SAVVI's client had a staff scaling and training problem. SAVVI’s client has hundreds of healthcare providers who need to actively assess thousands of patients weekly. Each assessment includes a set of interventions, based on a collection of statistical and categorical health care data. As new nurses are trained, they must also learn the patient patterns to determine the correct interventions to implement. It takes time to onboard new nurses and teach them these critical patterns of patient success.
SAVVI AI helps the client scale their team faster, but offering rank orders on the best interventions to recommend to their nurses and using “fleet learning” across the entire nursing team. These recommended interventions are highlighted directly in the patient management portal. As the seasoned nurses evaluate and confirm the decisioning, it further trains the predictive model to be even more accurate for future recommendations. This form of fleet learning, learning from the existing subject matter experts, helps train new nurses faster as it gives recommendations in specific situations.
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