A hospital stay usually involves being attached to a host of medical devices. But how useful is all that data, really? The FDA recently approved a new method of analyzing data to reduce preventable hospital deaths, which are estimated to number 400,000 yearly in the U.S. Studies have indicated that preventable deaths in hospitals are the third-leading cause of death in the U.S., behind heart disease and cancer.
The predictive algorithm approved by the FDA is used in the WAVE Clinical Platform, a monitoring system for hospital patients. WAVE is a product of Excel Medical, a Florida-based manufacturer of medical devices. The algorithm is the first of its kind to be recognized by the FDA. The platform analyzes patient data from electronic medical records (EMRs) and from monitoring systems for heart rate and blood pressure. This creates an early-warning system that can notify clinicians in a variety of ways, including through smartphone and tablet apps. According to a company press release, WAVE calculates risk, giving an at-a-glance early warning of patient deterioration up to six hours in advance of when clinicians might otherwise notice, while there is still time to prevent further deterioration. The company’s announcement cited a study at the University of Pittsburgh Medical Center that incorporated the algorithm, in which a trial group reported zero unexpected deaths, compared to six deaths in the control group.
Other predictive algorithms are under development for use with the WAVE platform, according to a company spokesman. We are entering an era where calculations based on algorithms are receiving the same sort of clearance from the FDA as chemical medications, giving a whole new dimension to the term “digital health.”
FDA clearance is very meaningful when you consider the new FDA guidance on claims for patient surveillance and for predictive algorithms.