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Presented by Courtney Brown, MSN, CRNA Clinical Education Coordinator Wake Forest University Baptist Medical Center.

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Presentation on theme: "Presented by Courtney Brown, MSN, CRNA Clinical Education Coordinator Wake Forest University Baptist Medical Center."— Presentation transcript:

1 Presented by Courtney Brown, MSN, CRNA Clinical Education Coordinator Wake Forest University Baptist Medical Center

2 Simulation: the history  Aviation industry, nuclear power plants, anesthesia  1967: Abrahamson, Denson, & Wolf SIM 1 project  1988: David Gaba introduced CASE

3 Definitions  David Gaba (Stanford University): “Simulation is a technique, not a technology, to replace or amplify real experiences with guided experiences, often immersive in nature, that evoke or replicate substantial aspects of the real world in a fully interactive fashion” Gaba (2007)

4 Definitions  Pamela Jeffries (Johns Hopkins University SON): “Simulations are defined as activities that mimic the reality of a clinical environment and are designed to demonstrate procedures, decision-making, and critical thinking through techniques such as role playing and the use of devices such as interactive videos or mannequins” Jeffries, (2005)

5 Definitions  S. Barry Issenberg (University of Miami): “In general, medical simulations aim to imitate real patients, anatomic regions, or clinical tasks, or to mirror the real-life situations in which medical services are rendered” Issenberg & Scalese (2008)

6 Definitions  Fidelity: The degree to which an electronic system accurately reproduces the sound or image of its input signal (Merriam-Webster)  Fidelity is also synonymous to realism

7 Level of FidelityExamples Low fidelityPatient actors Simulated interviews Written problems Task trainersIntubation mannequins Spinal and epidural trainers Venipuncture arms CVP insertion High FidelitySimMan (Laedal) HPS (METI) Virtual reality Turcato, Robertson, & Covert (2008)

8 The Simulation Environment  Environment fidelity: the degree the simulator replicates motion cues, visual cues, or sensory information from the task environment  Engineering fidelity: the degree to which the simulation device or training setting reproduces the physical characteristics of the real task  Psychologic fidelity: the degree to which the trainee perceives the simulation to be believable for the tasks Issenberg & Scalese (2008)

9 Types of Simulation  Task trainers: inexpensive, great for skill attainment or evaluation Examples: plastic arms for venipuncture, head or neck for intubation techniques, Resusci-Anne (chest compressions and ventilation)

10 Types of Simulation  Computer-enhanced mannequin: very expensive ($30,000- $250,000); full body, reproduce anatomy, normal and pathophysiologic function Examples: Human patient simulator (HPS) from Medical Education Technologies (METI); SimMan from Laerdal

11 Types of Simulation  Virtual reality: user interactions are within the a simulated virtual world which can range from computer-generated environments to CAVE simulations that allow for goggles and sensor-containing gloves Examples: virtual emergency department, trauma resuscitation scenarios, or virtual delivery rooms to assess neonates

12 Simulation in Nurse Anesthesia Programs Turcato, Robertson & Covert (2008)

13 Virtual Reality Emergency Room

14 Crisis Resource Management  Manser, Harrsion, Gaba, & Howard (2009): Observational study of 24 paired crews Higher performing crews: ○ Less task distribution ○ More situation assessment Low performing skills ○ Split into sub-crews ○ No shared plan

15 Crisis Resource Management  Team-focus  Crisis management skills  Can be Interdisciplinary  Atul Gawande, MD: Medicine is a team sport  In Situ Simulation: takes place on the patient unit itself (Miller et al., 2008)

16 Crisis Resource Management  Knudson et al. (2008), seven key elements: 1. Command 2. Leadership 3. Communication 4. Situation awareness 5. Workload management 6. Resource management 7. Decision making

17 Mobile simulation and On- Demand  On-demand simulation available at Harvard Medical School  Mobile simulation

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19 Theories  John Dewey  David Kolb  Albert Bandura  George Miller Kaakinen & Arwood (2009)

20 Kolb

21 Bandura

22 Miller Michelson & Manning (2008)

23 Gaba’s Dimensions

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26 Jeffries Simulation Framework

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28 The Creation of a Simulation 1. Know your purpose: Teach nurse anesthesia students the physiologic signs and symptoms and treatment of an intraoperative bronchospasm 2. The unit of participation Groups of 3 (team) 3. Know your participants: First semester, inexperienced, nurse anesthesia students. They are all former ICU nurses.

29 The Creation of a Simulation 4. The health care domain: High Stakes, OR environment 5. The providers: Student nurse anesthetists 6. The knowledge, skills, or behaviors chosen to address: Decision-making skills, attitudes, behavior, communication

30 The Creation of a Simulation 7. The age of the patient: A 65 year old female 8. The technology required: A human patient simulator with the ability to increase airway resistance and has monitoring 9. The site required: A physical environment that replicates the operating room 10. The extant of direct participation: Direct hands-on participation, immersive

31 The Creation of A Simulation 11. The feedback method accompanying Real-time mentoring and immediate feedback with start and stop of simulation

32 Set-up  Bring students in, provide background information (chart)  Offer time for questions/answers  Have all emergency equipment necessary for simulation readily available (including epinephrine, albuterol in emergency drugs in second drawer)  State on the intercom, “Simulation is beginning”

33 Create a Patient  Patient Name:  Name, age, and gender:  Chief Complaint:  History of Present Illness:  Past Medical History:  Past Surgical / Anesthetic History:  Review of Systems: CNS: Cardiovascular: Pulmonary: Renal / Hepatic: Endocrine: Heme/Coag:  Current Medications:  Physical Examination:  General:  Weight, Height:  Vital Signs:  Airway:  Lungs:  Heart:  Laboratory, Radiology, and other relevant studies:  Hematocrit:

34 Our patient…  Annie A. Mess 65 yo female for laparoscopic cholecystectomy. C/o abdominal pain for 2 weeks with increasing intensity PMH: GERD, Seasonal allergies, Obesity, and osteoarthritis of the left knee PSH: Left knee replacement one year prior done under a spinal technique, no anesthesia complications

35 Our patient…  Annie A. Mess:  ROS: CNS: Negative Cardiovascular: Negative; denies CP Pulmonary: Seasonal allergies; not currently Renal / Hepatic: GERD Endocrine: Obesity Heme/Coag: Negative  Takes prilosec daily (took last night); PRN sudafed  Overweight female in no acute distress  5’5”, 90 kg  HR 70, BP 125/70, SPO2 97%  Airway: MP 3, OA 3, TMD 2  Lungs: Clear, but distant  Heart: RRR, no murmurs, rubs or gallups  EKG: NSR, 68

36 Simulation Software  Prewritten versus Simulation user written  First, choose a background patient Built into the HPS software Can write as well  Then, choose the scenario “Bronchospasm with Hypoxia”  Allow participants to nest and get “into” the mode  Initiate the scenario and monitor

37 Course of Simulation Time FramePatient changesOutcomes expected/ Transitions Pre- induction: Chart Q/A None HPS: Choose Stannette patient Introduce team Focused assessment Medication last dose NPO status Last surgery Severity of GERD Discuss anesthetic choices “Your simulation is beginning” InductionHPS: Monitor drugs chosen Monitor patient need for pressors Initiate “Bronchospasm/Hypoxia” Scenario start HPS: Increase airway resistance Decrease SPO2 (shunt fraction) Increase HR Increase CO2 production Monitor for resolution r/t management Call for “Help” Team communication Listen to lung sounds Take patient off ventilator 100% FiO2, increase Vapor setting Give albuterol Consider epinephrine “Your simulation has ended”

38 Debriefing  Self assessment  Feedback via dialogue  Reflection  Video replay  Timing is irrelevant  Repetition if time avails Bond et al. (2008)

39 Best Evidence in Medical Education (BEME)  Feedback: MOST important  Repetitive practice  Range of difficulty level: progressive  Multiple learning strategies  Clinical variation  Controlled environment  Individualized learning  Defined Outcomes/Benchmarks  Simulator realism/Validity  Curricular integration Issenberg & Scalese (2008)

40 Choices, choices, choices  Simulation – Defaults to the Patient Profile (patient information and medical history)  Scenario – Play or Edit scenarios  Condition – Set parameters for assessment and trauma.  Drugs – Administer drugs  Fluids – Affect plasma and blood volumes and urine output  Cardiovascular – Set a wide array of parameters affecting cardiovascular physiology  Respiratory – Control airway, lung and respiratory parameters

41 Assessment  Bowel Sounds – Normal, Hyperactive, Hypoactive  Breath Sounds – Normal, Wheezing, Rales, Muffled  Heart Sounds – Normal, S3, S4, S3 and S4, Early Systolic Murmur, Mid Systolic Murmur, Late Systolic Murmur, Pan Systolic Murmur, Late Diastolic Murmur

42 Drugs  Narcotics  Hypnotics  Neuromuscular Blockers  Antagonists  Cardiovascular  ACLS

43 Simulation Center Ingredients  The simulation area  The control room  The debriefing area  An area for storage of equipment  Video and audio equipment

44 Easy, right?  Drawbacks to full-scale simulations: Technical difficulties Team dynamics issues Communication issues Unpredictable at times Necessity to orientation to environment “Buy-in”

45 Simulation Centers  Center for Immersive and Situation-based Learning Stanford University  Center for Medical Simulation Harvard Medical School  Peter M. Winter Institute for Simulation Education and Research (WISER) University of Pittsburg Medical Center  Center for Applied Learning Wake Forest University Baptist medical Center Cannon-Diehl (2009)

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47 SMARTER Approach Rosen, Salas, Silvestri, Wu, & Lazarra (2008)

48 Forms of Evaluations  Checklists: Did they, or didn’t they? Binary (performed or not) Incremental (performed, performed well, performed poorly) Easy, can be timed Objective Structured Clinical Examinations (OSCEs)  Rating scales Global (Likert) versus Criterion-based  Scoring rubrics  Formative versus summative Bould, Crabtree & Naik (2009)

49 Forms of Evaluations FormReliabilityValidityEase of Use Comprehensiven ess Direct Observation Poor reliabilityFace validity+++Potentially ChecklistsExcellent reliability Construct validity ++Depends on checklist Global scalesExcellent reliability Construct validity ++Depends on content Multiple stations Excellent reliability Construct validity Expensive Timely Potentially

50 Graduate Medical Education  Simulation-based assessment has been used since the OSCEs with simulation patient actors since the 1980s!  Accreditation Council for Graduate Medical Education (ACGME) Outcomes Project to assess the quality of GME Simulation is listed as a key assessment tool  American Board of Emergency Medicine 7 patients (5 single and 2 multiple) for high stakes examinations

51 ACGME Outcomes Project 1. Incorporation of a set of general competencies to organize curricula. 2. Support for programs through identification and development of useful, reliable, and valid methods for assessing attainment of the competencies. 3. Development of model resident evaluation systems to provide examples of dependable evaluation. 4. Support of a resources support system. http://www.acgme.org/Outcome

52 The Six Competencies 1. Patient Care 2. Medical Knowledge 3. Professionalism 4. Systems-based Practice 5. Practice-based Learning and Improvement 6. Interpersonal and Communication Skills http://www.acgme.org/Outcome

53 Examples of a Checklist: Knowledge Rosen, Salas, Silvestri, Wu, & Lazarra (2008)

54 Examples of a Checklist: Skill Rosen, Salas, Silvestri, Wu, & Lazarra (2008)

55 ACGME Components of Assessment 1. Assessment is consistent with curriculum/program objectives. 2. The educational objectives are representative of the educational domains of interest. 3. Multiple assessment approaches/instruments are employed. 4. Multiple observations are conducted. 5. Multiple observers/raters provide assessments. 6. Performance is assessed according to pre- specified standards or criteria. 7. Assessment is fair. http://www.acgme.org/Outcome/assess/Toolbox.pdf

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57 Simulation: Procedural Skills Kahol, Vanipuram & Smith (2009)

58 Practice makes perfect  Issenberg et al. (1999): “The most important identifiable factor separating the elite performer from others is the amount of “deliberate practice.” This includes practice undertaken over a long period of time to attain excellence as well as the amount of ongoing effort required to maintain it.”

59 Simulation experience: More is More McGaghie, Issenberg, Petrusa, & Scalese (2006):

60 Multiple-scenario Assessments Murray, Boulet< Avidan, Kras, Henrichs, Woodhouse, and Evers (2007)

61 Impact on Safety Climate  Cooper et al (2008): “Contrary to our expectations, the study gives no evidence that CRM faculty training produced any overall improvement in safety climate in the experimental hospitals, compared to the control hospitals.”

62 Patient Safety 1. Safety priority 2. Reporting mistakes 3. Safety valued 4. Emergency teamwork 5. Mgmt support 6. Safe workload 7. Asking for help 8. Reveal mistakes

63 Crisis Resource Management  MOSES course (UK): Multidisciplinary obstetric simulated emergency scenarios  MOES system: Mobile obstetric emergencies simulator

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65 Retention rates

66 Crisis Resource Management  How often should CRM be practiced?

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68 Simulation Research

69 Evidence still lacking  Outcomes research (Issenberg et al., 2005) BEME systematic literature review Focus was on education

70 Evidence still lacking  Outcomes research (Issenberg et al., 2005)

71 Evidence still lacking  Outcomes research (Issenberg et al., 2005)

72 Evidence still lacking  Outcomes research (Issenberg et al., 2005)

73 Newer Evidence Promising

74 Barriers for Educators Turcato, Robertson, & Covert (2008) 1. Time 2. Cost 3. Distance from Program 4. Scheduling 5. Lack of technical support 6. Lack of laboratory space 7. Lack of full-time equivalents 8. Administration unsupportive

75 Oregon: A Case Study Collaborative Project Oregon Simulation Alliance Objective: address the demand for quality simulation by making expertise available and developing a statewide system. Members: Representatives from the Governor’s office, organizations VPs, Area Healthcare Education Centers (AHECs) officials, public/private universities, the Department of Public Health, and simulation experts

76 Oregon: A Case Study  Outcomes: ○ Over $1,000,000 in funding for equipment, simulation specialist training, and faculty development ○ Education to help programs implement ○ Simulation training courses ○ 16 simulation specialists trained ○ A statewide summit (networking; process evaluation) ○ New simulation facilities

77 Oregon: A Case Study  Lessons learned: Need to encumber funds immediately after site visits instead of concurrently (had to accelerate site visits’ timeline) Hold awardees accountable for their use of equipment (one member institution was not meeting expectations) Hire a permanent director for the alliance

78 Oregon 2005 Seropian et al (2006)

79 Other interesting findings  Halamek (2008) NeoSim program developed First simulation-based training program in neonatal medicine Steering committee: developed a list of characteristics desired in a cost-effective neonatal simulator Became the first RFP in simulator history that a professional body rather than industry drove the development of a simulator

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81 The Public  IOM “To Err is Human”  Recent evidence that Simulation works Captain Sullenberger “Doing the jobs we were trained to do”

82 Simulation Professional Organizations  Society for Simulation in Healthcare (SSH) Have a Journal: Simulation in Healthcare Founded by Dr. David Gaba 2007: “the biggest step for simulation going forward will not be technological, but will be organizational”  Advanced Initiatives in Medical Simulation (AIMS)  International Meeting on Medical Simulation Gaba & Raemer (2007)

83 Professional Medical Organizations  American College of Surgeons  Accreditation Council for Graduate Medical Education  American Society of Anesthesiologists  American Board of Anesthesiologists  Society for Academic Emergency Medicine

84 Professional Nursing Organizations  National League of Nurses  National Council of State Boards of nursing  American Association of Colleges of Nursing  American Association of Nurse Anesthetists  American Association of Critical Care Nurses

85 Government Agencies  The US Food and Drug Administration  The Agency for Healthcare Research & Quality (AHRQ)  16 states have legislature allowing high fidelity simulation in lieu of clinical clock hours; 17 have legislation pending

86 Malpractice Insurance  Harvard Medical School 2-tier rate structure for anesthesiologists 6% less for those who participated in ACRM Cooper et al. (2008)

87 Web sources for simulation  Society of Simulation in Healthcare http://www.ssih.org/SSIH/SSIH/Home/  International Nursing Association for Clinical Simulation and Learning http://www.inacsl.org/INACSL_2010/  Society in Europe for Simulation Applied to Medicine http://www.sesam-web.org/  Advanced Initiatives in Medical Simulation (AIMS) http://www.medsim.org/ Cannon-Diehl (2009)

88 Web sources for simulation  Center for Immersive and Situation- based Learning http://cisl.stanford.edu/  Center for Medical Simulation http://www.harvardmedsim.org/  SIMS Medical Academy http://www.simsacademy.info/  University of Pittsburg, WISER http://www.wiser.pitt.edu/ Cannon-Diehl (2009)

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90  Pennsylvania State University has a mobile simulation program

91 Key Points  Simulation is a valuable tool for skill acquisition and maintenance  Crisis Resource management imparts team coordination skills  Evaluation tools are still under development (checklists/global pairs)  More Outcomes research needed  Multiple scenarios should be used for high stakes evaluation  Perhaps a culture of continued crisis competence would yield better results than biennial competence testing

92 Closing Quote  Gaba, “no industry in which human lives depend on skilled performance of responsible operators has waited for unequivocal proof of the benefit of simulation before embracing it.”

93 References  Accreditation Council for Graduate Medical Education (2000). Toolbox of Assessment Methods. Retrieved from http://www.acgme.org/Outcome/assess/Toolbox.pdf http://www.acgme.org/Outcome/assess/Toolbox.pdf  Bond, W., Kuhn, G., Binstadt, E., Quirk, M., Tews, M., Dev, P., & Ericsson, A. (2008). The use of simulation in the development of individual cognitive expertise in emergency medicine. Academic Emergency Medicine, 15, 1037-1045.  Bould, MD., Crabtree, NA., & Naik, VN. (2009). Assessment of procedural skills in anesthesia. British Journal of Anesthesia, 103 (4), 472-483.  Cannon-Diehl, MR. (2009). Simulation in healthcare and nursing. Critical Care Nursing Quarterly, 32 (2), 128-136.  Cooper, JB., Blum, RH., Carrol, JS., Dershwitz, M., Feinstein, DM., Gaba, DM., Morey, JC., & Single, AK. (2008). Differences in safety climate among hospital anesthesia departments and the effect of a realistic simulation-based training program. Anesthesia & Analgesia, 106 (2), 574-584.

94 References  DeAnda, A., & Gaba, DM. (1990). Unplanned incidents during comprehensive anesthesia simulation. Anesthesia & Analgesia, 71, 77-82.  Ericsson, KA. (2004). Deliberate practice and the acquisition and maintenance of expert performance in medicine and related domains. Academic Medicine, 79 (Supp), S70- S81.  Fitts, PM., & Posner, MI. (1979). Human Performance. Westport: Greenwood Press.  Friedman, Z., Siddiqui, N., Katznelson, R., Devito, I., Bould, MD., & Naik, V. (2009). Clinical impact of epidural anesthesia simulation on short- and long-term learning curve. Regional Anesthesia and Pain Medicine, 34 (3), 229-231.  Gaba, D. (2007). The future vision of simulation in healthcare. Quality & Safety in Healthcare, 13(Supp1), i2-i10.  Gaba, DM., & DeAnda, A. (1989). The response of anesthesia trainees to simulated critical incidents. Anesthesia & Analgesia, 68, 444-451.

95 References  Gaba, DM, & DeAnda, A. (1988). A comprehensive anesthesia simulation environment. Anesthesiology, 69, 387-394.  Gaba, D., & Raemer, D. (2007). The tide is turning: organizational structures to embed simulation in the fabric of healthcare. Simulation in Healthcare, 2(1), 1-3.  Halamek, LP. (2008). The simulated delivery-room environment as the future modality for acquiring and maintaining skills in fetal and neonatal resuscitation. Seminars in Fetal & Neonatal Medicine, 13, 448-453.  Hoadley, TA. (2009). Learning advanced cardiac life support: A comparison study of the effects of low- and high-fidelity simulation. Nursing Education Research, 30 (2), 91-95.  Holzman, RS., Cooper, JB., Gaba, DM., Philip, JH., Small, SD., & Feinstein, D. (1995). Anesthesia crisis resource management: Real-life simulation training in operating room crises. Journal of Clinical Anesthesia, 7: 675-687.  Isaacson, JJ., 7 Stacy, AS. (2009). Rubrics for clinical evaluation: Objectifying the subjective experience. Nurse Education in Practice, 9: 134-140.

96 References  Issenberg, SB, & Scalese, RJ. (2008). Simulation in health care education. Perspectives in Biology & Medicine, 51(1), 31-46.  Issenberg, SB., McGaghie, WC., Hart, IR., Mayer, JW., Felner, JM., Petrusa, ER….Ewey, GA. (1999). Simulation technology for health care professional skills training and assessment. Journal of American Medical Association, 282, 861-866.  Issenberg, SB., McGaghie, WC., Petrusa, ER., Gordon, DL., & Scalese, RJ. (2005). Features and uses of high-fidelity medical simulations that lead to effective learning: a BEME systematic review. Medical Teacher, 27 (1), 10-28.  Jeffries, P. (2005). A Framework for designing, implementing, and evaluate simulations used as teaching strategies in nursing. Nursing Education Perspectives, 96-103.  Kaakinen, J., & Arwood, E. (2009). Systematic review of nursing simulation literature for use of learning theory. International Journal of Nursing Education Scholarship, 6(1), 1-20.

97 References  Kahol, K., Vankipuram, M., & Smith, M. (2009). Cognitive simulators for medical education and training. Journal of Biomedical Informatics, 42, 593-604.  Knudson, MM., Khaw, L., Bullard, K., Dicker, R., Cohen, MJ., Staudenmayer, K... Krummel, T. (2008). Trauma training in simulation: Translating skills from SIM time to real time. The Journal of Trauma, 64 (2), 255-264.  Lammers, RL. (2008). Learning and retention rates after training in posterior epistaxis management. Academic Emergency Medicine, 15, 1181-1189.  Lammers, RL., Davenport, M., Korley, F., Griswold-Theodorson, S., Fitch, M., Narang, A.... Robey, WC. (2008). Teaching and assessing procedural skills using simulation: metrics and methodology. Academic Emergency Medicine, 15: 1079-1087.  Manser, T., Harrison, TK., Gaba, DM., & Howard, SK. (2009). Coordination patterns related to high clinical performance in a simulated anesthetic crisis. Anesthesia & Analgesia, 108 (5), 1606-1615.

98 References  McGaghie, WC., Issenberg, SB., Petrusa, ER., & Scalese, RJ. (2006). Effect of practice on standardised learning outcomes in simulation-based medical education. Medical Education, 40: 792-797.  McLaughlin, S., Fitch, MT., Goyal, D., Hayden, E., Yang Kauh, C., Laack, T... Gordon, JA. (2008). Simulation in graduate medical education 2008: A review for emergency medicine. Academic Emergency Medicine, 15, 1117-1129.  Michelson, J., & Manning, L. (2008) Competency assessment in simulation-based procedural education. The American Journal of Surgery, 196, 609-615.  Miller, GE. (1990). The assessment of clinical skills/competence/performance. Academic Medicine, 65 (Supp), S63-S67.  Miller, KK., Riley, W., Davis, S., & Hansen, HE. (2008). In situ simulation: A method of experiential learning to promote safety and team behavior. Journal of Perinatal & Neonatal Nursing, 22(2), 105-113.

99 References  Murray, DJ., Boulet, JR., Avidan, M., Kras, JF., Henrichs, B., Woodhouse, J., & Evers, AS. (2007). Performance of residents and anesthesiologists in a simulation-based skill assessment. Anesthesiology, 107: 705-713  Rosen, MA., Salas, E., Silvestri, S., Wu, TS, & Lazzara, E. (2008). A measurement tool for simulation-based training in emergency medicine: The simulation module for assessment of resident-targeted event responses (SMARTER) Approach. Simulation in Healthcare, 3, 170-179.  Seropian, MA., Driggers, B., Taylor, J., Gubrud-Howe, P., & Brady, G. (2006). The Oregon simulation experience: A statewide simulation network and alliance. Simulation in Healthcare, 1 (1), 56-61.  Turcato, N., Robertson, C., & Covert, K. (2008). Simulation based education: What’s in it for nurse anesthesia educators? AANA Journal, 76(4), 257-262.


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