Perioperative Pain Management Algorithm for Chronic Pain Patients
MetadataShow full item record
PublisherThe University of Arizona.
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
AbstractPurpose. The purpose of this quality improvement (QI) project was to develop an algorithm based on evidence-based practice to manage perioperative pain in chronic pain patients. The goal was to educate and improve anesthesia provider’s baseline knowledge on managing perioperative pain in the chronic pain population.Background. It can be difficult to manage acute perioperative pain in chronic pain patients due to physiologic changes that occur with chronic exposure to opioids such as opioid tolerance, opioid-induced hyperalgesia, and physical dependence (Coluzzi et al., 2017). A study by Gan, Habib, Miller, White, and Apfelbaum (2014) found that more than 70% of patients who underwent surgery reported post-surgical pain as moderate to extreme. The necessity to control perioperative pain in chronic pain patients is of upmost importance due to increased risk of postoperative complication, prolong hospital stay, increased risk of infection, and increased healthcare cost related to uncontrolled postoperative pain. Methods. Lewin’s change theory (LCT) served as theoretical framework as it was used as a guide to influence provider knowledge with education on management of perioperative pain in chronic pain patients. Participants (n=13) included certified registered nurse anesthetists (CRNAs) at a level one trauma facility. A pretest and posttest survey was submitted to participants before and after an educational PowerPoint (PPT) presentation that included principal investigator’s (PI) developed perioperative acute pain management algorithm for chronic pain patients. Results. A Wilcoxon signed-rank test was utilized to compare overall pretest and posttest scores and there was statistically significant improvement (Z = -3.06, p = 0.002). Most participant’s test scores improved 92% (n=12) with the exception of one participant who scored 100% in pretest therefore could not improve. Conclusion. There was a knowledge gap among CRNAs at this Level 1 trauma facility in managing acute pain in chronic pain patients. After educating providers about this topic, the posttest questionnaire demonstrated that there was an increase in knowledge among anesthesia care providers. Additionally, the posttest questionnaire indicated that CRNAs would change their practice. There is a high probability that participations will be utilizing developed perioperative pain management algorithm to manage acute pain in chronic pain patients.
Degree ProgramGraduate College