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Ann Surg. 2019 Aug 30. doi: 10.1097/SLA.0000000000003434. [Epub ahead of print]

A Pathway for Developing Postoperative Opioid Prescribing Best Practices.

Howard R1,2, Vu J1,2, Lee J1,2, Brummett C3,2, Englesbe M1,4,2, Waljee J1,2.

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Department of Surgery, University of Michigan, Ann Arbor, MI.
Michigan Opioid Prescribing Engagement Network, Ann Arbor, MI.
Department of Anesthesiology, University of Michigan, Ann Arbor, MI.
Michigan Surgical Quality Collaborative, Ann Arbor, MI.



Opioid 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.


During 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.


We conducted a MEDLINE/PubMed review of published examples and reviewed our institutional experience in developing and implementing evidence-based postoperative prescribing recommendations.


Thirty 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.


A 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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