, is a population health platform that is highly sensitive and highly specific because its alerts are tailored for each of the individuals that make up the population.

Sentrian is currently piloting its platform with a large insurer and expects to publish initial results during 2015.

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