Dec 15, 2022
Dr. Jason Cohen, Senior Director of Clinical Solutions at Qventus, is addressing the problems that hospitals face regarding discharging patients. Much of care planning starts during hospitalization or at the last minute, so patients and caregivers are often left confused about the next appropriate care environment. Qventus is deploying AI to build a model with hundreds of different data points to predict highly-individualized discharge plans. This benefits patients, hospitals, and care teams by keeping track of progress, identifying bottlenecks, and making necessary adjustments to the care plan.
Jason elaborates, "We look at patients, for example, who get an early discharge plan, which we define as being an estimated date of discharge and a disposition where they're likely to go. Those patients that have their care team aligned around that early plan by the second midnight in the hospital experience have significantly fewer excess days in the hospital. They're more likely to leave on time and get to their next most appropriate care environment, whether that's a skilled facility, rehab, home with home help, et cetera. And then on the other side of that, again, is that tension with the dynamically changing nature of that patient's health, and things can change from day to day."
"Our solution has multiple different components, which hopefully we'll get into, but one of the core parts is our AI machine learning model that is able to help care teams align on that early discharge plan as soon as possible. And in the case of our models, the majority of patients, we're able to populate that plan directly into the EHR so that there's transparency across all those teams after the first midnight in the hospital."
@Qventus #Qventus #HospitalDischargePlanning #HospitalDischarge #Hospitals #AI #BigData