Surgical patients often require opioid pain prescriptions after discharge from the hospital to control their pain during recovery, but healthcare providers may overestimate the number of pills the patient needs - contributing to pill diversion and opioid misuse. We are leveraging machine learning and causal inference techniques to develop accurate opioid prescribing guidelines for each type of major surgery, to predict which patients need customized prescribing, to increase adoption of guideline-informed prescribing by healthcare providers, and to statistically adapt guidelines and patient-oriented models developed at one institution to the patient and procedure mix at other institutions.
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