Student Registered Nurse Anesthetists:  The Impact of Structured High Fidelity Simulation on Anesthesia Ready Time

Michele Marie Ballister, DNP, CRNA, APRN

Michele Marie Ballister, DNP, CRNA, APRN Medical University of South Carolina

Abstract

Introduction: Student registered nurse anesthetists (SRNAs) at a large academic medical center are limited in clinical training experiences owing to the subjective perception by local anesthesia department administrators of decreased oper-ating room efficiency with SRNA involvement. The purpose of this project was to utilize structured high-fidelity simula-tion (HFS) to increase basic skill proficiency in SRNAs and evaluate the impact of the simulation within the first month of clinical training.
Methods: Utilizing the Iowa Model of Evidence-Based Practice to Promote Quality Care, a 5-week structured HFS program was inserted into the nurse anesthesia curriculum before the SRNAs’ first clinical rotation. The program pro-moted basic anesthesia skill proficiency through the assimilation of previously taught and tested technical skills. In-room times and anesthesia ready times of all SRNA cases involving general anesthesia with the placement of an endotrache-al tube during September 2012 and 2013 were compiled by use of retrospective chart review. Using the calculation of elapsed time between in-room time and anesthesia ready time (IRTART), the clinical performance of 2 consecutive classes of SRNAs was compared, one with structured HFS training and one without.
Results: The mean IRTART for both groups was similar at 20 minutes with a standard deviation of 10 minutes. The IRTARTs from both groups were within the institution’s operative norm.
Conclusion: Structured HFS did not impact the anesthesia ready time of new-to-practice SRNAs. However, the in-formation collected during implementation of HFS and data analysis can be used to develop future avenues to improve current processes for structured HFS and clinical training opportunities.

References

1. Harder BN. Use of simulation in teaching and learning in health sciences: a systematic review. J Nurs Educ. 2010;49(1):23-28. https://doi.org/10.3928/01484834-20090828-08.
2. Gore T, Van Gele P, Ravert P, Mabire CA. 2010 survey of the INACSL membership about simulation use. Clin Simul Nurs. 2012;8(4):e125-e133. https://doi.org/10.1016/j.ecns.2012.01.002.
3. Cannon-Diehl MR, Rugari SM, Jones TS. High-fidelity simulation for continuing education in nurse anesthesia. AANA J. 2012;80(3):191-196.
4. Council on Accreditation of Nurse Anesthesia Programs. Accreditation Standards, Policies and Procedures, and Guidelines Website. Standards for Accreditation of Nurse Anesthesia Programs. Practice Doctorate. http://home.coa.us.com/accreditation/Documents/Standards%20for%20Accreditation%20of%20Nurse%20Anesthesia%20Programs%20-%20 Practice%20Doctorate,%20rev%20June%202016.pdf. Accessed July 7, 2017.
5. Zafar SU, Khan FA, Khan M. Standardization of anesthesia ready time and reasons of delay in induction of anesthesia. J Pak Med Assoc. 2006;56(3):112-115.
6. Dracup K. Nursing education: recommendations for the future. In: Institute of Medicine (US) Committee on the Robert Wood Johnson Foundation Initiative on the Future of Nursing. The Future of Nursing: Leading Change, Advancing Health. Washington, DC: National Academies Press (US); 2011:516-525.
7. Nehring WM, Ellis WE, Lashley FR. Human patient simulators in nursing education: an overview. Simul Gaming. 2001;32(2):194-204. https://doi.org/10.1177/104687810103200207.
8 Detty-Oswaks JS. The Use of Simulated Clinical Experiences to Improve Competency in the Novice Anesthesia Provider [dissertation]. Memphis: University of Tennessee; 2002. Retrieved from Proquest Dissertations and Thesis database (UMI No. 3067791).
9. Schwid HA, Rooke GA, Carline J, et al; Anesthesia Simulator Research Consortium. Evaluation of anesthesia residents using mannequin-based simulation. Anesthesiology. 2002;97(6):1434-1444. https://doi.org/10.1097/00000542-200212000-00015.
10. Issenberg SB, Mcgghie WC, Petrusa ER, Gordon DL, Ross RJ. Features and uses of high-fidelity medical simulations that lead to effective learning: a BEME systematic review. Med Teach. 2005;27:1,10-28. https://doi.org/10.1080/10421590500046924.
11. Cantrell MA. The importance of debriefing in clinical simulations. Clin Simul Nurs. 2008;4(2):e19-e23. https://doi.org/10.1016/j.ecns.2008.06.006.
12. Meyer MN, Connors H, Hou Q, Gajewski B. The effect of simulation on clinical performance. Simul Healthc. 2011;6(5):269-277. https://doi.org/10.1097/SIH.0b013e318223a048.
13. Titler MG, Keliber C, Steelman V, et al. The Iowa model of evidence-based practice to promote quality care. Crit Care Nurs Clin North Am. 2001;13:497-509.
14. Maheshwari K, You J, Cummings KC III, et al. Attempted development of a tool to predict anesthesia preparation time from patient-related and procedure-related characteristics. Anesth Analg. 2017;125(2):580-592. https://doi.org/10.1213/ANE.0000000000002018.