- http://orcid.org/0000-0002-8092-4427Daniel Rusiecki1,
- Melanie Walker2,
- Stuart L Douglas3,
- Sharleen Hoffe3,
- Timothy Chaplin3
- 1 School of Medicine, Queen’s University, Kingston, Canada
- 2 School of Medicine, Emergency Medicine, Public Health Sciences, Queen’s University, Kingston, Canada
- 3 Emergency Medicine, Queen’s University, Kingston, Canada
- Correspondence to Timothy Chaplin, Department of Emergency Medicine, Queen’s University, Kingston, Canada, 76 Stuart Street, Kingston, ON K7L2V7, Canada;
Objectives To describe the association between participant profession and the number and type of latent safety threats (LSTs) identified during in situ simulation (ISS). Secondary objectives were to describe the association between both (a) participants’ years of experience and LST identification and (b) type of scenario and number of identified LSTs.
Methods Emergency staff physicians (MDs), registered nurses (RNs) and respiratory therapists (RTs) participated in ISS sessions in the emergency department (ED) of a tertiary care teaching hospital. Adult and paediatric scenarios were designed to be high-acuity, low-occurrence resuscitation cases. Simulations were 10 min in duration. A written survey was administered to participants immediately postsimulation, collecting demographic data and perceived LSTs. Survey data was collated and LSTs were grouped using a previously described framework.
Results Thirteen simulation sessions were completed from July to November 2018, with 59 participants (12 MDs, 41 RNs, 6 RTs). Twenty-four unique LSTs were identified from survey data. RNs identified a median of 2 (IQR 1, 2.5) LSTs, significantly more than RTs (0.5 (IQR 0, 1.25), p=0.04). Within respective professions, MDs and RTs most commonly identified equipment issues, and RNs most commonly identified medication issues. Participants with ≤10 years of experience identified a median of 2 (IQR 1, 3) LSTs versus 1 (IQR 1, 2) LST in those with >10 years of experience (p=0.06). Adult and paediatric patient scenarios were associated with the identification of a median of 4 (IQR 3.0, 4.0) and 5 LSTs (IQR 3.5, 6.5), respectively (p=0.15).
Conclusions Inclusion of a multidisciplinary team is important during ISS in order to gain a breadth of perspectives for the identification of LSTs. In our study, participants with ≤10 years of experience and simulations with paediatric scenarios were associated with a higher number of identified LSTs; however, the difference was not statistically significant.
- In Situ Simulation
- Interdisciplinary Training
- Emergency Medicine
- Interprofessional Education
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Twitter Daniel Rusiecki @daniel_rusiecki.
Acknowledgements In memory of Jane Reid. Your diligent note taking and data entry made this project possible. We would like to thank Drs Nicole Rocca and Heather White for their contribution in developing scenarios and facilitating in situ simulation sessions. We would like to thank Mr Loren Fleming for operating the patient simulator during simulation and Ms Wilma Hopman for her assistance with the data analysis.
Contributors DR was involved in the study design, survey creation, data collection, data analysis, statistical analysis and manuscript writing. MW was involved in study design, survey creation, data analysis and manuscript revisions. SLD was involved in data analysis and manuscript revision. SH was involved in study design, survey creation and development of simulation scenarios. TC was involved in study design, survey creation, statistical analysis, manuscript revision, development of simulation scenarios, liaising with ED administration and simulation centre staff to facilitate in situ simulation sessions.
Funding DR was awarded the Clinical Simulation Summer Studentship from the Clinical Simulation Centre (CSC), Queen's University. The CSC provided simulation equipment (patient simulators) and staff to operate the equipment. They had no involvement in the research study.
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
Data availability statement Data including the list of specific LSTs found in our institution and raw survey transcription can be found at https://bit.ly/2IMaVtO.
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