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Technology: Neurocritical Care Meets Precision Medicine
When patients are in a hospital’s neurocritical care unit, the host of bedside devices used to monitor them, such as mechanical ventilators and intracranial pressure monitors, together produce more than 250 data points at any given time.
Some devices record the data, but the information is usually only accessible for doctors and nurses to review for a limited number of hours while the patient is being monitored. Once a patient leaves the unit, most of the data are lost.
Jose Suarez, director of the Neurosciences Critical Care Division, and his colleagues are working to use that data to improve patient outcomes. They are capturing deidentified data from hundreds of patients to develop an algorithm that recognizes patterns in patients who experience worsening in neurological function. The team will also develop a separate algorithm that predicts which patients will require intensive care as opposed to less observation in a nonintensive care unit.
“This is precision medicine for the neurocritical care unit,” says Suarez. “Automated, early detection of crises precursors can help doctors intervene to prevent secondary brain injuries.”
Last July, Suarez began using a data-gathering platform to continuously collect all of this real-time information in the neurocritical care unit. Between 7 and 10 terabytes of data will be stored annually on servers at Johns Hopkins’ Mount Washington data centers. Suarez and research associate Peter Dziedzic, director of the Center of mHealth and Innovations, will then use these data to build the algorithms.
The team expects the algorithms will improve not only patient outcomes but also patient flow and lessen length of hospital stays. Testing is planned for 2019; in the meantime, Suarez is working to identify additional funding sources.