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LOS ANGELES -- Big data and sophisticated analytics can help deliver personalized care through a telemedicine discipline known as remote patient monitoring, according to healthcare analytics expert Martin Kohn, M.D.
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Kohn formerly led IBM's healthcare projects, including deploying the Watson super-computing system for personalized care and payment reform. He is now chief medical scientist for telemedicine startup Sentrian, which bills itself as a "remote patient intelligence" developer.
In this podcast, recorded at the American Telemedicine Association's annual meeting and trade show, Kohn told SearchHealthIT that sophisticated data analytics can pinpoint the most acutely and chronically ill patients in population health programs.
With this knowledge, clinicians and caregivers can target these patients with personalized treatment plans designed to prevent hospitalization and re-admission by predicting acute medical events such as congestive heart failure, according to Kohn.
One way Sentrian and other telemedicine companies are doing this is with remote patient monitoring: hooking up patients to relatively simple medical devices such as heart rate sensors, blood pressure gauges and pulse oximeters.
Clinicians then track the measurements over time and analytics programs sift through the data to identify the most at-risk patients.
By keeping more patients out of the hospital, caregivers are starting to help reduce the cost of healthcare while providing better service, Kohn said.
This strategy also meshes with the healthcare industry trend toward value-based care, in which providers are paid for healthier outcomes, rather than a fee-for-service model, Kohn added.
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