FDA approves clinical platform that predicts patient deterioration
Surveillance system uses a predictive algorithm that risk stratifies hospital patients based on their vital signs.
The Food and Drug Administration has approved a clinical monitoring platform that alerts hospital staff in near real time of a patient’s deteriorating condition using a predictive algorithm.
The WAVE Clinical Platform from Excel Medical acts as an early warning system that automatically calculates the risk of patient deterioration about six hours before the patient actually worsens, enabling clinicians to take corrective action before it’s too late to intervene.
Also See: App identifies patients needing advanced heart failure therapies
According to Mary Baum, chief strategy officer for Excel Medical, WAVE is designed to eliminate unexpected deaths in U.S. hospitals which take the lives of more than 400,000 Americans each year and is the country’s third-leading cause of death.
“Rapid response teams in hospitals need an accurate measure of what’s going on with patients and whether they are going in the wrong direction,” contends Baum. The patient monitoring system sends alerts to clinicians via their mobile devices, hospital workstations, and through electronic health records, letting them know when a patient is at risk.
“It’s not just a physician tool. It’s not just a nursing tool. It’s a team tool, so all of the staff involved in that patient’s care are notified and there’s an escalation policy that’s put in place,” she observes.
The “always-on” surveillance platform tracks patient vital signs, “risk stratifying patients who are most vulnerable” and assigning them a number between one and five, says Baum, who notes that WAVE is the first FDA-cleared patient deterioration predictive algorithm that which is targeted at acute care hospitals.
“Five vital signs are correlated, so it’s not just when the blood pressure or heart rate drops—it’s truly an algorithm,” according to Baum.
She points to a study by the University of Pittsburgh Medical Center in which the algorithm—called the Visensia Safety Index—in which UPMC’s control group reported six unexpected deaths while its trial group reported zero deaths.
Baum adds that Excel Medical has other predictive algorithms that are currently under development, including one for pediatric patients. “There will be a whole series—we have a bunch more coming,” she concludes.
The WAVE Clinical Platform from Excel Medical acts as an early warning system that automatically calculates the risk of patient deterioration about six hours before the patient actually worsens, enabling clinicians to take corrective action before it’s too late to intervene.
Also See: App identifies patients needing advanced heart failure therapiesAccording to Mary Baum, chief strategy officer for Excel Medical, WAVE is designed to eliminate unexpected deaths in U.S. hospitals which take the lives of more than 400,000 Americans each year and is the country’s third-leading cause of death.
“Rapid response teams in hospitals need an accurate measure of what’s going on with patients and whether they are going in the wrong direction,” contends Baum. The patient monitoring system sends alerts to clinicians via their mobile devices, hospital workstations, and through electronic health records, letting them know when a patient is at risk.
“It’s not just a physician tool. It’s not just a nursing tool. It’s a team tool, so all of the staff involved in that patient’s care are notified and there’s an escalation policy that’s put in place,” she observes.
The “always-on” surveillance platform tracks patient vital signs, “risk stratifying patients who are most vulnerable” and assigning them a number between one and five, says Baum, who notes that WAVE is the first FDA-cleared patient deterioration predictive algorithm that which is targeted at acute care hospitals.
“Five vital signs are correlated, so it’s not just when the blood pressure or heart rate drops—it’s truly an algorithm,” according to Baum.
She points to a study by the University of Pittsburgh Medical Center in which the algorithm—called the Visensia Safety Index—in which UPMC’s control group reported six unexpected deaths while its trial group reported zero deaths.
Baum adds that Excel Medical has other predictive algorithms that are currently under development, including one for pediatric patients. “There will be a whole series—we have a bunch more coming,” she concludes.
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