HealthcareDIVE – June 2, 2016
A medical algorithm capable of real-time monitoring of electronic health records can predict whether a hospital patient will deteriorate hours in advance and alert physicians about their decline.
The algorithm, developed at the University of Chicago Medical Center and marketed by Quant HC, tracks 28 variables like respiratory rate, age, kidney function and length of hospital stay and provides a timeline of the patient’s risk.
It detects about 88% of patients who are at risk of deteriorating from organ failure, cardiac arrest, sepsis and other life-threatening conditions within a median 33-hour timeframe, improving clinical decision-making and resource management, says Rick Halton, co-founder and chief marketing officer of Apervita, an online marketplace and platform for more than 1,000 health algorithms, including Quant HC.
“This has a huge potential impact on reducing length of stay in hospital, because you’re catching that patient really early” instead of after their condition has deteriorated and they’ve been moved to intensive care, he adds. “It’s a lot more cost to the hospital, and clearly the patient’s life is at risk.”
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