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Web-Based Versus High-Fidelity Simulation Training for Certified Registered Nurse Anesthetists in the Management of High Risk/Low Occurrence Anesthesia Events

dc.contributor.authorKimemia, Judy
dc.contributor.advisorMotz, Jane
dc.date.accessioned2017-08-23T18:56:27Z
dc.date.availableNO_RESTRICTIONen_US
dc.date.available2017-08-23T18:56:27Z
dc.date.issued2017-08-04
dc.date.submitted2017
dc.identifier.urihttps://hdl.handle.net/2027.42/138011
dc.description.abstractPurpose: The purpose of this project was to compare web-based to high-fidelity simulation training in the management of high risk/low occurrence anesthesia related events, to enhance knowledge acquisition for Certified Registered Nurse Anesthetists (CRNAs). This project was designed to answer the question: Is web-based training as effective as high-fidelity manikin based simulation training, in assisting CRNAs to maintain knowledge for the management of high risk/low occurrence anesthesia related events over a training period of four weeks in a level one trauma facility? Methods: This was a quantitative study. Institutional Review Board (IRB) approval was obtained from Penn State Hershey Medical Center (PSHMC) and the University of Michigan-Flint (U of M-Flint), before study participants were enrolled. A total of 32 participants were enrolled in the study. Participants were randomly assigned to either group I (web-based training) or group II (high-fidelity simulation training). All enrolled participants completed a written demographic survey and pre-test. After their respective training sessions, participants completed a post knowledge test. Quantitative data analysis was used to process the data. Results: Average baseline pre-training percentage correct score for the web-based group was 80.67%, with a post-training average score of 87% reflecting an increase of 6.33% p value 0.13 not significantly different from zero. In the high-fidelity simulation group, average baseline pre-training score was 82.33%; average post-training score was 83.66%, p value 0.70 reflecting a non-significant increase of 1.33%. Comparison of average percentage correct improvement between the training groups (6.3 web vs. 1.3 sim) p value 0.34, revealed a non-significant difference in the knowledge gained between the web-based and high-fidelity simulation groups. Conclusion: Maintaining skills for the management of high risk/low occurrence anesthesia related events can be difficult due to the infrequency of these events occurring during a practitioner’s career. It is important that CRNAs maintain the knowledge and skills to manage these rare events. High fidelity simulation has been shown to be an effective training technique in anesthesia. Some institutions may not have the advantage of offering simulation to employees, due to budget constraints, or the availability of lab time and instructors. Web-based training is easily accessible, and can be conveniently available to learners. It may accommodate diverse learning styles, and offer an opportunity for CRNAs to train at their own pace, to enhance learning. This study showed, web-based training is as effective as high-fidelity simulation for training CRNAs for the management of high risk/ low occurrence anesthesia related events at Penn State Hershey Medical Center. Data Sources: Medscape, PubMED, CINAHL, and Google scholar. Keywords: web-based learning, high-fidelity simulation learning, high and low risk anesthesia events.en_US
dc.language.isoen_USen_US
dc.subjecthigh-fidelity simulation learningen_US
dc.subjectCertified Registered Nurse Anesthetistsen_US
dc.subjecthigh risk low occurrence anesthesia related eventsen_US
dc.subjectweb-based learningen_US
dc.subject.otherAnesthesiaen_US
dc.subject.othereducational evaluationen_US
dc.subject.otherhealth educationen_US
dc.titleWeb-Based Versus High-Fidelity Simulation Training for Certified Registered Nurse Anesthetists in the Management of High Risk/Low Occurrence Anesthesia Eventsen_US
dc.typeThesisen_US
dc.description.thesisdegreenameDoctor of Anesthesia Practice (DAP)en_US
dc.description.thesisdegreedisciplineAnesthesia Practiceen_US
dc.description.thesisdegreegrantorUniversity of Michigan-Flinten_US
dc.contributor.committeememberStump, Lawrence
dc.identifier.uniqname11353120en_US
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/138011/1/Kimemia2017.pdf
dc.description.filedescriptionDescription of Kimemia2017.pdf : Thesis
dc.owningcollnameDissertations and Theses (Ph.D. and Master's)


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