Maintenance of clinical competencies with in situ nursing simulation.
* Simulation combined with debriefing improves critical care nurses' clinical knowledge and technical proficiency.
* Low-fidelity in situ simulations can identify errors, knowledge gaps and latent safety threats.
* In situ simulations do not impede patient care and are appreciated by critical care nurses.
Critical care nurses must master a wide variety of clinical competencies. Clinical competencies can be defined as a combination of clinical knowledge (job-related knowledge, interpretation of clinical situations and the need for an intervention) and technical proficiency (ability to operate and troubleshoot equipment) needed to provide patient care.
High-acuity low-occurrence (HALO) competencies are rarely performed (less than four times per year), limiting opportunities for nurses to maintain clinical competencies. If these competencies are performed by unprepared nurses under considerable psychological, physiological, and time pressures, errors will occur (Galy et al., 2012).
Simulation education enhances competencies of healthcare workers (Abe et al., 2013) by replacing real experiences with guided interactive experiences (Gaba, 2007). These interactive experiences can be low-fidelity (less realistic), high-fidelity (more realistic), onsite (in situ) or off site (simulation centres).
Low-fidelity in situ simulations (LFISS) can provide nurses with HALO experiences to integrate into their cognitive framework (Lisko & O'Dell, 2010). Unfortunately, there is limited literature discussing the use of simulation-based learning in maintaining clinical competencies for practising nurses (Lucas, 2014). This study addresses that gap.
The primary objective of this study was to determine if LFISS can improve critical care nurses' HALO competencies (clinical knowledge and technical proficiency). The secondary objective was to determine if LFISS would reveal latent safety threats.
Study participants were part-time and full-time registered nurses from two critical care units at a large university affiliated hospital in Halifax, Nova Scotia. Site 1 was a 12-bed medical, surgical, trauma and neurosurgical unit (MSNICU) and Site 2 was a nine-bed medical and surgical unit (MSICU). Convenience sampling of on-duty critical care nurses was utilized and simulations were conducted by a unit resource nurse twice per week (1000h to 2200h) for a seven-week period. Participation in the simulations was voluntary.
On each unit, a simulation room was created and stocked to emulate actual patient care rooms. All simulation equipment and supplies were clearly marked as 'simulation only' to ensure patient safety. Two low-fidelity manikins (ALS Skills Trainer; Laerdal, Sweden) were used to simulate patients.
Two unit resource nurses, with previous simulation and debriefing experience, developed brief (30- to 40-minute), focused (one HALO competency per simulation) simulations grounded in experiential learning theory (Fewster-Thuente & Batteson, 2018). Each simulation was followed by a debriefing, giving nurses the opportunity to reflect on their experiences. Four HALO competencies were identified after consultation with nursing staff: prone patient positioning (PPP), massive transfusion protocol (MTP), Advanced Cardiac Life Support (ACLS) Pulseless Algorithm and cardiac pacing (transcutaneous and transvenous).
The objective of the PPP simulation was for the participants to understand the indications for prone positioning and to safely prone an intubated manikin with a central line and multiple intravenous infusions. During the MTP simulations, nurses had to safely administer simulated blood products with the rapid infuser (Belmont Rapid Infuser; Belmont Instruments, USA) while adhering to institutional policy and procedures. For the ACLS Pulseless Algorithm simulations, nurses had to demonstrate high-quality CPR; operate the defibrillator (LifePac20e; PhysioControl, USA); identify ventricular fibrillation (VF), pulseless ventricular tachycardia (pVT) and pulseless electrical activity (PEA), while administering simulated code medications. For the cardiac pacing simulation, nurses had to identify the loss of transvenous pacing (TVP) electrical/mechanical capture and successfully transition to transcutaneous pacing (TCP) with a LifePac20e.
A quasi experimental, pre-test and post-test design was used to test the primary objective. Prior to each simulation, nurses completed a confidential questionnaire using a five-point interval scale to rank their clinical knowledge and technical proficiency. Following each simulation, participants ranked their post-test clinical knowledge and technical proficiency. A paired sample (pre-test and post-test intervention) t-test was performed to ascertain the statistical significance of the intervention. Data analysis was completed using Microsoft Excel (2010).
Debriefing sessions were conducted after each simulation.
In total, 93 (79%) of the 118 full-time and part-time nurses participated in the study. Sixty-four nurses (63%) participated in two or more simulations (Table 1). Study results indicate that LFISS are an effective educational tool for critical care nurses to maintain HALO clinical competencies. Multiple latent safety threats were identified and corrected during this study.
Nurses who participated in HALO simulations demonstrated a statistically significant improvement in clinical knowledge and technical proficiency (Table 2). Prone patient positioning simulation participants showed both improved clinical knowledge (n = 55, p < 0.01) and technical proficiency (n = 55, p < 0.01). Massive transfusion protocol simulations participants showed improved clinical knowledge (n = 56, p < 0.01) and technical proficiency (n = 56, p < 0.01). Advanced Cardiac Life Support Pulseless Algorithm simulations participants showed improved clinical knowledge (n = 35, p < 0.01) and technical proficiency (n = 35, p < 0.01). In the cardiac pacing (TVP and TCP) simulations, participants showed improved capabilities related to this competency (n = 28, p < 0.01).
High-acuity low-occurrence simulations provide nurses with an experiential learning opportunity to reinforce strengths and reveal deficiencies. Experiential learning occurs during the experience, reflection afterwards and during debriefing. This cycle enables nurses to develop new ways of thinking and new behaviours (Fewster-Thuente & Batteson, 2018; Lisko & O'Dell, 2010).
Psychological, physiological, and time pressures increase errors (Galy et al., 2012). Low-fidelity in situ simulations provided nurses with the opportunity to develop strategies to deal with these stressors, thereby reducing errors. This enhanced performance may have a secondary benefit. Research suggests that feelings of inadequacy can contribute to burnout (Lewis et al., 2015) particularly among young nurses (<35 years of age) new to critical care (Chuang et al., 2016). Potentially, ongoing simulations may reduce feelings of inadequacy and subsequent burnout, especially among young nurses new to critical care, but more research on this is required.
Improved clinical knowledge and technical proficiency are finite and will decay over time. Therefore, ongoing simulations would prevent this decay. Research suggests that simulations should be conducted at least every six months (Abe et al., 2013; Singleton et al., 2018). Multiple latent safety threats were identified during the simulations (Table 3).
During an MTP simulation session, the Belmont Rapid Infuser dual-lumen extension tubing was inadequately primed with intravenous fluids resulting in an air embolism. The root cause of this adverse event was miscommunication among multiple nurses operating the rapid infuser. Training now emphasizes one nurse being responsible for operation of the rapid infuser and the dual-lumen extension lines were removed from service.
During the ACLS simulations nurses experienced difficulties in identifying the reversible causes of a PEA arrest; differentiating between shockable (VF, pVT), non-shockable rhythms (PEA); and operation of the LifePac20e. On three occasions, the incorrect initial dose of Amiodarone was administered and on two occasions, PEA was defibrillated. Multiple ACLS courses are now offered throughout the year for the MSNICU and the MSICU nurses.
This study has several limitations. First, it is limited to one university-affiliated medical centre. Second, the simulations were not strictly scripted, which resulted in some variance from simulation to simulation. Third, nurses self-reported their pretest and post-test clinical knowledge and technical proficiency, which could be subject to bias.
Simulation combined with debriefing improves nurses' clinical knowledge and technical proficiency while identifying latent safety threats. The LFISS does not impede patient care and are appreciated by critical care nurses. The should be conducted every six months to prevent clinical knowledge and technical proficiency performance decay.
David Hersey, BA, BScN, RN, Critical Care Nurse, Halifax Infirmary, Nova Scotia Health Authority, 1799 Robie Street, Halifax, NS B3K 4N1. Email: email@example.com
Elinor Kelly, BA, BScN, RN, Nova Scotia Health Authority
Jamie Hersey BN, ACP, RN, Emergency Health Services Nova Scotia LifeFlight
Nova Scotia Health Authority Nursing Strategy and Nurse-Led Workplace Improvement Initiative; Critical Care Nursing Leadership Team: Lesley Bishop, Patricia Daley, David Hersey, Cynthia Isenor, Elinor Kelly, Christine Price, Karen Webb-Anderson, and Debbie White; Emily Hart for editing and research assistance.
Abe, Y., Kawahara, C., Yamashina, A., & Tsuboi, R. (2013). Repeated scenario simulation to improve competency in critical care: A new approach for nursing education. American Journal of Critical Care, 22(1), 33-40. https://doi. org/10.4037/ajcc2013229
Chuang, C. H., Tseng, P. C., Lin, C. Y., Lin, K. H., & Chen, Y. Y. (2016). Burnout in the intensive care unit professionals: A systematic review. Medicine, 95(50), e5629. https://doi.org/10.1097/ MD.0000000000005629
Dreifuerst, K. (2012). Using debriefing for meaningful learning to foster development of clinical reasoning in simulation. Journal of Nursing Education, 51(6), 326-333. https://doi. org/10.3928/01484834-20120409-02
Fewster-Thuente, L., & Batteson, T. J. (2018). Kolb's experiential learning theory as a theoretical underpinning for interprofessional education. Journal of Allied Health, 47(1), 3-8.
Gaba, D. (2007). The future vision of simulation in healthcare. Simulation in Healthcare: The Journal of the Society for Simulation in Healthcare, 2(2), 126-135. https://doi.org/10.1097/01. SIH.0000258411.38212.32
Galy, E., Cariou, M., & Melan, C. (2012). What is the relationship between mental workload factors and cognitive load types? International Journal of Psychophysiology: Official Journal of the International Organization of Psychophysiology, 83(3), 269275. https://doi.org/10.1016Aj. ijpsycho.2011.09.023
Lewis, E. J., Baernholdt, M. B., Yan, G., & Guterbock, T G. (2015). Relationship of adverse events and support to RN burnout. Journal of Nursing Care Quality, 30(2), 144-152. https://doi.org/10.1097/ NCQ.0000000000000084
Lisko, S., & O'Dell, V. (2010). Integration of theory and practice: Experiential learning theory and nursing education. Nursing Education Perspectives, 31(2), 105-108
Lucas, A. N. (2014). Promoting continuing competence and confidence in nurses through high-fidelity simulation-based learning. The Journal of Continuing Education in Nursing, 45(8), 360-5. https://doi. org/10.3928/00220124-20140716-02
Singleton, M. N., Allen, K. F., Li, Z., McNerney, K., Naber, U. H., & Braga, M. S. (2018). Rolling-refresher simulation improves performance and retention of paediatric intensive care unit nurse code cart management. BMJ Simulation & Technology Enhanced Learning, 4(2), 77-82. https://doi.org/10.1136/bmjstel-2017-000243
By David Hersey, BA, BScN, RN, Elinor Kelly, BA, BScN, RN, Jamie Hersey BN, ACP, RN
Hersey, D., Kelly, E., & Hersey, J. (2020). Maintenance of clinical competencies with in situ nursing simulation. The Canadian Journal of Critical Care Nursing, 31(3), 9-11.
Table 1. Nurse Participation in Simulations n Percentage of Nursing Staff No Simulations 25 21.1% One Simulation 29 24.5% Two Simulations 35 29.6% Three Simulations 21 17.1% Four Simulations 7 5.9% Five Simulations 1 0.84%
Table 2. Low-fidelity in situ High Acuity Low Occurrence Simulations Simulation n (SD) p-value Prone Patient Positioning Pre-Test Clinical Knowledge 55 4.11(0.76) Post-Test Clinical Knowledge 55 4.87(0.34) <0.01 Pre-Test Technical Proficiency 55 3.80(0.36) Post-test Technical Proficiency 55 4.80(0.36) <0.01 Massive Transfusion Protocol Pre-Test Clinical Knowledge 56 4.28(0.80) Post-Test Clinical Knowledge 56 4.91(0.29) <0.01 Pre-Test Technical Proficiency 56 3.21(1.13) Post-Test Technical Proficiency 56 4.82(0.43) <0.01 ACLS Pulseless Algorithm Pre-Test Clinical Knowledge 34 3.71(0.76) Post-Test Clinical Knowledge 34 4.59(0.50) <0.01 Pre-Test Code Blue 34 3.68(0.84) Post-Test Code Blue 34 4.24(0.65) <0.01 Cardiac Pacing Pre-Test Transvenous Pacing 34 2.76(1.17) Post-Test Transvenous Pacing 34 4.07(0.06) <0.01 Pre-Test Transcutaneous Pacing 34 3.21(1.13) Post-Test Transcutaneous Pacing 34 4.32(0.05) <0.01
Table 3. Observed Latent Safety Threats During Low-Fidelity In Situ Simulations Simulation n Massive Transfusion Protocol Difficulty programing Belmont 3 Failure to plug in Belmont 1 Air embolism 1 Advanced Cardiac Life Support Incorrect pad placement 1 Defibrillation of PEA 2 Incorrect Amiodarone dose 3 Symptomatic Bradycardia Delay connecting EKG and pads 2 Difficulty locating pace button 4 Difficulty adjusting rate and output 3 Prone Patient Positioning No safety threats identified
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|Author:||Hersey, David; Kelly, Elinor; Hersey, Jamie|
|Publication:||The Canadian Journal of Critical Care Nursing|
|Date:||Dec 22, 2020|
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