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Chapter 33

Role of cognitive simulations in healthcare Usha Satish and Satish Krishnamurthy

Overview ◆

Simulations allow healthcare providers to hone their skills without endangering the patient or hurting their self confidence. A number of simulations are available and their use enhances safety of patient care.

Cognitive simulations provide a realistic replication of a healthcare professional’s workday that involves several complex demands that have to be processed simultaneously. Cognitive simulations help assess and train the underlying process variables of medical decision making, including planning, strategy, multitasking, critical thinking and overall perspective.

Healthcare provider is often challenged by VUCAD (volatility, uncertainty, complexity, ambiguity, and by problems with delayed feedback such as test results) when decisions have to be made. Healthcare providers need to have the ability to respond to complex challenges by processing information optimally in addition to factual content knowledge necessary to respond to the task at hand. Strategic management simulations (SMS) provide an optimal opportunity to acquire both.

SMS assesses and trains ‘how’ we think.

Standard testing of cognitive parameters are usually performed individually and the interaction of various parameters are extrapolated to real life subsequently. SMS simultaneously evaluates multiple cognitive parameters simultaneously in a ‘real-life’ situation. This real world atmosphere allows for a more realistic (ecologically relevant) assessment of competency.

In addition, SMS can also help both the learners and teachers to understand performance in the simulation in relation to a number of well-validated factors as well as help in retraining. SMS can be used for individual or team evaluation or training.

SMS has been used to evaluate generic thinking in a wide variety of subjects. SMS successfully differentiates performance among normal subjects (superior functioning managers versus average functioning managers; better medical residents versus average or poorly functioning residents). SMS is effective in evaluating a change in functioning due to medications or environmental chemicals, or due to disordered brain function.

SMS can demonstrate milder deficits in head injured patients in the relative absence of deficits in standard neuropsychological tests.

SMS technology provides a strong compliment to existing simulator technologies, which greatly enhance specific procedural or algorithmic skills.


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33.1 Introduction “High-quality learning is impossible in the absence of high-quality patient care; likewise, high-quality patient care is impossible without high-quality learning. Attention to both is needed.” Leach and Philibret, 2006. A number of constituencies are becoming increasingly interested in measuring the performance of physicians in their day-to-day clinical practices, especially since the Institute of Medicine’s report suggested that the quality of care may often be less than optimal (1) . Purchasers of healthcare services, for instance, are concerned about the effects of suboptimal care on workforce productivity, and seek to maximize the quality of care provided. Consumers of care also want to be able to identify high-quality physicians and institutions but lack the effective means to do so. Although some groups have measured and reported quality of care for individual medical groups and physicians, these efforts have been limited(2). Both patients and healthcare purchasers desire more effective means of identifying excellent clinicians, and a number of organizations have begun discussing and implementing plans for assessing the performance of individual clinicians and the settings in which they choose to practice. The combination of changes in healthcare delivery, shortened hospital stays, more home and ambulatory care, variations in care not explained by science, declining reimbursements and, above all, the inexorable and visible failure of the current system to deliver safe care, has been described as the ‘perfect storm’. Safer and more predictable care is needed. Paul O’Neill has said that he knows of no other industry that accepts a 38% reimbursement on amounts billed. McGlynn et al. (3) has said that we deliver care known to be best only 54% of the time. These numbers may be related(4). Simulation enhances both safety and predictability. Every patient deserves a competent physician every time. The domains of simulation and rehearsal in medicine encompasses non-computer-dependent modalities such as human cadavers, animal models and standardized patients, along with various forms that rely on electronic technology to create situations and scenarios. They range from simple electronic models and mannequins, personal computer screen-based approaches to high-technology, high fidelity interactive patient simulators for individuals and teams of participants. Simulation scenarios can encompass procedural tasks, crisis resource management, and introduction of learners to clinical situations.

33.1 Definition The Society for Simulation in Healthcare(5) uses the following definition of simulation in healthcare: Simulation is a technique – not a technology – to replace or amplify real patient experiences with guided experiences, artificially contrived, that evokes or replicates substantial aspects of the real world in a fully interactive manner(6). Artificial environments such as flight simulators for the training of airline pilots, the USS Enterprise’s Holodeck, movie set-like towns and alleys for military to train within, computer models of weather prediction using ‘what if ’ scenarios or hospital drills come within this definition(5). All of these techniques for learning and training have been successful in improving pattern recognition thought process, specific skills, outcomes, and post-encounter evaluations. Despite this plethora of simulation options, medicine as a whole is a relative newcomer to simulation, when compared with domains such as aviation and one medical specialty – anaesthesiology. Yet in the span of a few years, robust evidence of its benefits has moved simulation from the vanguard to the cutting edge of validated practice in medical education and the professional development of practising physicians(7).


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UNDERLYING PRINCIPLES: THE NEED FOR SIMULATIONS

Widespread use of computers has enabled simulating real environments and its application to the field of healthcare possible. There are several attractions in applying simulations to the field of healthcare. Healthcare providers whether they are in training or already trained are constantly learning how to provide better care for patients. Maintenance of certification which includes lifelong learning and audit of one’s practice is a requirement for physicians from all specialties. Various tasks involved in taking care of a patient, namely clinical skills, algorithmic management of emergent conditions, surgical procedures, thinking skills, and teamwork have all been successfully simulated with good results. The recipient of care, subjects covered, skills learnt, time required and the cost of simulation vary widely. Literature search using either general search engines or Medline generates several hundred articles. A variety of institutions have a centre for simulation, several societies and journals devoted to simulation exist, reflecting an explosive interest in this area. The prime goal for all these simulations appears to be improved patient safety. Simulations allow healthcare providers to hone their skills without endangering the patient or hurting their self confidence. Simulation has the potential for the evolution of a new teaching paradigm for the new millennium(8). These techniques do not depend on hospital encounters and can be re-run, stopped, or otherwise altered to enhance educational value. Thereby, creating a non threatening learning environment where multiple options could potentially be tested, worked through and mastered. “Every patient deserves a competent physician every time. Every resident deserves competent teachers and an excellent learning environment. Simulation serves both of these core principles.”(4)

33.2 Underlying principles: the need for simulations In To Err Is Human: Building a Safer Health System the Institute of Medicine encouraged the medical community to reach out boldly to other domains for insight and inspiration for different models of performance and teaching(1). Effective use of simulation technology is a substantial contributor to making commercial air transportation the safest available mode of travel. Human error is routinely blamed for disasters in the air, on the railways, in complex surgery, and in healthcare generally(9). While one action or omission may be the immediate cause of an incident, closer analysis usually reveals a series of events and departures from safe practice; each influenced by the working environment and the wider organizational context. Understanding the characteristics of a safe and high performing system, therefore, requires research of the context, the development and maintenance of individual skills, the role of high technology, the impact of working conditions on team performance, and the nature of high performance teams. Simulation is an essential tool in the learning and understanding of high performing systems. Safety in these high reliability organizations (HROs) is ultimately understood as a characteristic of the system – the sum total of all the parts and their interactions(10). This cultural evolution required the creation of a continuous improvement process. This process includes firstly, an event reporting system that processes data into meaningful knowledge, creating opportunity for meaningful change within an organization. Secondly, it required simulations to study systems and to implement changes within an organization. The importance of effective teamwork in aviation is critical to safety. Human beings make mistakes. Until crew performance was studied in simulation, the captain was God in the cockpit; and his crew disagreed with him at their peril. In this tradition or ‘culture’, the airplane, passengers, and crew were exposed to the captain’s potential errors while deprived of the knowledge and skill that resided among the remaining members of the crew. Simulation studies demonstrated that airplanes could be more safely and reliably operated if the knowledge and skills of the entire crew were applied to the flight tasks. Techniques and procedures

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were developed in simulation that preserve and enhance the captain’s authority and effectiveness by enhancing the flow of information among the entire crew(10). Contemporary airline safety is in significant measure the product of this loop of operational reporting, analysis in simulation, and training in simulation. State-of-the-art airline crew training, the Advanced Qualification Program (AQP), emerged out of simulation studies during which reported actual events were recreated in simulation. AQP identified specific team skills that enhance safety through effective use of all available resources – human, hardware, and information. The process achieved a greater degree of integration of the team skills in part because AQP team training and practice increases awareness of human and system error, and provides techniques and skills that will minimize their effects. This is accomplished through awareness of crew member attitudes and behaviour, and the use of practical management skills(10). An important variant of simulators are cognitive simulations. These simulations have the intrinsic capability of replicating several aspects of a learner’s environment simultaneously. This provides a realistic replication of a healthcare professional’s workday that involves several complex demands that have to be processed simultaneously. In other words, cognitive simulation technologies, help assess and train the underlying process variables of medical decision making, including but not limited to planning, strategy, multitasking, critical thinking and overall perspective. This technology provides a strong compliment to existing simulator technologies, which greatly enhance specific procedural or algorithmic skills.

33.3 Requirements for effective medical decision making Competency in professional endeavours may require much more than finding a single ‘correct’ response to some particular situation(11,12). There are task situations where a single correct action or where multiple correct actions will solve the problems at hand, but not all challenges fit that pattern. Complex tasks – including medical decision making tasks – can generate unpredictable dynamics that defy treatment with standard content knowledge approaches (13,14). Factual (content) knowledge can be gained from reading books or from memorizing lecture notes, and from repeating successful prior actions in response to repetitive challenges that led to success. When a task is highly challenging and does not fit a memorized or documented pattern, an additional set of skills is necessary; adequate competency in information processing is essential(15). Just as factual knowledge must be learned, information processing skills are also subject to learning and training although this form of training cannot be transmitted through books or lectures(16). In fact, modern learning theorists clearly distinguish the processes involved in the acquisition and use of specific content knowledge and the acquisition and use of intellectual processing skills that are free of specific knowledge content(17). The latter skills represent cognitive strategies that an effective decision maker uses to regulate his or her own processes of attending, learning, remembering and thinking(18), involving external (incoming) information as well as internal or remembered information and concepts(19). These ‘information processing strategies’ are not fixed; they must adjust to changes in task challenges – for example, different patients with different sets of morbidities and conditions – and they must adjust to gains in knowledge over time(20). Learning to apply such processing strategies requires guided personal experience. We respond to an environmental stimulus based on our interpretation of ‘normal’ for the situation we are in. Our sense of normal depends on extent of exposure to that particular situation, our knowledge, and our ability to learn. Response to a stimulus depends on our alertness, ability to focus (without distractions akin to sterile areas in the cockpit where no one is allowed to distract the pilot and the co-pilot during take-off or landing), knowledge of the context, accurate interpretation of the stimulus and threshold level for a response. Last but not the least, the execution of the


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Stimulus: Symptom Exam finding Lab result Radiology result Surgical finding Intrinsic Curiosity etc.

Interpretation: Evaluate stimulus in response to context and background knowledge

Feedback loop essential to learning, and to develop better interpretation and response in future

Response: Act/ don’t act Seek more information Ignore as irrelevant Plan for future

Design and execute appropriate response/s in an error free manner

Evaluate and monitor effectiveness of response: Maintain course of action Stop the response Modify the response

Fig. 33.1 Stimulus-Response-Feedback loop.

response needs to be error free. The results need to be monitored for desired outcome and the response is modified if the outcome is deviating from the optimum (Fig. 33.1) In addition, the physician or medical team is often challenged by VUCAD (volatility, uncertainty, complexity, ambiguity and by problems with delayed feedback such as test results)(15) when decisions have to be made. How can we make sure that physicians will effectively manage a network of interrelated problems that involve ambiguity, inconsistency, novelty and surprise(21)? We have known for some time that learning, transfer of knowledge and ability are impacted by both task structure and task complexity, and by the structural information processing competence of the individual (physician) involved(22). We need to ensure that medical personnel have the factual content knowledge needed to respond to the task at hand, but we also need to make sure that they can respond to complex challenges by processing information optimally. Simulations, if used as part of an appropriate training system, provide an optimal opportunity to acquire both.

33.4 Fundamental concepts of strategic management simulations

and its relevance to healthcare and HROs Cognitive simulations have the intrinsic capability of replicating several aspects of a learner’s environment simultaneously. This provides a realistic replication of a healthcare professional’s workday that involves several complex demands that have to be processed simultaneously.

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This technology provides a strong compliment to existing simulator technologies which greatly enhance specific procedural or algorithmic skills. Standard testing of cognitive parameters are usually performed individually and the interaction of various parameters are extrapolated to real life subsequently. The true impact of a mild memory loss and a decreased attention span in a head injured patient might mean that s/he will not be employable. Strategic management simulations (SMS) simultaneously evaluates multiple cognitive parameters simultaneously in a ‘real life’ like situation. This ‘real life’ like situation means that the subject experiences volatility, uncertainty, delayed feedback and ambiguity with inadequate information, which are part of everyday decision making. SMS can demonstrate milder deficits in head injured patients in the relative absence of standard neuropsychological deficits(23). The real world atmosphere of the task and setting, involving multiple potentially interactive components of task demands as well as multiple and interactive options to engage in various aspects of behavior allows for a more realistic (ecologically relevant) assessment of competency. SMS is unique in the absence of requirements to engage in specific actions or to make decisions at specific points in time, the absence of stated demands to respond to specific information, the freedom to develop initiative, and freedom for strategy development and decision implementation allows each participant to utilize his/her own preferred or typical action, planning and strategic styles. Most of the simulations are interactive and directly responsive to the actions taken by the subject. SMS records the responses of the subject in relation to the evolution of the scenario but does not alter the course of the simulation. This feature is known as quasi experimental simulation and allows comparison of performance of different subjects using the same scenario. This property has allowed determination of norms for different levels of functioning in normal subjects. Comparison of a subject with or without a drug or medication can be evaluated. Reported studies include effects of caffeine(24), alcohol(25) etc. SMS described below go beyond simply recreating the learner’s complex environment and allowing the learner to practice or be evaluated. In addition, SMS can also help both the learners and teachers to understand performance in the simulation in relation to a number of well-validated factors as well as help in retraining(26). SMS has been used to evaluate generic thinking in a wide variety of subjects. SMS successfully differentiates performance among normal subjects (superior functioning managers versus average functioning managers(27); better medical residents versus average or poorly functioning residents (28)). SMS is effective in evaluating a change in functioning due to medications 29 or environmental chemicals, or due to disordered brain function23. It is commonly known in the managerial world that a CEO who is successful in selling cars can be successful in selling any other widget. This implies that successful managers think differently and this ‘how of thinking’ is important in addition to specific knowledge of cars or the specific widget. Whereas team task analysis as detailed by Burke et al.(30) focuses on designing a simulation for a specific situation, SMS evaluates generic thinking processes. As mentioned previously, both content specific knowledge as well as generic decision making competencies is essential for optimal functioning. Further, SMS uses several different scenarios all of which evaluate the same generic thinking processes, effect of learning from repetition is eliminated. Effectiveness of focused training of areas of deficiencies in a subject can be objectively evaluated using SMS. 33.4.1

Description of the SMS

SMS assess both basic cognitive and behavioural responses to task demands as well as cognitive and behavioural components that are commonly subsumed under the rubric of executive functions. High levels of predictive validity, reliability and applicability of the SMS simulations to real


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world settings have been repeatedly demonstrated both in North America and Europe (26,31). The method provides more than 80 computer gathered and calculated measures of functioning, loading on 12 reliable factors (based on factor analytic varimax rotation for more than 2000 prior subjects). Among others, simulation data predict success on indicators such as ‘job level at age’, ‘income at age’, “number of persons supervised’, and ‘number of job promotions during the past 10 years’ (corrected for industry, location, etc)26. These simulations can be administered to both individual participants as well as teams. While individual simulation runs offer feedback to a participant on their individual decision making pattern, group performances yield rich data on how teams function together. Further team evaluations also provide detailed information on each of the individual team participants thereby enhancing the feedback and improvement potential. These are particularly important performance of teams of physicians and other healthcare providers. Potential applications for team performance include handling of mass casualties and disastrous situations. During a simulation, participants make decisions during a one half-hour task period. The absence of requirements to engage in specific actions or to make decisions at specific points in time, the absence of stated demands to respond to specific information, the freedom to develop initiative, and freedom for strategy development and decision implementation allows each participant to use his/her own preferred or typical action, planning and strategic styles. The real world atmosphere of the task and setting, involving multiple potentially interactive components of task demands as well as multiple and interactive options to engage in various aspects of behaviour allows for a more realistic (ecologically relevant) assessment of competency. 33.4.2

SMS measurement outputs

Data in response to the factors listed in Table 33.1 are captured and provided via computer generated scores and represented in two primary output modalities. These outputs are used for feedback and potential training as required.

Table 33.1 Definition of SMS Measures. Measures

Definitions

Activity level

Overall level of activity (measures both focused activity that is directed to a specific context and activity that is directed toward overall goals)

Response speed

Speed of responses both in terms of emergent and non-emergent situations

Task orientation

Ability to focus on a task at hand and also focus on ‘larger’ goals

Initiative

Ability to generate activity without an overt external stimulus that would aid in successful task completion. Elements pertaining to initiative in context and strategy are also measured

Information management Ability to seek and use information efficaciously

Strategy

Ability to form systematic plans and actions that are optimally sequenced and goal directed in the long term

Breadth of approach

Ability to think along multiple dimensions and find different solutions to problems

Planning

Ability to make task oriented plans in the short and long term

Emergency responses

Ability to think critically and strategically under conditions of emergency and stress

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111 112 113 114 121 124 131 141 142 211 212 231 232 233 322 333 411 431 453 513 521 522 532 622 666 732 772

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33.4.2.1 Time event matrix (Fig. 33.2)

These are direct graphic representations of performance, and are captured during the performance period. A good analogy to describe this complex output is like a magnetic resonance imaging scan of decision making. These graphs are represented with various combinations of lines and symbols that represent different aspects of decision making. Based on appropriate interpretation these graphs accurately predict the ‘underlying process’ of thinking in a participant. In general, richer performance by the subject during the simulation is indicated by a more complex graph. Time during the simulation is plotted on the horizontal axis and the vertical axis represents the variety of decisions made by the participant. Individual actions are represented by a point, placed vertically above the time when the action occurred and horizontally in line with the particular decision code. Information provided or incoming information is denoted with a star. If an action corresponds to incoming information, one or more stars (depending on the number of pieces of information) are placed on the same horizontal level where the action is located, with stars placed at the point when each item of information was received. The action is circled to indicate that it was responsive to an event or a message. If the participants thinks and acts strategically these actions are connected with diagonal lines. If these actions are strategy based on use of opportunity and information that is already provided these lines are coloured red. If the strategies represent visionary thinking and are not necessarily cued, they are represented by green lines. Blue lines also an integral part of this output represents the ability to create plans. In addition, there are several other symbols and line formations that represent elements of critical thinking such as initiative, multitasking, and sustained planning, among others. A serious emergency is introduced at some point in all the strategic management simulation scenarios. The emergency requires rapid and decisive action. Performance patterns during this time point can be compared to other time points in the simulation to judge both the effectiveness of crisis handling as well as preparation for a crisis and recovery patterns after crisis. 33.4.3.2 Profile (Fig. 33.3)

This profile represents the 12 factors listed above in terms of percentile scores. The scores reflect low, moderate and high levels of performance based on normative data. These profiles are used to ascertain the performance pattern of a participant in the various parameters of decision making. Further since these measures are fine tuned in terms of the definition of a given parameter and its implications in the real world, it helps make the training more focused and thereby time effective. 33.4.3

SMS and healthcare applications

David Leach outlines several reasons why simulations should be used for medical education(4). To ensure patient safety, clinical skills have to be learnt as far away from the patient as possible. Simulations allow actions to be planned, studied and debriefed to allow safer patient care. Simulation is a great tool for educating residents. Simulations can be used as a formative tool for resident development. Simulation can be used to expose mastery of both rules and values. Familiarity with protocols becomes clear during simulations. At the same time, it is also possible to require improvization as the learner manages emerging situations. Rules are either demonstrated or not; improvization calls forth adaptive expertise. Improvisation exposes values. It is an efficient and safe way to explore competence. Residents can intentionally make mistakes and learn about their consequences during simulations. Simulation can determine how residents respond in different contexts. Simulation can be used to populate a portfolio of assessed experiences that enable residents to demonstrate their abilities. Simulation offers a controlled way to learn systems based practice. Simulations can be constructed

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Fig. 33.3 Strategic management simulation profile chart.


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REFERENCES

that involve multiple interdependent variables. Simulation can document how residents think, as well as what they think. Every resident deserves competent teachers and an excellent learning environment(4). The complexity of medicine is best demonstrated in the fact that frequently there is inadequate information, rapidly changing conditions, delayed feedback, uncertainty of results with the same treatment in different individuals and multiple providers involved in the care of a single patient. These challenges are best addressed using complex cognitive simulation scenarios where participants can actually think through all the possibilities and arrive at appropriate solutions. Clearly, simulations have the distinct advantage of providing ‘real world’ experiences to the learner without causing harm to patients or learners. Simulations can be designed to replicate virtually all complex realities and offer training and retraining using well-standardized paradigms. Simulations are increasingly used for training in and evaluation of procedural skills in surgery and anaesthesia, for example. We believe that simulation can also be a highly effective way to evaluate decision-making and leadership skills in medicine, providing students and residents with insights into their own abilities and needs, and assisting faculty in reliably assessing competence in these areas. The complexity of teaching the art and science of medicine is a quest that will be a continued challenge to healthcare professionals. However, it would be wise to bear in mind the virtue of constant learning and improvement as noted by Mahatma Gandhi’s words of wisdom, “Live as if you were to die tomorrow, Learn as if you were to live forever.”

References 1. Kohn, L, Corrigan, J, Donaldson M, Eds. (2000). To Err is Human: Building a Safer Health System. National Academy Press, Washington, DC: 146. 2. Landon BE, Normand ST, Blumenthal D, Daley J (2003). Physician Clinical Performance Assessment: Prospects and Barriers. JAMA 290: 1183–9. 3. McGlynn EA, Asch SM, Adams J, et al. (2003). The quality of healthcare delivered to adults in the United States. N Engl J Med 348(26): 2635–45. 4. Leach D (2005). Simulation: it’s about respect. ACGME Bulletin December 2005. 5. http://www.ssih.org/about%20ssh/ssh-what-is-sim.html 6. Gaba DM (2004). The future vision of simulation in healthcare. Qual Saf Health Care 13(Suppl. 1): i2–i10. 7. Editor’s Introduction (2005). ACGME Bulletin December 2005. 8. Dunn WF (2004). Simulators in Critical Care Education and Beyond. Society of Critical Care Medicine: Introduction. 9. Reason J (1990). Human Error. New York: Cambridge University Press. 10. Hamman W, Rutherford W (2005). The language of aviation simulation training: Relevance for medical education. ACGME Bulletin December 2005: 5–7. 11. Breuer K, Streufert D (1996). Authoring of complex learning environments: design considerations for dynamic simulations. J Struct Learn 12: 315–21. 12. Scandura JM, Stone DC, Scandura AB (1986). An intelligent role tutor CBI system for diagnostic testing and instruction. J Sruct Learn 9: 15–61. 13. Streufert S (1970). Complexity and complex decision making: convergences between differentiation and integration approaches to the prediction of task performance. J Exp Soc Psychol 6: 494–509. 14. Hall N (1993). Explaining Chaos: a Guide to the New Science of Disorder. New York: W W Norton. 15. Streufert S, Streufert SC (1978). Behavior in the Complex Environment. New York: John Wiley. 16. Streufert S, Swezey R (1985). Complexity, Managers and Organizations. New York: Academic Press. 17. Gagné RM (1985). The Conditions of Learning and Theory of Instruction. New York: Holt Rinehart and Winston.

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18. Breuer K (1992). Cognitive development based on process-learning environments. In: Dijstra S, Krammer HPM, van Merrienboer JJG, Eds. Instructional Models in Computer Based Learning Environments. Berlin: Springer Verlag. 19. Tennyson RD, Thurlow K, Breuer K (1987). Problem oriented simulations to develop and improve higher order thinking strategies. Comput Hum Behav 3: 151–65. 20. Toffler D (1980). Zukunftschance. Munich: Deutscher Taschenbuch Verlag. 21. Isenberg DJ (1984). How senior managers think. Harvard Bus Rev: 84608. 22. Buss AR (1972). Learning, transfer and changes in ability factor: a multivariate model. Psychol Bull 80: 106–12. 23. Satish U, Streufert S, Eslinger PJ (1999). Complex decision making after orbitofrontal damage. Neurocase 5: 355–64. 24. Streufert S, Satish U, Pogash R, et al. (1997). Excess coffee consumption in simulated complex work settings: detriment or facilitation of performance? J Appl Psychol 82(5): 774–82. 25. Streufert S, Pogash RM, Roache J, et al. (1992). Effects of alcohol intoxication on risk taking, strategy, and error rate in visuomotor performance. J Appl Psychol 77(4): 515–24. 26. Streufert S, Nogami G, Swezey RW, et al. (1988). Computer assisted training of complex managerial performance. Computers Hum Behav 4: 77–88. 27. Streufert S, Pogash R, Piasecki M (1988). Simulation-based assessment of managerial competence: reliability and validity. Personnel Psychol 41: 537–57. 28. Satish U, Streufert S, Marshall R, et al. (2001). Strategic management simulation is a novel way to measure resident competencies. Am J Surg 181: 557–61. 29. Streufert S, DePadova A, McGlynn T, Pogash R, Piasecki M (1988). Impact of beta blockade on complex cognitive functioning. Am Heart J 116(1 Pt 2): 311–5. 30. Burke CS, Salas E, Wilson-Donnelly K, Priest H (2004). How to turn a team of experts into an expert medical team: guidance from the aviation and military communities. Qual Saf Health Care 13(Suppl. 1):i96–i104. 31. Breuer K, Satish U (2003). Emergency management Simulations: An approach to the assessment of decision-making processes in complex dynamic crisis environments. In: From Modeling to Managing Security. Norwegian Academic Press, Norway: 145–55.

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