Clinical Decision Support to Reduce Opioid Prescribing at Discharge for Inpatients Undergoing Surgery (LESS Study): An Interrupted Time Series Analysis

Megan L Rolfzen; Kristin Daniel; Karan Shah; Craig G Reha; Edward J Mascha; Matt Muellner; Mark C Bicket; Chad M Brummett; Jennifer F Waljee; Grace E Majeres; Stephan G Frangakis; Amy S Bohnert; Karsten Bartels

doi:10.1097/ALN.0000000000006174

Clinical Decision Support to Reduce Opioid Prescribing at Discharge for Inpatients Undergoing Surgery (LESS Study): An Interrupted Time Series Analysis

Anesthesiology. 2026 Aug 4. doi: 10.1097/ALN.0000000000006174. Online ahead of print.

Authors

Affiliations

¹ Department of Anesthesiology and Department of Psychiatry, University of Michigan, Ann Arbor, Michigan.
² Department of Pharmaceutical and Nutritional Care, Nebraska Medicine, Omaha, Nebraska.
³ Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio.
⁴ Department of Anesthesiology, University of Nebraska Medical Center, Omaha, Nebraska.
⁵ Department of Anesthesiology, and Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, Michigan.
⁶ Division of Plastic and Reconstructive Surgery, Department of Surgery, Indiana University, Bloomington, Indiana.
⁷ Department of Anesthesiology, University of Michigan, Ann Arbor, Michigan.
⁸ Department of Anesthesiology, Institute for Healthcare Policy and Innovation, and Department of Psychiatry, Medical School, University of Michigan, Ann Arbor, Michigan; and Center for Clinical Management Research, VA Ann Arbor Heathcare System, Ann Arbor, Michigan.
⁹ Department of Anesthesiology, Institute for Healthcare Policy and Innovation, and Department of Psychiatry, Medical School, University of Michigan, Ann Arbor, Michigan.

PMID: 42166796
DOI: 10.1097/ALN.0000000000006174

Abstract

Background: Unnecessary opioid prescribing after surgery is wasteful and expands the reservoir for nonmedical use, thereby contributing to preventable morbidity and mortality. The authors used an interrupted time series design to evaluate whether implementing a systemwide clinical decision support intervention reduced opioid prescribing at discharge.

Methods: The authors included adult surgical patients hospitalized for at least 24 h who had not received any opioids in the 24 h before discharge, as prescriptions in this cohort are more likely to represent unnecessary opioid prescribing. The pre- and postintervention 2-yr periods were February 13, 2021, to February 12, 2023, and February 13, 2023, to February 12, 2025, respectively. The primary outcome was discharge oxycodone in morphine milligram equivalents (MME). Secondary outcomes included whether any opioids were prescribed, and if so, how much. Segmented regression models adjusted for confounders were used to assess the immediate and trend-level effects of the intervention.

Results: Analyzed data included 10,422 pre- and 11,795 postintervention discharges. Total oxycodone prescribed per discharge was 27.4 MME before intervention and 16.5 MME after intervention. Oxycodone MME prescribed at discharge was significantly lower after intervention, with a ratio of geometric means of 0.83 (95% CI, 0.76 to 0.90; one-tailed superiority, P < 0.001) for the level change but no difference in slopes ( P = 0.919). For secondary outcomes, 21% of discharges were prescribed any oxycodone before intervention versus 18% after intervention, with a relative risk of 0.87 (95% CI, 0.79 to 0.96) assessing the level change. For the discharges with a prescription, median MME [quartile 1, quartile 3] was lower after intervention than before (75 [38, 112] vs. 112 [75, 150]), with a ratio of geometric means of 0.70 (95% CI, 0.65 to 0.75).

Conclusions: An automated real-time clinical decision support tool resulted in clinically significant reductions in oxycodone prescribed at discharge. Incorporation of similarly simple decision support tools in electronic health record systems may significantly reduce unnecessary opioid prescriptions at scale and better align with guideline-concordant care.