Reducing Opioid Use Following Posterior Spinal Fusion Procedures: A Pilot Project

<p>Importance: Opioid misuse and mortality remain a prevalent problem in the United States and there is a high rate of chronic opioid-use after spinal fusions. Current guidelines recommend the optimization of non-opioid analgesics as a primary pain control strategy with opioids acting as a secondary agent. Objective: To pilot an analgesic decision tree (ADT) featuring non-opioid analgesics to reduce postoperative pain, opioid consumption, and the incidence of adverse events during the first 48 hours after patients undergo a posterior spinal fusion. Methods: A literature review of opioid-sparing analgesics was conducted and a protocol developed as an interdisciplinary collaboration. The ADT was piloted in an intensive care unit for 10 weeks. Pain control, opioid consumption, and the incidence of adverse events were compared to historical controls from a previous 10-week period. Results: In total, 12 historical control charts were reviewed and 17 patients enrolled in the ADT group. There was no significant difference in groups. The ADT did not affect NRS scores, CPOT scores, MME consumption, or ORAE in a statistically significant way. Power analyses indicate that a minimum of 9894 patients are required to detect significance. Conclusions: The ADT may be non-inferior in pain control and opioid consumption, but future testing is required. Further pilots should control confounding influences to optimize power analyses. Subsequent projects should utilize these power analyses to determine the ADT’s influence on pain control, opioid consumption, and adverse event incidence.</p>

Name thesis:degree_name

Doctor of Nursing Practice (DNP)

Level thesis:degree_level

Open Access Thesis

Discipline thesis:degree_discipline

Yale University School of Nursing

Year

2025

Author dc:creator

• Cornett, Kevin Matthew

Contributors dc:contributor

• Shelli Feder

Repository record dc:identifier

https://elischolar.library.yale.edu/ysndt/1184

OAI identifier oai:identifier

oai:elischolar.library.yale.edu:ysndt-1183