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1.  Heart rate, anxiety and performance of residents during a simulated critical clinical encounter: a pilot study 
BMC Medical Education  2014;14:153.
High-fidelity patient simulation has been praised for its ability to recreate lifelike training conditions. The degree to which high fidelity simulation elicits acute emotional and physiologic stress among participants – and the influence of acute stress on clinical performance in the simulation setting – remain areas of active exploration. We examined the relationship between residents’ self-reported anxiety and a proxy of physiologic stress (heart rate) as well as their clinical performance in a simulation exam using a validated assessment of non-technical skills, the Ottawa Crisis Resource Management Global Rating Scale (Ottawa GRS).
This was a prospective observational cohort study of emergency medicine residents at a single academic center. Participants managed a simulated clinical encounter. Anxiety was assessed using a pre- and post-simulation survey, and continuous cardiac monitoring was performed on each participant during the scenario. Performance in the simulation scenario was graded by faculty raters using a critical actions checklist and the Ottawa GRS instrument.
Data collection occurred during the 2011 academic year. Of 40 eligible residents, 34 were included in the analysis. The median baseline heart rate for participants was 70 beats per minute (IQR: 62 – 78). During the simulation, the median maximum heart rate was 140 beats per minute (IQR: 137 – 151). The median minimum heart rate during simulation was 81 beats per minute (IQR: 72 – 92), and mean heart rate was 117 beats per minute (95% CI: 111 – 123). Pre- and post-simulation anxiety scores were equal (mean 3.3, IQR: 3 to 4). The minimum and maximum Overall Ottawa GRS scores were 2.33 and 6.67, respectively. The median Overall score was 5.63 (IQR: 5.0 to 6.0). Of the candidate predictors of Overall performance in a multivariate logistic regression model, only PGY status showed statistical significance (P = 0.02).
Simulation is associated with physiologic stress, and heart rate elevation alone correlates poorly with both perceived stress and performance. Non-technical performance in the simulation setting may be more closely tied to one’s level of clinical experience than to perceived or actual stress.
PMCID: PMC4131479  PMID: 25064689
2.  Exploring intensive care nurses’ team performance in a simulation-based emergency situation, − expert raters’ assessments versus self-assessments: an explorative study 
BMC Nursing  2014;13(1):47.
Effective teamwork has proven to be crucial for providing safe care. The performance of emergencies in general and cardiac arrest situations in particular, has been criticized for primarily focusing on the individual’s technical skills and too little on the teams’ performance of non-technical skills. The aim of the study was to explore intensive care nurses’ team performance in a simulation-based emergency situation by using expert raters’ assessments and nurses’ self-assessments in relation to different intensive care specialties.
The study used an explorative design based on laboratory high-fidelity simulation. Fifty-three registered nurses, who were allocated into 11 teams representing two intensive care specialties, participated in a videotaped simulation-based cardiac arrest setting. The expert raters used the Ottawa Crisis Resource Management Global Rating Scale and the first part of the Mayo High Performance Teamwork Scale to assess the teams’ performance. The registered nurses used the first part of the Mayo High Performance Teamwork Scale for their self-assessments, and the analyses used were Chi-square tests, Mann–Whitney U tests, Spearman’s rho and Intraclass Correlation Coefficient Type III.
The expert raters assessed the teams’ performance as either advanced novice or competent, with significant differences being found between the teams from different specialties. Significant differences were found between the expert raters’ assessments and the registered nurses’ self-assessments.
Teams of registered nurses representing specialties with coronary patients exhibit a higher competence in non-technical skills compared to team performance regarding a simulated cardiac arrest. The use of expert raters’ assessments and registered nurses’ self-assessments are useful in raising awareness of team performance with regard to patient safety.
Electronic supplementary material
The online version of this article (doi:10.1186/s12912-014-0047-5) contains supplementary material, which is available to authorized users.
PMCID: PMC4299298  PMID: 25606023
Assessment; Emergency; Intensive care; Non-technical skills; Nursing; Patient safety; Simulation-based training; Team performance
3.  Transfer of learning and patient outcome in simulated crisis resource management: a systematic review 
Canadian Journal of Anaesthesia  2014;61(6):571-582.
Simulation-based learning is increasingly used by healthcare professionals as a safe method to learn and practice non-technical skills, such as communication and leadership, required for effective crisis resource management (CRM). This systematic review was conducted to gain a better understanding of the impact of simulation-based CRM teaching on transfer of learning to the workplace and subsequent changes in patient outcomes.
Studies on CRM, crisis management, crew resource management, teamwork, and simulation published up to September 2012 were searched in MEDLINE®, EMBASE™, CINAHL, Cochrane Central Register of Controlled Trials, and ERIC. All studies that used simulation-based CRM teaching with outcomes measured at Kirkpatrick Level 3 (transfer of learning to the workplace) or 4 (patient outcome) were included. Studies measuring only learners’ reactions or simple learning (Kirkpatrick Level 1 or 2, respectively) were excluded. Two authors independently reviewed all identified titles and abstracts for eligibility.
Principal findings
Nine articles were identified as meeting the inclusion criteria. Four studies measured transfer of simulation-based CRM learning into the clinical setting (Kirkpatrick Level 3). In three of these studies, simulation-enhanced CRM training was found significantly more effective than no intervention or didactic teaching. Five studies measured patient outcomes (Kirkpatrick Level 4). Only one of these studies found that simulation-based CRM training made a clearly significant impact on patient mortality.
Based on a small number of studies, this systematic review found that CRM skills learned at the simulation centre are transferred to clinical settings, and the acquired CRM skills may translate to improved patient outcomes, including a decrease in mortality.
Electronic supplementary material
The online version of this article (doi:10.1007/s12630-014-0143-8) contains supplementary material, which is available to authorized users.
PMCID: PMC4028539  PMID: 24664414
4.  The simulated operating theatre: comprehensive training for surgical teams 
Quality & safety in health care  2004;13(Suppl 1):i27-i32.
Surgical excellence is traditionally defined in terms of technical performance, with little regard for the importance of interpersonal communication and leadership skills. Studies in the aviation industry have stressed the role of human factors in causing error and, in an attempt to reduce the occurrence of adverse events, led to the organisation of simulation based training scenarios. Similar strategies have recently been employed for the surgical team with the development of a simulated operating theatre project. This enables technical and non-technical performance of the surgeon and circulating staff to be assessed by experts situated in an adjacent control room, and provides an opportunity for constructive feedback. The scenarios have good face validity and junior surgeons can benefit from the process of learning new technical skills in a realistic environment. The effect of external influences such as distractions, new technology, or a crisis scenario can also be defined, with the ultimate aim of reducing the number of adverse events arising in the real operating room.
PMCID: PMC1765789  PMID: 15465952
5.  Emergency medicine resident crisis resource management ability: a simulation-based longitudinal study 
Medical Education Online  2014;19:10.3402/meo.v19.25771.
Simulation has been identified as a means of assessing resident physicians’ mastery of technical skills, but there is a lack of evidence for its utility in longitudinal assessments of residents’ non-technical clinical abilities. We evaluated the growth of crisis resource management (CRM) skills in the simulation setting using a validated tool, the Ottawa Crisis Resource Management Global Rating Scale (Ottawa GRS). We hypothesized that the Ottawa GRS would reflect progressive growth of CRM ability throughout residency.
Forty-five emergency medicine residents were tracked with annual simulation assessments between 2006 and 2011. We used mixed-methods repeated-measures regression analyses to evaluate elements of the Ottawa GRS by level of training to predict performance growth throughout a 3-year residency.
Ottawa GRS scores increased over time, and the domains of leadership, problem solving, and resource utilization, in particular, were predictive of overall performance. There was a significant gain in all Ottawa GRS components between postgraduate years 1 and 2, but no significant difference in GRS performance between years 2 and 3.
In summary, CRM skills are progressive abilities, and simulation is a useful modality for tracking their development. Modification of this tool may be needed to assess advanced learners’ gains in performance.
PMCID: PMC4262767  PMID: 25499769
simulation; assessment; crisis resource management
6.  Identifying and training non-technical skills for teams in acute medicine 
Quality & safety in health care  2004;13(Suppl 1):i80-i84.
The aviation domain provides a better analogy for the "temporary" teams that are found in acute medical specialities than industrial or military teamwork research based on established teams. Crew resource management (CRM) training, which emphasises portable skills (for whatever crew a pilot is rostered to on a given flight), has been recognised to have potential application in medicine, especially for teams in the operating theatre, intensive care unit, and emergency room. Drawing on research from aviation psychology that produced the behavioural marker system NOTECHS for rating European pilots' non-technical skills for teamwork on the flightdeck, this paper outlines the Anaesthetists Non-Technical Skills behavioural rating system for anaesthetists working in operating theatre teams. This taxonomy was used as the design basis for a training course, Crisis Avoidance Resource Management for Anaesthetists used to develop these skills, based in an operating theatre simulator. Further developments of this training programme for teams in emergency medicine are outlined.
PMCID: PMC1765790  PMID: 15465960
7.  Teamwork skills, shared mental models, and performance in simulated trauma teams: an independent group design 
Non-technical skills are seen as an important contributor to reducing adverse events and improving medical management in healthcare teams. Previous research on the effectiveness of teams has suggested that shared mental models facilitate coordination and team performance. The purpose of the study was to investigate whether demonstrated teamwork skills and behaviour indicating shared mental models would be associated with observed improved medical management in trauma team simulations.
Revised versions of the 'Anesthetists' Non-Technical Skills Behavioural marker system' and 'Anti-Air Teamwork Observation Measure' were field tested in moment-to-moment observation of 27 trauma team simulations in Norwegian hospitals. Independent subject matter experts rated medical management in the teams. An independent group design was used to explore differences in teamwork skills between higher-performing and lower-performing teams.
Specific teamwork skills and behavioural markers were associated with indicators of good team performance. Higher and lower-performing teams differed in information exchange, supporting behaviour and communication, with higher performing teams showing more effective information exchange and communication, and less supporting behaviours. Behavioural markers of shared mental models predicted effective medical management better than teamwork skills.
The present study replicates and extends previous research by providing new empirical evidence of the significance of specific teamwork skills and a shared mental model for the effective medical management of trauma teams. In addition, the study underlines the generic nature of teamwork skills by demonstrating their transferability from different clinical simulations like the anaesthesia environment to trauma care, as well as the potential usefulness of behavioural frequency analysis in future research on non-technical skills.
PMCID: PMC2939527  PMID: 20807420
8.  Is High Fidelity Simulation the Most Effective Method for the Development of Non-Technical Skills in Nursing? A Review of the Current Evidence 
The Open Nursing Journal  2012;6:82-89.
To review the literature on the use of simulation in the development of non-technical skills in nursing
The potential risks to patients associated with learning 'at the bedside' are becoming increasingly unacceptable, and the search for innovative education and training methods that do not expose the patient to preventable errors continues. All the evidence shows that a significant proportion of adverse events in health care is caused by problems relating to the application of the 'non-technical' skills of communication, teamwork, leadership and decision-making.
Simulation is positively associated with significantly improved interpersonal communication skills at patient handover, and it has also been clearly shown to improve team behaviours in a wide variety of clinical contexts and clinical personnel, associated with improved team performance in the management of crisis situations. It also enables the effective development of transferable, transformational leadership skills, and has also been demonstrated to improve students' critical thinking and clinical reasoning in complex care situations, and to aid in the development of students' self-efficacy and confidence in their own clinical abilities.
High fidelity simulation is able to provide participants with a learning environment in which to develop non-technical skills, that is safe and controlled so that the participants are able to make mistakes, correct those mistakes in real time and learn from them, without fear of compromising patient safety. Participants in simulation are also able to rehearse the clinical management of rare, complex or crisis situations in a valid representation of clinical practice, before practising on patients.
PMCID: PMC3415625  PMID: 22893783
Communication; decision-making; non-technical skills; nurse education; simulation; situation awareness; teamwork; team training; interprofessional.
9.  An innovative longitudinal curriculum to increase emergency medicine residents’ exposure to rarely encountered and technically challenging procedures 
Procedural skills have historically been taught at the bedside. In this study, we aimed to increase resident knowledge of uncommon emergency medical procedures to increase residents’ procedural skills in common and uncommon emergency medical procedures and to integrate cognitive training with hands-on procedural instruction using high- and low-fidelity simulation.
We developed 13 anatomically/physiologically-based procedure modules focusing on uncommon clinical procedures and/or those requiring higher levels of technical skills. A departmental expert directed each session with collaboration from colleagues in related subspecialties. Sessions were developed based on Manthey and Fitch’s stages of procedural competency including 1) knowledge acquisition, 2) experience/technical skill development, and 3) competency evaluation. We then distributed a brief, 10-question, online survey to our residents in order to solicit feedback regarding their perceptions of increased knowledge and ability in uncommon and common emergency medical procedures, and their perception of the effectiveness of integrated cognitive training with hands-on instruction through high- and low-fidelity simulation.
Fifty percent of our residents (11/22) responded to our survey. Responses indicated the procedure series helped with understanding of both uncommon (65% strongly agreed [SA], 35% agreed [A]) and common (55% SA, 45% A) emergency medicine procedures and increased residents’ ability to perform uncommon (55% SA, 45% A) and common (45% SA, 55% A) emergency medical procedures. In addition, survey results indicated that the residents were able to reach their goal numbers.
Based on survey results, the procedure series improved our residents’ perceived understanding of and perceived ability to perform uncommon and more technically challenging procedures. Further, results suggest that the use of a cognitive curriculum model as developed by Manthey and Fitch is adaptable and could be modified to fit the needs of other medical specialties.
PMCID: PMC4108255  PMID: 25083138
graduate medical education; emergency medical education; procedural competency; high-fidelity simulation
10.  A Multirater Instrument for the Assessment of Simulated Pediatric Crises 
Few validated instruments exist to measure pediatric code team skills. The goal of this study was to develop an instrument for the assessment of resuscitation competency and self-appraisal using multirater and gap analysis methodologies.
Multirater assessment with gap analysis is a robust methodology that enables the measurement of self-appraisal as well as competency, offering faculty the ability to provide enhanced feedback. The Team Performance during Simulated Crises Instrument (TPDSCI) was grounded in the Accreditation Council for Graduate Medical Education competencies. The instrument contains 5 competencies, each assessed by a series of descriptive rubrics. It was piloted during a series of simulation-based interdisciplinary pediatric crisis resource management education sessions. Course faculty assessed participants, who also did self-assessments. Internal consistency and interrater reliability were analyzed using Cronbach α and intraclass correlation (ICC) statistics. Gap analysis results were examined descriptively.
Cronbach α for the instrument was between 0.72 and 0.69. The overall ICC was 0.82. ICC values for the medical knowledge, clinical skills, communication skills, and systems-based practice were between 0.87 and 0.72. The ICC for the professionalism domain was 0.22. Further examination of the professionalism competency revealed a positive skew, 43 simulated sessions (98%) had significant gaps for at least one of the competencies, 38 sessions (86%) had gaps indicating self-overappraisal, and 15 sessions (34%) had gaps indicating self-underappraisal.
The TPDSCI possesses good measures of internal consistency and interrater reliability with respect to medical knowledge, clinical skills, communication skills, systems-based practice, and overall competence in the context of simulated interdisciplinary pediatric medical crises. Professionalism remains difficult to assess. These results provide an encouraging first step toward instrument validation. Gap analysis reveals disparities between faculty and self-assessments that indicate inadequate participant self-reflection. Identifying self-overappraisal can facilitate focused interventions.
PMCID: PMC3186273  PMID: 22379528
11.  Improving medical emergency team (MET) performance using a novel curriculum and a computerized human patient simulator 
Quality & safety in health care  2005;14(5):326-331.

Problem: Advance cardiac life support (ACLS) training does not address coordination of team resources to improve the ability of teams to deliver needed treatments reliably and rapidly. Our objective was to use a human simulation training educational environment to develop multidisciplinary team skills and improve medical emergency team (MET) performance. We report findings of a crisis team training course that is focused on organization.
Setting: Large center for human simulation training at a university affiliated tertiary care hospital.
Participants: Ten courses were delivered and 138 clinically experienced individuals were trained (69 critical care nurses, 48 physicians, and 21 respiratory therapists). All participants were ACLS trained and experienced in responding to cardiac arrest situations.
Course design: Each course had four components: (1) a web based presentation and pretest before the course; (2) a brief reinforcing didactic session on the day of the course; (3) three of five different simulated scenarios; each followed by (4) debriefing and analysis with the team. Three of five simulator scenarios were used; scenario selection and order was random. Trainees did not repeat any scenario or role during the training. Participants were video recorded to assist debriefing. Debriefing focused on reinforcing organizational aspects of team performance: assuming designated roles independently, completing goals (tasks) assigned to each role, and directed communication.
Measures for improvement: Participants graded their performance of specific organizational and treatment tasks within specified time intervals by consensus. Simulator "survival" depended on supporting oxygenation, ventilation, circulation within 60 seconds, and delivering the definitive treatment within 3 minutes.
Effects of change: Simulated survival (following predetermined criteria for death) increased from 0% to 89%. The initial team task completion rate was 10–45% and rose to 80–95% during the third session.
Lessons learnt: Training multidisciplinary teams to organize using simulation technology is feasible. This preliminary report warrants more detailed inquiry.
PMCID: PMC1744065  PMID: 16195564
12.  Crises in clinical care: an approach to management 
Quality & safety in health care  2005;14(3):156-163.

 A "crisis" in health care is "the point in the course of a disease at which a decisive change occurs, leading either to recovery or to death". The daunting challenges faced by clinicians when confronted with a crisis are illustrated by a tragic case in which a teenage boy died after a minor surgical procedure. Crises are challenging for reasons which include: presentation with non-specific signs or symptoms, interaction of complex factors, progressive evolution, new situations, "revenge effects", inadequate assistance, and time constraints. In crises, clinicians often experience anxiety- and overload-induced performance degradation, tend to use "frequency gambling", run out of "rules" and have to work from first principles, and are prone to "confirmation bias". The effective management of crises requires formal training, usually simulator-based, and ideally in the inter-professional groups who will need to function as a team. "COVER ABCD–A SWIFT CHECK" is a precompiled algorithm which can be applied quickly and effectively to facilitate a systematic and effective response to the wide range of potentially lethal problems which may occur suddenly in anaesthesia. A set of 25 articles describing additional precompiled responses collated into a manual for the management of any crisis under anaesthesia has been published electronically as companion papers to this article. This approach to crisis management should be applied to other areas of clinical medicine as well as anaesthesia.
PMCID: PMC1744000  PMID: 15933309
13.  The World – Socio-economically and politically: What you need to know 
The gravest challenge facing the USA and the nations of the world is the coming economic crisis of the world economies, if present policies are pursued. Few are aware or believe that this event could happen. The spread of centralized government control of the economies, the growth of the welfare state worldwide, the expenditures on entitlements beyond what any nation or even most states can afford, the cost of wars, the rapidly climbing debt of the USA and other countries and their inability to pay for these excessive expenses, the actions of many countries to print “fiat” (false) money to pay for their debts, the raising of taxes to pay for these debts, the rise in immigration to developed countries from the undeveloped world, the associated costs to their societies of this immigration, the promises made by politicians to get elected that cannot be fulfilled, and the desire of the public to have what they want, now, paid for by credit cards (debt), are all contributing to the coming economic crisis.
The unfunded promised benefits to the citizens of the USA in Medicare, Medicaid, Social Security, and pensions plus the USA debt amount to about $140 trillion. The total value of all the assets of all the people in the USA is $99 trillion dollars. So, one can see that the people of the USA do not have the resources to pay their expenses. Besides, these entitlements, the rest of the expenses are paid for with borrowed or printed (fiat) money that has little chance of being repaid unless perhaps by subsequent generations or by increases in taxes. Efforts to correct this coming economic crisis by austerity and sacrifice have been rejected by the public and the politicians worldwide. The Governments and the Press have participated in deception of the public about these issues in order to maintain their positions of power, for the truth would destroy them. No solution is in sight except more spending and valueless money printing.
This unchecked desire for more of everything without the responsibility to work or pay for these entitlements, has touched many countries and people with a few exceptions. This problem is the result of a worldwide breakdown of ethics and morality in society and a desire of the few for centralized control and power over the people. No country has instituted a solution to these problems that results in reducing expenditures or the growing debts. As many have stated in this paper, this policy cannot be sustained. The result of this scenario will be a worldwide economic crisis.
Fundamental to this impending economic crisis is the failure of centrally controlled economies and socialistic programs. Those selected groups, who benefit from having control, are the politicians, bankers, some selected industry leaders, and socialist planners, who will stop at nothing to maintain power and control over the people. Liberty of the people is in jeopardy worldwide. Read the evidence presented and decide if this summary is correct.
The troubling question is, “What will happen if the world economy collapses?” Will this crisis be a time for the few to take more control of the people through fear, crisis decisions, misinformation, prevention of the public from protecting themselves with guns, and pervasive spying technology on each citizen or will more democratic governments arise from the failure of centralized control, the welfare state, and the loss of liberty? Such crises have been repeated throughout 4000 years of recorded history. What happened in those past times? Read the quotations of Vladimir Lenin, developer of Marxism–Leninism, the foundation of Communism and judge what you have read from his statements.
An alternative to this dismal scenario is little discussed also in the Press. Why not? In the past 150 years, the alternative has happened with a rapid growth in democracy, communications technology, and life expectancy from advances in science and medicine. To unleash this huge human potential, at this time, will require individual freedom to create and innovate with the opportunity for risk and reward in an environment aided by unrestrictive governments even at the community and organizational levels. History records the success of the alternatives in the great leadership and creativity of humankind. The USA and the world are at the critical choice for their futures. We are experiencing the results of centrally controlling governments worldwide that are not working. Is it time for an alternative option? Read the evidence in this paper and decide for yourself.
Reading this paper will take you time, but you will not read all of this information elsewhere. It is key to your future. Decide for yourself what you should do after reading it. The URLs of many of the references are included so that you can read further about the many subjects presented yourself.
PMCID: PMC3815094  PMID: 24231906
Economics; politics; socialism; socioeconomics; welfare
14.  Canadian Association of University Surgeons’ Annual Symposium. Surgical simulation: The solution to safe training or a promise unfulfilled? 
Canadian Journal of Surgery  2012;55(4 Suppl 2):S200-S206.
At its 2009 annual symposium, chaired by Dr. William (Bill) Pollett, the Canadian Association of University Surgeons brought together speakers with expertise in surgery and medical education to discuss the role of surgical simulation for improving surgical training and safety. Dr. Daniel Jones, of Harvard University and the 2009 Charles Tator Lecturer, highlighted how simulation has been used to teach advanced laparoscopic surgery. He also outlined how the American College of Surgeons is moving toward competency assessments as a requirement before surgeons are permitted to perform laparoscopic surgery on patients. Dr. Teodor Grantcharov, from the University of Toronto, highlighted the role of virtual reality simulators in laparoscopic surgery as well as box trainers. Dr. Peter Brindley from the University of Alberta, although a strong proponent of simulation, cautioned against an overzealous adoption without addressing its current limitations. He also emphasized simulation’s value in team training and crisis resource management training. Dr. Chris de Gara, also from the University of Alberta, questioned to what extent simulators should be used to determine competency. He raised concerns that if technical skills are learned in isolation, they may become “decontextualized,” and therefore simulation might become counterproductive. He outlined how oversimplification can have an “enchanting” effect, including a false sense of security. As a result, simulation must be used appropriately and along the entire education continuum. Furthermore, far more needs to be done to realize its role in surgical safety.
PMCID: PMC3432250  PMID: 22854147
15.  Validation of a self-efficacy instrument and its relationship to performance of crisis resource management skills 
Self-efficacy is thought to be important for resuscitation proficiency in that it influences the development of and access to the associated medical knowledge, procedural skills and crisis resource management (CRM) skills. Since performance assessment of CRM skills is challenging, self-efficacy is often used as a measure of competence in this area. While self-efficacy may influence performance, the true relationship between self-efficacy and performance in this setting has not been delineated. We developed an instrument to measure pediatric residents’ self-efficacy in CRM skills and assessed its content validity, internal structure, and relationship to other variables. After administering the instrument to 125 pediatric residents, critical care fellows and faculty, we performed an exploratory factor analysis within a confirmatory factor analysis as well as a known group comparison. The analyses specified four factors that we defined as: situation awareness, team management, environment management, and decision making. Pediatric residents reported lower self-efficacy than fellows and faculty in each factor. We also examined the correlation between self-efficacy and performance scores for a subset of 30 residents who led video recorded simulated resuscitations and had their performances rated by three observers. We found a significant, positive correlation between residents’ self-efficacy in situation awareness and environment management and their overall performance of CRM skills. Our findings suggest that in a specific context, self-efficacy as a form of self-assessment may be informative with regards to performance.
PMCID: PMC3226693  PMID: 21264508
Crisis resource management skills; Mock codes; Non-technical skills; Performance assessment; Self-assessment; Self-efficacy; Simulated resuscitations; Simulation
16.  Enhancing residents’ neonatal resuscitation competency through unannounced simulation-based training 
Medical Education Online  2013;18:10.3402/meo.v18i0.18726.
Almost half of pediatric third-year residents surveyed in 2000 had never led a resuscitation event. With increasing restrictions on residency work hours and a decline in patient volume in some hospitals, there is potential for fewer opportunities.
Our primary purpose was to test the hypothesis that an unannounced mock resuscitation in a high-fidelity in-situ simulation training program would improve both residents’ self-confidence and observed performance of adopted best practices in neonatal resuscitation.
Each pediatric and medicine–pediatric resident in one pediatric residency program responded to an unannounced scenario that required resuscitation of the high fidelity infant simulator. Structured debriefing followed in the same setting, and a second cycle of scenario response and debriefing occurred before ending the 1-hour training experience. Measures included pre- and post-program confidence questionnaires and trained observer assessments of live and videotaped performances.
Statistically significant pre–post gains for self-confidence were observed for 8 of the 14 NRP critical behaviors (p=0.00–0.03) reflecting knowledge, technical, and non-technical (teamwork) skills. The pre–post gain in overall confidence score was statistically significant (p=0.00). With a maximum possible assessment score of 41, the average pre–post gain was 8.28 and statistically significant (p<0.001). Results of the video-based assessments revealed statistically significant performance gains (p<0.0001). Correlation between live and video-based assessments were strong for pre–post training scenario performances (pre: r=0.64, p<0.0001; post: r=0.75, p<0.0001).
Results revealed high receptivity to in-situ, simulation-based training and significant positive gains in confidence and observed competency-related abilities. Results support the potential for other applications in residency and continuing education.
PMCID: PMC3606478  PMID: 23522399
simulation-based training; neonatal resuscitation; competency; pediatric residents
17.  Developing an efficient scheduling template of a chemotherapy treatment unit 
The Australasian Medical Journal  2011;4(10):575-588.
This study was undertaken to improve the performance of a Chemotherapy Treatment Unit by increasing the throughput and reducing the average patient’s waiting time. In order to achieve this objective, a scheduling template has been built. The scheduling template is a simple tool that can be used to schedule patients' arrival to the clinic. A simulation model of this system was built and several scenarios, that target match the arrival pattern of the patients and resources availability, were designed and evaluated. After performing detailed analysis, one scenario provide the best system’s performance. A scheduling template has been developed based on this scenario. After implementing the new scheduling template, 22.5% more patients can be served.
CancerCare Manitoba is a provincially mandated cancer care agency. It is dedicated to provide quality care to those who have been diagnosed and are living with cancer. MacCharles Chemotherapy unit is specially built to provide chemotherapy treatment to the cancer patients of Winnipeg. In order to maintain an excellent service, it tries to ensure that patients get their treatment in a timely manner. It is challenging to maintain that goal because of the lack of a proper roster, the workload distribution and inefficient resource allotment. In order to maintain the satisfaction of the patients and the healthcare providers, by serving the maximum number of patients in a timely manner, it is necessary to develop an efficient scheduling template that matches the required demand with the availability of resources. This goal can be reached using simulation modelling. Simulation has proven to be an excellent modelling tool. It can be defined as building computer models that represent real world or hypothetical systems, and hence experimenting with these models to study system behaviour under different scenarios.1, 2
A study was undertaken at the Children's Hospital of Eastern Ontario to identify the issues behind the long waiting time of a emergency room.3 A 20-­‐day field observation revealed that the availability of the staff physician and interaction affects the patient wait time. Jyväskylä et al.4 used simulation to test different process scenarios, allocate resources and perform activity-­‐based cost analysis in the Emergency Department (ED) at the Central Hospital. The simulation also supported the study of a new operational method, named "triage-team" method without interrupting the main system. The proposed triage team method categorises the entire patient according to the urgency to see the doctor and allows the patient to complete the necessary test before being seen by the doctor for the first time. The simulation study showed that it will decrease the throughput time of the patient and reduce the utilisation of the specialist and enable the ordering all the tests the patient needs right after arrival, thus quickening the referral to treatment.
Santibáñez et al.5 developed a discrete event simulation model of British Columbia Cancer Agency"s ambulatory care unit which was used to study the impact of scenarios considering different operational factors (delay in starting clinic), appointment schedule (appointment order, appointment adjustment, add-­‐ons to the schedule) and resource allocation. It was found that the best outcomes were obtained when not one but multiple changes were implemented simultaneously. Sepúlveda et al.6 studied the M. D. Anderson Cancer Centre Orlando, which is a cancer treatment facility and built a simulation model to analyse and improve flow process and increase capacity in the main facility. Different scenarios were considered like, transferring laboratory and pharmacy areas, adding an extra blood draw room and applying different scheduling techniques of patients. The study shows that by increasing the number of short-­‐term (four hours or less) patients in the morning could increase chair utilisation.
Discrete event simulation also helps improve a service where staff are ignorant about the behaviour of the system as a whole; which can also be described as a real professional system. Niranjon et al.7 used simulation successfully where they had to face such constraints and lack of accessible data. Carlos et al. 8 used Total quality management and simulation – animation to improve the quality of the emergency room. Simulation was used to cover the key point of the emergency room and animation was used to indicate the areas of opportunity required. This study revealed that a long waiting time, overload personnel and increasing withdrawal rate of patients are caused by the lack of capacity in the emergency room.
Baesler et al.9 developed a methodology for a cancer treatment facility to find stochastically a global optimum point for the control variables. A simulation model generated the output using a goal programming framework for all the objectives involved in the analysis. Later a genetic algorithm was responsible for performing the search for an improved solution. The control variables that were considered in this research are number of treatment chairs, number of drawing blood nurses, laboratory personnel, and pharmacy personnel. Guo et al. 10 presented a simulation framework considering demand for appointment, patient flow logic, distribution of resources, scheduling rules followed by the scheduler. The objective of the study was to develop a scheduling rule which will ensure that 95% of all the appointment requests should be seen within one week after the request is made to increase the level of patient satisfaction and balance the schedule of each doctor to maintain a fine harmony between "busy clinic" and "quiet clinic".
Huschka et al.11 studied a healthcare system which was about to change their facility layout. In this case a simulation model study helped them to design a new healthcare practice by evaluating the change in layout before implementation. Historical data like the arrival rate of the patients, number of patients visited each day, patient flow logic, was used to build the current system model. Later, different scenarios were designed which measured the changes in the current layout and performance.
Wijewickrama et al.12 developed a simulation model to evaluate appointment schedule (AS) for second time consultations and patient appointment sequence (PSEQ) in a multi-­‐facility system. Five different appointment rule (ARULE) were considered: i) Baily; ii) 3Baily; iii) Individual (Ind); iv) two patients at a time (2AtaTime); v) Variable Interval and (V-­‐I) rule. PSEQ is based on type of patients: Appointment patients (APs) and new patients (NPs). The different PSEQ that were studied in this study were: i) first-­‐ come first-­‐serve; ii) appointment patient at the beginning of the clinic (APBEG); iii) new patient at the beginning of the clinic (NPBEG); iv) assigning appointed and new patients in an alternating manner (ALTER); v) assigning a new patient after every five-­‐appointment patients. Also patient no show (0% and 5%) and patient punctuality (PUNCT) (on-­‐time and 10 minutes early) were also considered. The study found that ALTER-­‐Ind. and ALTER5-­‐Ind. performed best on 0% NOSHOW, on-­‐time PUNCT and 5% NOSHOW, on-­‐time PUNCT situation to reduce WT and IT per patient. As NOSHOW created slack time for waiting patients, their WT tends to reduce while IT increases due to unexpected cancellation. Earliness increases congestion whichin turn increases waiting time.
Ramis et al.13 conducted a study of a Medical Imaging Center (MIC) to build a simulation model which was used to improve the patient journey through an imaging centre by reducing the wait time and making better use of the resources. The simulation model also used a Graphic User Interface (GUI) to provide the parameters of the centre, such as arrival rates, distances, processing times, resources and schedule. The simulation was used to measure the waiting time of the patients in different case scenarios. The study found that assigning a common function to the resource personnel could improve the waiting time of the patients.
The objective of this study is to develop an efficient scheduling template that maximises the number of served patients and minimises the average patient's waiting time at the given resources availability. To accomplish this objective, we will build a simulation model which mimics the working conditions of the clinic. Then we will suggest different scenarios of matching the arrival pattern of the patients with the availability of the resources. Full experiments will be performed to evaluate these scenarios. Hence, a simple and practical scheduling template will be built based on the indentified best scenario. The developed simulation model is described in section 2, which consists of a description of the treatment room, and a description of the types of patients and treatment durations. In section 3, different improvement scenarios are described and their analysis is presented in section 4. Section 5 illustrates a scheduling template based on one of the improvement scenarios. Finally, the conclusion and future direction of our work is exhibited in section 6.
Simulation Model
A simulation model represents the actual system and assists in visualising and evaluating the performance of the system under different scenarios without interrupting the actual system. Building a proper simulation model of a system consists of the following steps.
Observing the system to understand the flow of the entities, key players, availability of resources and overall generic framework.
Collecting the data on the number and type of entities, time consumed by the entities at each step of their journey, and availability of resources.
After building the simulation model it is necessary to confirm that the model is valid. This can be done by confirming that each entity flows as it is supposed to and the statistical data generated by the simulation model is similar to the collected data.
Figure 1 shows the patient flow process in the treatment room. On the patient's first appointment, the oncologist comes up with the treatment plan. The treatment time varies according to the patient’s condition, which may be 1 hour to 10 hours. Based on the type of the treatment, the physician or the clinical clerk books an available treatment chair for that time period.
On the day of the appointment, the patient will wait until the booked chair is free. When the chair is free a nurse from that station comes to the patient, verifies the name and date of birth and takes the patient to a treatment chair. Afterwards, the nurse flushes the chemotherapy drug line to the patient's body which takes about five minutes and sets up the treatment. Then the nurse leaves to serve another patient. Chemotherapy treatment lengths vary from less than an hour to 10 hour infusions. At the end of the treatment, the nurse returns, removes the line and notifies the patient about the next appointment date and time which also takes about five minutes. Most of the patients visit the clinic to take care of their PICC line (a peripherally inserted central catheter). A PICC is a line that is used to inject the patient with the chemical. This PICC line should be regularly cleaned, flushed to maintain patency and the insertion site checked for signs of infection. It takes approximately 10–15 minutes to take care of a PICC line by a nurse.
Cancer Care Manitoba provided access to the electronic scheduling system, also known as "ARIA" which is comprehensive information and image management system that aggregates patient data into a fully-­‐electronic medical chart, provided by VARIAN Medical System. This system was used to find out how many patients are booked in every clinic day. It also reveals which chair is used for how many hours. It was necessary to search a patient's history to find out how long the patient spends on which chair. Collecting the snapshot of each patient gives the complete picture of a one day clinic schedule.
The treatment room consists of the following two main limited resources:
Treatment Chairs: Chairs that are used to seat the patients during the treatment.
Nurses: Nurses are required to inject the treatment line into the patient and remove it at the end of the treatment. They also take care of the patients when they feel uncomfortable.
Mc Charles Chemotherapy unit consists of 11 nurses, and 5 stations with the following description:
Station 1: Station 1 has six chairs (numbered 1 to 6) and two nurses. The two nurses work from 8:00 to 16:00.
Station 2: Station 2 has six chairs (7 to 12) and three nurses. Two nurses work from 8:00 to 16:00 and one nurse works from 12:00 to 20:00.
Station 3: Station 4 has six chairs (13 to 18) and two nurses. The two nurses work from 8:00 to 16:00.
Station 4: Station 4 has six chairs (19 to 24) and three nurses. One nurse works from 8:00 to 16:00. Another nurse works from 10:00 to 18:00.
Solarium Station: Solarium Station has six chairs (Solarium Stretcher 1, Solarium Stretcher 2, Isolation, Isolation emergency, Fire Place 1, Fire Place 2). There is only one nurse assigned to this station that works from 12:00 to 20:00. The nurses from other stations can help when need arises.
There is one more nurse known as the "float nurse" who works from 11:00 to 19:00. This nurse can work at any station. Table 1 summarises the working hours of chairs and nurses. All treatment stations start at 8:00 and continue until the assigned nurse for that station completes her shift.
Currently, the clinic uses a scheduling template to assign the patients' appointments. But due to high demand of patient appointment it is not followed any more. We believe that this template can be improved based on the availability of nurses and chairs. Clinic workload was collected from 21 days of field observation. The current scheduling template has 10 types of appointment time slot: 15-­‐minute, 1-­‐hour, 1.5-­‐hour, 2-­‐hour, 3-­‐hour, 4-­‐hour, 5-­‐hour, 6-­‐hour, 8-­‐hour and 10-­‐hour and it is designed to serve 95 patients. But when the scheduling template was compared with the 21 days observations, it was found that the clinic is serving more patients than it is designed for. Therefore, the providers do not usually follow the scheduling template. Indeed they very often break the time slots to accommodate slots that do not exist in the template. Hence, we find that some of the stations are very busy (mostly station 2) and others are underused. If the scheduling template can be improved, it will be possible to bring more patients to the clinic and reduce their waiting time without adding more resources.
In order to build or develop a simulation model of the existing system, it is necessary to collect the following data:
Types of treatment durations.
Numbers of patients in each treatment type.
Arrival pattern of the patients.
Steps that the patients have to go through in their treatment journey and required time of each step.
Using the observations of 2,155 patients over 21 days of historical data, the types of treatment durations and the number of patients in each type were estimated. This data also assisted in determining the arrival rate and the frequency distribution of the patients. The patients were categorised into six types. The percentage of these types and their associated service times distributions are determined too.
ARENA Rockwell Simulation Software (v13) was used to build the simulation model. Entities of the model were tracked to verify that the patients move as intended. The model was run for 30 replications and statistical data was collected to validate the model. The total number of patients that go though the model was compared with the actual number of served patients during the 21 days of observations.
Improvement Scenarios
After verifying and validating the simulation model, different scenarios were designed and analysed to identify the best scenario that can handle more patients and reduces the average patient's waiting time. Based on the clinic observation and discussion with the healthcare providers, the following constraints have been stated:
The stations are filled up with treatment chairs. Therefore, it is literally impossible to fit any more chairs in the clinic. Moreover, the stakeholders are not interested in adding extra chairs.
The stakeholders and the caregivers are not interested in changing the layout of the treatment room.
Given these constraints the options that can be considered to design alternative scenarios are:
Changing the arrival pattern of the patients: that will fit over the nurses' availability.
Changing the nurses' schedule.
Adding one full time nurse at different starting times of the day.
Figure 2 compares the available number of nurses and the number of patients' arrival during different hours of a day. It can be noticed that there is a rapid growth in the arrival of patients (from 13 to 17) between 8:00 to 10:00 even though the clinic has the equal number of nurses during this time period. At 12:00 there is a sudden drop of patient arrival even though there are more available nurses. It is clear that there is an imbalance in the number of available nurses and the number of patient arrivals over different hours of the day. Consequently, balancing the demand (arrival rate of patients) and resources (available number of nurses) will reduce the patients' waiting time and increases the number of served patients. The alternative scenarios that satisfy the above three constraints are listed in Table 2. These scenarios respect the following rules:
Long treatments (between 4hr to 11hr) have to be scheduled early in the morning to avoid working overtime.
Patients of type 1 (15 minutes to 1hr treatment) are the most common. They can be fitted in at any time of the day because they take short treatment time. Hence, it is recommended to bring these patients in at the middle of the day when there are more nurses.
Nurses get tired at the end of the clinic day. Therefore, fewer patients should be scheduled at the late hours of the day.
In Scenario 1, the arrival pattern of the patient was changed so that it can fit with the nurse schedule. This arrival pattern is shown Table 3. Figure 3 shows the new patients' arrival pattern compared with the current arrival pattern. Similar patterns can be developed for the remaining scenarios too.
Analysis of Results
ARENA Rockwell Simulation software (v13) was used to develop the simulation model. There is no warm-­‐up period because the model simulates day-­‐to-­‐day scenarios. The patients of any day are supposed to be served in the same day. The model was run for 30 days (replications) and statistical data was collected to evaluate each scenario. Tables 4 and 5 show the detailed comparison of the system performance between the current scenario and Scenario 1. The results are quite interesting. The average throughput rate of the system has increased from 103 to 125 patients per day. The maximum throughput rate can reach 135 patients. Although the average waiting time has increased, the utilisation of the treatment station has increased by 15.6%. Similar analysis has been performed for the rest of the other scenarios. Due to the space limitation the detailed results are not given. However, Table 6 exhibits a summary of the results and comparison between the different scenarios. Scenario 1 was able to significantly increase the throughput of the system (by 21%) while it still results in an acceptable low average waiting time (13.4 minutes). In addition, it is worth noting that adding a nurse (Scenarios 3, 4, and 5) does not significantly reduce the average wait time or increase the system's throughput. The reason behind this is that when all the chairs are busy, the nurses have to wait until some patients finish the treatment. As a consequence, the other patients have to wait for the commencement of their treatment too. Therefore, hiring a nurse, without adding more chairs, will not reduce the waiting time or increase the throughput of the system. In this case, the only way to increase the throughput of the system is by adjusting the arrival pattern of patients over the nurses' schedule.
Developing a Scheduling Template based on Scenario 1
Scenario 1 provides the best performance. However a scheduling template is necessary for the care provider to book the patients. Therefore, a brief description is provided below on how scheduling the template is developed based on this scenario.
Table 3 gives the number of patients that arrive hourly, following Scenario 1. The distribution of each type of patient is shown in Table 7. This distribution is based on the percentage of each type of patient from the collected data. For example, in between 8:00-­‐9:00, 12 patients will come where 54.85% are of Type 1, 34.55% are of Type 2, 15.163% are of Type 3, 4.32% are of Type 4, 2.58% are of Type 5 and the rest are of Type 6. It is worth noting that, we assume that the patients of each type arrive as a group at the beginning of the hourly time slot. For example, all of the six patients of Type 1 from 8:00 to 9:00 time slot arrive at 8:00.
The numbers of patients from each type is distributed in such a way that it respects all the constraints described in Section 1.3. Most of the patients of the clinic are from type 1, 2 and 3 and they take less amount of treatment time compared with the patients of other types. Therefore, they are distributed all over the day. Patients of type 4, 5 and 6 take a longer treatment time. Hence, they are scheduled at the beginning of the day to avoid overtime. Because patients of type 4, 5 and 6 come at the beginning of the day, most of type 1 and 2 patients come at mid-­‐day (12:00 to 16:00). Another reason to make the treatment room more crowded in between 12:00 to 16:00 is because the clinic has the maximum number of nurses during this time period. Nurses become tired at the end of the clinic which is a reason not to schedule any patient after 19:00.
Based on the patient arrival schedule and nurse availability a scheduling template is built and shown in Figure 4. In order to build the template, if a nurse is available and there are patients waiting for service, a priority list of these patients will be developed. They are prioritised in a descending order based on their estimated slack time and secondarily based on the shortest service time. The secondary rule is used to break the tie if two patients have the same slack. The slack time is calculated using the following equation:
Slack time = Due time - (Arrival time + Treatment time)
Due time is the clinic closing time. To explain how the process works, assume at hour 8:00 (in between 8:00 to 8:15) two patients in station 1 (one 8-­‐hour and one 15-­‐ minute patient), two patients in station 2 (two 12-­‐hour patients), two patients in station 3 (one 2-­‐hour and one 15-­‐ minute patient) and one patient in station 4 (one 3-­‐hour patient) in total seven patients are scheduled. According to Figure 2, there are seven nurses who are available at 8:00 and it takes 15 minutes to set-­‐up a patient. Therefore, it is not possible to schedule more than seven patients in between 8:00 to 8:15 and the current scheduling is also serving seven patients by this time. The rest of the template can be justified similarly.
PMCID: PMC3562880  PMID: 23386870
18.  Research Priorities in Surgical Simulation for the 21st Century 
American Journal of Surgery  2012;203(1):49-53.
Despite a tremendous growth research in surgical simulation remains uncoordinated and unfocused. The objective of this study was to develop research priorities for surgical simulation.
Using a systematic methodology (Delphi), members of the Association for Surgical Education submitted 5 research questions on surgical simulation. An expert review panel categorized and collapsed the submitted questions and redistributed them to the membership to be ranked using a priority scale from 1(lowest) to 5(highest). The results were analyzed and categorized by consensus in distinct topics.
Sixty members submitted 226 research questions that were reduced to 74. Ratings ranged from 2.19–4.78. Topics included simulation effectiveness and outcomes, performance assessment and credentialing, curriculum development, team training and non-technical skills, simulation center resources and personnel, simulator validation, and other. The highest ranked question was “Does simulation training lead to improved quality of patient care, patient outcomes and safety?”
Research priorities for surgical simulation were developed using a systematic methodology and can be used to focus surgical simulation research in areas most likely to advance the field.
PMCID: PMC3322506  PMID: 22172482
surgical simulation; research priorities; research agenda; Delphi methodology
19.  Technical and Technological Skills Assessment in Laparoscopic Surgery 
Surgical appraisal and revalidation are key components of good surgical practice and training. Assessing technical skills in a structured manner is still not widely used. Laparoscopic surgery also requires the surgeon to be competent in technological aspects of the operation.
Checklists for generic, specific technical, and technological skills for laparoscopic cholecystectomies were constructed. Two surgeons with >12 years postgraduate surgical experience assessed each operation blindly and independently on DVD. The technological skills were assessed in the operating room.
One hundred operations were analyzed. Eight trainees and 10 consultant surgeons were recruited. No adverse events occurred due to technical or technological skills. Mean interrater reliability was kappa=0.88, P=<0.05. Construct validity for both technical and technological skills between trainee and consultant surgeons were significant, Mann-Whitney P=<0.05.
Our study demonstrates that technical and technological skills can be measured to assess performance of laparoscopic surgeons. This technical and technological assessment tool for laparoscopic surgery seems to have face, content, concurrent, and construct validities and could be modified and applied to any laparoscopic operation. The tool has the possibility of being used in surgical training and appraisal. We aim to modify and apply this tool to advanced laparoscopic operations.
PMCID: PMC3015707  PMID: 17212881
Assessment; Laparoscopic; Technical; Technology
20.  Implementation and evaluation of a simulation curriculum for paediatric residency programs including just-in-time in situ mock codes 
Paediatrics & Child Health  2012;17(2):e16-e20.
To develop, implement and evaluate a simulation-based acute care curriculum in a paediatric residency program using an integrated and longitudinal approach.
Curriculum framework consisting of three modular, year-specific courses and longitudinal just-in-time, in situ mock codes.
Paediatric residency program at BC Children’s Hospital, Vancouver, British Columbia.
The three year-specific courses focused on the critical first 5 min, complex medical management and crisis resource management, respectively. The just-in-time in situ mock codes simulated the acute deterioration of an existing ward patient, prepared the actual multidisciplinary code team, and primed the surrounding crisis support systems. Each curriculum component was evaluated with surveys using a five-point Likert scale.
A total of 40 resident surveys were completed after each of the modular courses, and an additional 28 surveys were completed for the overall simulation curriculum. The highest Likert scores were for hands-on skill stations, immersive simulation environment and crisis resource management teaching. Survey results also suggested that just-in-time mock codes were realistic, reinforced learning, and prepared ward teams for patient deterioration.
A simulation-based acute care curriculum was successfully integrated into a paediatric residency program. It provides a model for integrating simulation-based learning into other training programs, as well as a model for any hospital that wishes to improve paediatric resuscitation outcomes using just-in-time in situ mock codes.
PMCID: PMC3299361  PMID: 23372405
Curriculum; Education; Paediatric; Residency; Resuscitation; Simulation
21.  Safe eye surgery: non-technical aspects 
Eye  2011;25(9):1109-1111.
The traditional training of surgeons focused exclusively on developing knowledge, clinical expertise, and technical (surgical) skills. However, analyses of the reasons for adverse events in surgery have revealed that many underlying causes originate from behavioural or non-technical aspects of performance (eg, poor communication among members of the surgical team) rather than from a lack of surgical (ie, technical) skills. Therefore, technical skills appear to be necessary but not sufficient to ensure patient safety. Paying attention to non-technical skills, such as team working, leadership, situation awareness, decision making, and communication, will increase the likelihood of maintaining high levels of error-free performance. Identification and training of non-technical skills has been developed for high-risk careers, such as civil aviation and nuclear power. Only recently, training in non-technical skills has been adopted by the surgical world and anaesthetists. Non-technical skills need to be tailored to the environment where they are used, and eye surgery has some substantial differences compared with other surgical areas, for example, high volume of surgery, use of local anaesthetics, and very sophisticated equipment. This review highlights the need for identification of the non-technical skills relevant to eye surgeons and promotion of their use in the training of eye surgeons.
PMCID: PMC3178242  PMID: 21637301
surgery; complications; education; training; safety
22.  A tool for immediate and automated assessment of resuscitation skills for a full-scale simulator 
BMC Research Notes  2011;4:550.
For performance assessment during simulation, mostly observers rate the trainees' performance using checklists. Simulator outcome may provide immediate and objective feedback to the participants but requires additional work for the accurate scenario design. High-fidelity simulators are based on physiologic models and store all changes of the simulator conditions during the scenarios and may therefore be used for the assessment of performance. In the present work, the design of a simulator script for the assessment of resuscitation skills using an Emergency Care Simulator (ECS, METI, Sarasota, Florida) is described.
A standardized resuscitation simulator script and a visual basic-based macro were programmed for the immediate and automated extraction of performance-related variables from the log files. The following parameters were assessed: mean cardiac output, time until return of spontaneous circulation, no-flow-time, no-flow-time fraction, the time until the first defibrillation, the number and fraction of indicated and non-indicated defibrillations. Furthermore, mean deviation of defibrillation interval from the 2 minutes interval, the mean interval of defibrillations and the time until the first administration of epinephrine were calculated. As an example, the results of resuscitation efforts according to 2005 guidelines by five teams that consisted of one emergency physician and two paramedics are presented. No data are provided about its validity and reliability.
The tool can be used to assess adherence to European and American cardiopulmonary resuscitation guidelines (both 2005 and 2010) and to compare simulator outcome if different guidelines are trained and applied according to specific curricula. It represents an example of how simulator outcome can be used for performance assessment and may help to design more complex test-scenarios including the field of critical incidents in anesthesia.
PMCID: PMC3260387  PMID: 22185649
23.  Crisis management during anaesthesia: the development of an anaesthetic crisis management manual 
Background: All anaesthetists have to handle life threatening crises with little or no warning. However, some cognitive strategies and work practices that are appropriate for speed and efficiency under normal circumstances may become maladaptive in a crisis. It was judged in a previous study that the use of a structured "core" algorithm (based on the mnemonic COVER ABCD–A SWIFT CHECK) would diagnose and correct the problem in 60% of cases and provide a functional diagnosis in virtually all of the remaining 40%. It was recommended that specific sub-algorithms be developed for managing the problems underlying the remaining 40% of crises and assembled in an easy-to-use manual. Sub-algorithms were therefore developed for these problems so that they could be checked for applicability and validity against the first 4000 anaesthesia incidents reported to the Australian Incident Monitoring Study (AIMS).
Methods: The need for 24 specific sub-algorithms was identified. Teams of practising anaesthetists were assembled and sets of incidents relevant to each sub-algorithm were identified from the first 4000 reported to AIMS. Based largely on successful strategies identified in these reports, a set of 24 specific sub-algorithms was developed for trial against the 4000 AIMS reports and assembled into an easy-to-use manual. A process was developed for applying each component of the core algorithm COVER at one of four levels (scan-check-alert/ready-emergency) according to the degree of perceived urgency, and incorporated into the manual. The manual was disseminated at a World Congress and feedback was obtained.
Results: Each of the 24 specific crisis management sub-algorithms was tested against the relevant incidents among the first 4000 reported to AIMS and compared with the actual management by the anaesthetist at the time. It was judged that, if the core algorithm had been correctly applied, the appropriate sub-algorithm would have been resolved better and/or faster in one in eight of all incidents, and would have been unlikely to have caused harm to any patient. The descriptions of the validation of each of the 24 sub-algorithms constitute the remaining 24 papers in this set. Feedback from five meetings each attended by 60–100 anaesthetists was then collated and is included.
Conclusion: The 24 sub-algorithms developed form the basis for developing a rational evidence-based approach to crisis management during anaesthesia. The COVER component has been found to be satisfactory in real life resuscitation situations and the sub-algorithms have been used successfully for several years. It would now be desirable for carefully designed simulator based studies, using naive trainees at the start of their training, to systematically examine the merits and demerits of various aspects of the sub-algorithms. It would seem prudent that these sub-algorithms be regarded, for the moment, as decision aids to support and back up clinicians' natural responses to a crisis when all is not progressing as expected.
PMCID: PMC1744021  PMID: 15933282
24.  Description and validation of realistic and structured endourology training model 
Purpose: The aim of the present study was to validate a model of training, which combines the use of non-biological and ex vivo biological bench models, as well as the modelling of urological injuries for endourological treatment in a porcine animal model. Material and Methods: A total of 40 participants took part in this study. The duration of the activity was 16 hours. The model of training was divided into 3 levels: level I, concerning the acquisition of basic theoretical knowledge; level II, involving practice with the bench models and level III, concerning practice in the porcine animal model. First, trainees practiced with animals without using a model of injured (ureteroscopy, management of guide wires and catheters under fluoroscopic control) and later practiced in lithiasic animal model. During the activity, an evaluation of the face and content validity was conducted, as well as constructive validation provided by the trainees versus experts. Evolution of the variables during the course within each group was analysed using the Student’s t test for paired samples, while comparisons between groups, were performed using the Student’s t test for unpaired samples. Results: The assessments of face and content validity were satisfactory. The constructive validation, “within one trainee” shows that were statistical significant differences between the first time the trainees performed the tasks in the animal model and the last time, mainly in the knowledge of procedure and Holmium laser lithotripsy cathegories. At the beginning of level III, there are also statistical significant differences between trainee’s scores and the expert’s scores.Conclusions: This realistic Endourology training model allows the acquisition of knowledge and technical and non-technical skills as evidenced by the face, content and constructive validity. Structured use of bench models (biological and non biological) and animal model simulators increase the endourological basic skills.
PMCID: PMC4219312  PMID: 25374928
Endourology; training; animal model; bench model; validation
25.  Innovative Simulation Strategies in Education 
Nursing Research and Practice  2012;2012:765212.
The use of simulation in the undergraduate nursing curriculum is gaining popularity and is becoming a foundation of many nursing programs. The purpose of this paper is to highlight a new simulation teaching strategy, virtual reality (VR) simulation, which capitalizes on the technological skills of the new generation student. This small-scale pilot study focused on improving interpersonal skills in senior level nursing students using VR simulation. In this study, a repeated-measure design was used to evaluate the effectiveness of VR simulation on improving student's performance over a series of two VR scenarios. Using the Emergency Medicine Crisis Resource Management (EMCRM) tool, student performance was evaluated. Overall, the total EMCRM score improved but not significantly. The subscale areas of communication (P = .047, 95% CI: − 1.06, −.007) and professional behavior (P = .003, 95% CI: − 1.12, −.303) did show a significant improvement between the two scenario exposures. Findings from this study show the potential for virtual reality simulations to have an impact on nursing student performance.
PMCID: PMC3328148  PMID: 22550573

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