Predictive technology helps to identify heart failure patients

New predictive modeling technology could help hospitals improve care and lower costs by identifying high-risk congestive heart failure (CHF) patients before they are admitted.

Developed by healthcare informatics vendor Humedica, the technology pulls data from a patient's electronic health record, according to an announcement. "We are leveraging the power of millions of patient experiences in our data warehouse [to] identify CHF patients who would likely end up hospitalized without prior medical intervention," Humedica Chief Medical Officer Paul Bleicher said in a statement.

The technology currently is being deployed by the Indianapolis-based Community Physician Network.

Other predictive healthcare technology unveiled this week included an interactive tool that can estimate the life expectancy of older adults. The technology was created by University of California San Francisco researchers to help doctors estimate how much time their patients have left before recommending specific treatments. Also announced this week, a DNA sequencer that can map a human genome within 24 hours for $1,000. 

The latter technology, which was on display at both the Consumer Electronics Show in Las Vegas and the J.P. Morgan Healthcare Conference in San Francisco, created quite a buzz in the healthcare industry, as DNA sequencing eventually could lead to more personalized treatments for patients.

A study published in the Annals of Internal Medicine last May determined that personalized treatment protocols can be developed using EHR technology. The study compared the effectiveness and costs of individualized guidelines with the national consensus protocols for treating hypertension.

To learn more:
- here's the Humedica announcement

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