A Patient’s Own Vital Signs – Using RWD for Pain Care Planning

Earlier this year (and quietly, we might add) a group of Northwestern University engineers published a study that focused on how to leverage data hiding in plain sight for pain care.  The scientists developed and applied artificial intelligence (AI), or machine-learning, algorithms to physiological data.  They used respiratory rate, blood pressure, heart rate, body temperature and oxygen levels from patients with chronic pain from sickle cell disease. Their approach outperformed baseline models to estimate subjective pain levels.  It also detected changes in pain – atypical pain fluctuations.