- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT02683447
Ageing and Acute Care Physicians' Performance
Impact of Acute Care Physician's Age on Crisis Management Performance and Learning After Simulation-based Education
Study Overview
Detailed Description
The proportion of older acute care physicians (ACP), emergency, critical care & anesthesia, has been steadily increasing. Ageing is associated with physiological changes, which in turn can influence a physician's clinical abilities and decision-making. The litigation and physician disciplinary data suggests that incidents involving all physicians are likely to occur later in practice, with degree of injury identified in the claims being of greater severity. However research, investigating how age-related physiological changes affect clinical performance and patient safety, is lacking.
CRM skills are essential skills within acute care specialties, and are vital for patient safety. CRM encompasses technical skills, as well as a rapid and organized approach to non-technical, cognitive skills such as decision-making, task management, situational awareness and team management. High-fidelity full body mannequin simulation-based education is effective for learning CRM, including transfer of skills from the simulated setting to the clinical setting and improving patient outcome. However, there is a gap in the literature on whether physicians' age influences baseline CRM performance and also learning from simulation-based education.
Although the effectiveness of high-fidelity simulation-based education has been studied extensively in junior learner populations (students, residents, fellows), there are a limited number of studies investigating its effectiveness in teaching CRM in the ageing physician population. In fact, a recent systematic review looking at the role of simulation in continuing medical education (CME) in ACPs supported that there is limited evidence supporting improved learning. Despite not knowing whether simulation is the correct tool in an ageing population, it is being recommended as a training, regulation and assessment tool for practicing physicians.
Objectives:
The goals of this study are to:
- Investigate whether ageing has a correlation with baseline CRM skills of ACPs using simulated crisis scenarios and
- Assess whether ageing influences learning from high fidelity simulation.
Study Type
Enrollment (Actual)
Contacts and Locations
Study Locations
-
-
Ontario
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Ottawa, Ontario, Canada, K1H 8L6
- University of Ottawa
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Toronto, Ontario, Canada, M4N3M5
- Sunnybrook Health Sciences Centre
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Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Child
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Emergency physicians
- Critical care physicians
- Anesthesiologists
- minimum 5 years of practice post-residency
Exclusion Criteria:
- Post-call day of participation
Study Plan
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
|---|---|
|
CRM Simulation
Each participant will manage a PEA arrest scenario (pre-test) and then be debriefed on their CRM skills by a trained facilitator for 20 minutes.
They will then manage another crisis scenario (PEA arrest with a different inciting event) as an immediate post-test.
Three months afterwards participants will return to manage a third PEA arrest scenario, which will serve as a retention post-test.
|
Each participant will manage a PEA arrest scenario (pre-test) and then be debriefed on their CRM skills by a trained facilitator for 20 minutes.
They will then manage another crisis scenario (PEA arrest with a different inciting event) as an immediate post-test.
Three months afterwards participants will return to manage a third PEA arrest scenario, which will serve as a retention post-test.
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
CRM Performance During First Sim Scenario Assessed by Ottawa Global Rating Scale (GRS)
Time Frame: After managing first simulation scenario - Day 1
|
Ottawa GRS score correlated with chronological age.
The Ottawa GRS assesses non-technical CRM skills on a 7-point scale (minimum 1, maximum 7), with higher scores indicating better performance.
|
After managing first simulation scenario - Day 1
|
|
CRM Performance During First Sim Scenario Assessed by ACLS Checklist
Time Frame: After managing first simulation scenario - Day 1
|
ACLS (Advanced Cardiac Life Support) score will be correlated with chronological age.
Items on the checklist were separated into two components: 1) the ACLS correct score (minimum score 0, maximum score 30), where higher scores indicate better performance, and 2) the ACLS risk score (minimum score 0, maximum score 17) where higher scores indicate worse performance.
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After managing first simulation scenario - Day 1
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Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Learning From High-fidelity Simulation Education Assessed by Ottawa Global Rating Scale
Time Frame: After managing second simulation scenario - Day 1
|
Ottawa GRS score will be compared to score in first scenario to look for improvement.
The Ottawa GRS assesses non-technical CRM skills on a 7-point scale (minimum 1, maximum 7), with higher scores indicating better performance.
The mean difference in GRS score between pre-test (scenario 1) and immediate post-test (scenario 2) is reported.
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After managing second simulation scenario - Day 1
|
|
Learning From High-fidelity Simulation Education Assessed by ACLS Checklist
Time Frame: After managing second simulation scenario - Day 1
|
ACLS (Advanced Cardiac Life Support) score will be compared to score in first scenario to look for improvement.
Items on the checklist were separated into two components: 1) the ACLS correct score (minimum score 0, maximum score 30), where higher scores indicate better performance, and 2) the ACLS risk score (minimum score 0, maximum score 17) where higher scores indicate worse performance.
The mean difference in ACLS score between pre-test (scenario 1) and immediate post-test (scenario 2) is reported.
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After managing second simulation scenario - Day 1
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Other Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Retention of Learning From Simulation as Assessed by Ottawa Global Rating Scale
Time Frame: 3 months after completing first two scenarios - Day 90
|
Ottawa GRS score will be compared to score in second scenario on Day 1 to look for improvement.
The Ottawa GRS assesses non-technical CRM skills on a 7-point scale (minimum 1, maximum 7), with higher scores indicating better performance.
The mean difference in GRS score between immediate post-test (scenario 2) and retention post-test (scenario 3) is reported.
|
3 months after completing first two scenarios - Day 90
|
|
Retention of Learning From Simulation as Assessed by ACLS Checklist
Time Frame: 3 months after completing first two scenarios - Day 90
|
ACLS (Advanced Cardiac Life Support) score will be compared to score in second scenario on Day 1 to look for improvement.
Items on the checklist were separated into two components: 1) the ACLS correct score (minimum score 0, maximum score 30), where higher scores indicate better performance, and 2) the ACLS risk score (minimum score 0, maximum score 17) where higher scores indicate worse performance.
The mean difference in ACLS score between immediate post-test (scenario 2) and retention post-test (scenario 3) is reported.
|
3 months after completing first two scenarios - Day 90
|
Collaborators and Investigators
Investigators
- Principal Investigator: Sylvain Boet, MD, MEd, PhD, University of Ottawa
- Principal Investigator: Fahad Alam, MD, FRCPC, Sunnybrook Health Sciences Centre
Publications and helpful links
General Publications
- Duclos A, Peix JL, Colin C, Kraimps JL, Menegaux F, Pattou F, Sebag F, Touzet S, Bourdy S, Voirin N, Lifante JC; CATHY Study Group. Influence of experience on performance of individual surgeons in thyroid surgery: prospective cross sectional multicentre study. BMJ. 2012 Jan 10;344:d8041. doi: 10.1136/bmj.d8041.
- Khanduja PK, Bould MD, Naik VN, Hladkowicz E, Boet S. The role of simulation in continuing medical education for acute care physicians: a systematic review. Crit Care Med. 2015 Jan;43(1):186-93. doi: 10.1097/CCM.0000000000000672.
- Katz JD. Issues of concern for the aging anesthesiologist. Anesth Analg. 2001 Jun;92(6):1487-92. doi: 10.1097/00000539-200106000-00027. No abstract available.
- Baxter AD, Boet S, Reid D, Skidmore G. The aging anesthesiologist: a narrative review and suggested strategies. Can J Anaesth. 2014 Sep;61(9):865-75. doi: 10.1007/s12630-014-0194-x. Epub 2014 Jul 2.
- Baird M, Daugherty L, Kumar KB, Arifkhanova A. Regional and Gender Differences and Trends in the Anesthesiologist Workforce. Anesthesiology. 2015 Nov;123(5):997-1012. doi: 10.1097/ALN.0000000000000834.
- Siu LW, Boet S, Borges BC, Bruppacher HR, LeBlanc V, Naik VN, Riem N, Chandra DB, Joo HS. High-fidelity simulation demonstrates the influence of anesthesiologists' age and years from residency on emergency cricothyroidotomy skills. Anesth Analg. 2010 Oct;111(4):955-60. doi: 10.1213/ANE.0b013e3181ee7f4f. Epub 2010 Aug 24.
- Daugherty L, Fonseca R, Kumar KB, Michaud PC. An Analysis of the Labor Markets for Anesthesiology. Rand Health Q. 2011 Sep 1;1(3):18. eCollection 2011 Fall.
- Duke, E. (2006). The Critical Care Workforce: A Study of the Supply and Demand for Critical Care Physicians : Report to Congress (p. 36). U.S. Department of Health & Human Sciences.
- Durning SJ, Artino AR, Holmboe E, Beckman TJ, van der Vleuten C, Schuwirth L. Aging and cognitive performance: challenges and implications for physicians practicing in the 21st century. J Contin Educ Health Prof. 2010 Summer;30(3):153-60. doi: 10.1002/chp.20075.
- Eva KW. The aging physician: changes in cognitive processing and their impact on medical practice. Acad Med. 2002 Oct;77(10 Suppl):S1-6. doi: 10.1097/00001888-200210001-00002. No abstract available.
- Trunkey DD, Botney R. Assessing competency: a tale of two professions. J Am Coll Surg. 2001 Mar;192(3):385-95. doi: 10.1016/s1072-7515(01)00770-0. No abstract available.
- Turnbull J, Carbotte R, Hanna E, Norman G, Cunnington J, Ferguson B, Kaigas T. Cognitive difficulty in physicians. Acad Med. 2000 Feb;75(2):177-81. doi: 10.1097/00001888-200002000-00018.
- Norman G, Young M, Brooks L. Non-analytical models of clinical reasoning: the role of experience. Med Educ. 2007 Dec;41(12):1140-5. doi: 10.1111/j.1365-2923.2007.02914.x. Epub 2007 Nov 13.
- Tessler MJ, Shrier I, Steele RJ. Association between anesthesiologist age and litigation. Anesthesiology. 2012 Mar;116(3):574-9. doi: 10.1097/ALN.0b013e3182475ebf.
- Alam A, Khan J, Liu J, Klemensberg J, Griesman J, Bell CM. Characteristics and rates of disciplinary findings amongst anesthesiologists by professional colleges in Canada. Can J Anaesth. 2013 Oct;60(10):1013-9. doi: 10.1007/s12630-013-0006-8. Epub 2013 Jul 30.
- Khaliq AA, Dimassi H, Huang CY, Narine L, Smego RA Jr. Disciplinary action against physicians: who is likely to get disciplined? Am J Med. 2005 Jul;118(7):773-7. doi: 10.1016/j.amjmed.2005.01.051.
- Boet S, Bould MD, Fung L, Qosa H, Perrier L, Tavares W, Reeves S, Tricco AC. Transfer of learning and patient outcome in simulated crisis resource management: a systematic review. Can J Anaesth. 2014 Jun;61(6):571-82. doi: 10.1007/s12630-014-0143-8. Epub 2014 Mar 25.
- Marinopoulos SS, Dorman T, Ratanawongsa N, Wilson LM, Ashar BH, Magaziner JL, Miller RG, Thomas PA, Prokopowicz GP, Qayyum R, Bass EB. Effectiveness of continuing medical education. Evid Rep Technol Assess (Full Rep). 2007 Jan;(149):1-69.
- Steadman RH. Improving on reality: can simulation facilitate practice change? Anesthesiology. 2010 Apr;112(4):775-6. doi: 10.1097/ALN.0b013e3181d3e337. No abstract available.
- Curtis MT, DiazGranados D, Feldman M. Judicious use of simulation technology in continuing medical education. J Contin Educ Health Prof. 2012 Fall;32(4):255-60. doi: 10.1002/chp.21153.
- Savoldelli GL, Naik VN, Hamstra SJ, Morgan PJ. Barriers to use of simulation-based education. Can J Anaesth. 2005 Nov;52(9):944-50. doi: 10.1007/BF03022056.
- Davis DA, Mazmanian PE, Fordis M, Van Harrison R, Thorpe KE, Perrier L. Accuracy of physician self-assessment compared with observed measures of competence: a systematic review. JAMA. 2006 Sep 6;296(9):1094-102. doi: 10.1001/jama.296.9.1094.
- Kim J, Neilipovitz D, Cardinal P, Chiu M, Clinch J. A pilot study using high-fidelity simulation to formally evaluate performance in the resuscitation of critically ill patients: The University of Ottawa Critical Care Medicine, High-Fidelity Simulation, and Crisis Resource Management I Study. Crit Care Med. 2006 Aug;34(8):2167-74. doi: 10.1097/01.CCM.0000229877.45125.CC.
- McEvoy MD, Smalley JC, Nietert PJ, Field LC, Furse CM, Blenko JW, Cobb BG, Walters JL, Pendarvis A, Dalal NS, Schaefer JJ 3rd. Validation of a detailed scoring checklist for use during advanced cardiac life support certification. Simul Healthc. 2012 Aug;7(4):222-35. doi: 10.1097/SIH.0b013e3182590b07.
- Alam F, LeBlanc VR, Baxter A, Tarshis J, Piquette D, Gu Y, Filipowska C, Krywenky A, Kester-Greene N, Cardinal P, Au S, Lam S, Boet S, Clinical Trials Group PA. Does the age of acute care physicians impact their (1) crisis management performance and (2) learning after simulation-based education? A protocol for a multicentre prospective cohort study in Toronto and Ottawa, Canada. BMJ Open. 2018 Apr 21;8(4):e020940. doi: 10.1136/bmjopen-2017-020940. Erratum In: BMJ Open. 2018 Jun 30;8(6):bmjopen-2017-020940corr1. doi: 10.1136/bmjopen-2017-020940corr1.
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Actual)
Study Completion (Actual)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Estimated)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Other Study ID Numbers
- 140-2015
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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