• Ryan Howard, Joceline Vu, Jay Lee, Chad Brummett, Michael Englesbe, and Jennifer Waljee.
• Department of Surgery, University of Michigan, Ann Arbor, MI.
• Ann. Surg. 2020 Jan 1; 271 (1): 869386-93.

ObjectiveOpioid prescriptions after surgery are effective for pain management but have been a significant contributor to the current opioid epidemic. Our objective is to review pragmatic approaches to develop and implement evidence-based guidelines based on a learning health system model.Summary Background DataDuring the last 2 years there has been a preponderance of data demonstrating that opioids are overprescribed after surgery. This contributes to a number of adverse outcomes, including diversion of leftover pills in the community and rising rates of opioid use disorder.MethodsWe conducted a MEDLINE/PubMed review of published examples and reviewed our institutional experience in developing and implementing evidence-based postoperative prescribing recommendations.ResultsThirty studies have described collecting data regarding opioid prescribing and patient-reported use in a cohort of 13,591 patients. Three studies describe successful implementation of opioid prescribing recommendations based on patient-reported opioid use. These settings utilized learning health system principles to establish a cycle of quality improvement based on data generated from routine practice. Key components of this pathway were collecting patient-reported outcomes, identifying key stakeholders, and continual assessment. These pathways were rapidly adopted and resulted in a 37% to 63% reduction in prescribing without increasing requests for refills or patient-reported pain scores.ConclusionA pathway for creating evidence-based opioid-prescribing recommendations can be utilized in diverse practice environments and can lead to significantly decreased opioid prescribing without adversely affecting patient outcomes.

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