Abstract

Background: Gan et al. (2014) reports in the past 5 years 86% of surgical patients’ experienced immediate post-operative pain, and 75% of those reported pain severities of moderate to extreme in the immediate post-operative pain. Uncontrolled pain leads to multiple health problems such as pneumonia, chronic pain syndrome, and delayed healing. Post-operative pain is best treated with multimodal management. Pain algorithms allow nurses to implement non-pharmacologic techniques and escalate use of medications in a safe manner while improving pain management.

Framework: The Comfort Theory (CT) by Katherine Kocalba will be used to guide this project. Kocalba’s CT identifies three types of comfort: 1) relief, 2) ease, and 3) transcendence. Relief of pain allows the patient to relax, rest, and recover.

Methods: HCAHPS scores will be collected from January 2018 until three months after the implementation of the algorithm. The 40 registered nurses (RNs) on MS 5 will receive an online evite including the cover/consent letter, demographic survey and “Knowledge and Attitudes Survey Regarding Pain” (KASRP) Ferrell and McCaffery, 2014). Using a semi structured script nurses will be educated regarding implementing an evidence-based algorithm for post-operative pain management, attending brief education classes, and completing three online pain courses.

Results: Unfortunately, there was poor response from the nurses and we are unable to analyze data. Out of 41 eligible RNs 10 returned the pre survey, two returned the first post survey, and no responses were recorded from the second post survey. It is unknown if RNs found the algorithm to help them in communication of pain management and treatment with the patient.

Implications of Intervention: Implementing a post-operative pain algorithm that involves multimodal pain management will improve patients’ pain. Use of the algorithm assists nurses in communicating effectively with the patients about their pain and pain management.

Publication Date

10-25-2019

Presented At:

14th Annual BHSF Research Conference

Content Type

Poster

Additional Authors:

Additional authors and institutional affiliations

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