Predicting Pressure Injuries with Machine Learning, EHR Data

Fueled by EHR data, machine learning tools have shown potential in improving several areas of care delivery, including sepsis prediction, chronic disease management, and cancer detection. As providers increasingly experience financial pressure to ensure patient safety, more organizations are seeking to use big data analytics tools to predict and prevent hospital-acquired conditions and potentially deadly infections. Hospital-acquired pressure injuries are one area where researchers are applying these advanced technologies. Pressure injuries are prevalent among patients in intensive care units (ICUs), occurring in eight to ten percent of critical care patients. These injuries are also associated with longer hospital stays, more patient suffering, and increased healthcare costs.