Humedica, a Boston, Mass.-based clinical analytics company, announced the launch of a new predictive analytic model that will help providers identify patients at high-risk for a Congestive Heart Failure (CHF) hospitalization. This model will aim to help providers look for high-risk CHF patients before they have been hospitalized. It could help reduce hospital admissions among the sickest, most costly patients in America says Humedica.
Developed with clinical data pulled directly from the electronic medical record (EMR), the Humedica system runs off claims-based risk predictors.
CHF is among the most costly and most preventable cause of inpatient admissions in the US, according to Humeidca. Heart failure affects nearly five million patients nationwide with 500,000 new cases diagnosed annually. Despite well-known and highly effective interventions, 40 percent of all Medicare patients with CHF are readmitted within 90 days.
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