Abstract

BackgroundOpioids can cause respiratory depression, which could lead to patient harm. The project site noted a gap in identifying and monitoring postsurgical thoracic patients at risk for opioid-induced respiratory depression (OIRD), so an evidence-based solution was sought. AimsThe purpose of this quality improvement project was to determine if translating the research by Khanna et al. (2020) on implementing the prediction of opioid-induced respiratory depression in patients monitored by capnography (PRODIGY) risk prediction tool would affect rapid response team (RRT) activation among postsurgical thoracic patients in a cardiovascular and thoracic care unit (CVTCU) at John Muir Medical Center, Concord Campus over four weeks. MethodsThe four-week quantitative quasi-experimental project had a total sample size of 29 participants. Pulse oximetry was used to identify OIRD in the comparison group (n = 12). The implementation group consisted of patients identified as at-risk for OIRD by the PRODIGY risk prediction tool and were monitored with pulse oximetry and capnography (n = 17). ResultsA χ2 analysis showed χ2 (1, n = 29) = .73, p = .393 for activation of the RRT using the PRODIGY risk prediction tool, which was not statistically significant. However, clinical significance was supported by a 5.9% increase in RRT activations. ConclusionBased on the results, implementing the PRODIGY risk prediction tool and capnography monitoring on at-risk patients may affect RRT activation in this population.

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