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Systems Design, Modeling, and Simulation in Medicine

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Guide to Simulation-Based Disciplines

Abstract

Health care is changing at a very rapid pace. So does its attendant complexity and ever increasing reliance on high technology support. Technical medicine, where sophisticated, technology-based methods are used in education of healthcare professionals and in treatment of patients, is becoming a recognized discipline. Such methods require a new generation of engineers, scientists, systems designers, and physicians to integrate medical and technical domains. With this in mind, this chapter provides an overview of modeling and simulation technologies as applied to healthcare. A historical perspective is given followed by the discussion of how simulation helps in gaining professional competency and how it improves healthcare outcomes. Systems for support of medical training and clinical practice are discussed from both engineering and clinical perspectives. Challenges and opportunities for further development of complex simulation-based medical trainers are presented as well.

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References

  • Abrahamson, S., Denson, J. S., & Wolf, R. M. (1969). Effectiveness of a simulator in training anesthesiology residents. Academic Medicine, 44(6), 515–519.

    Google Scholar 

  • Abrahamson, S., Denson, J. S., & Wolf, R. M. (2004). Effectiveness of a simulator in training anesthesiology residents. Quality and Safety in Health Care, 13(5), 395–397.

    Google Scholar 

  • Aggarwal, R., Ward, J., Balasundaram, I., Sains, P., Athanasiou, T., & Darzi, A. (2007). Proving the effectiveness of virtual reality simulation for training in laparoscopic surgery. Annals of surgery, 246(5), 771–779.

    Google Scholar 

  • Ahlberg, G., Enochsson, L., Gallagher, A. G., Hedman, L., Hogman, C., McClusky, D. A., & Arvidsson, D. (2007). Proficiency-based virtual reality training significantly reduces the error rate for residents during their first 10 laparoscopic cholecystectomies. The American journal of surgery, 193(6), 797–804.

    Google Scholar 

  • Alaker, M., Wynn, G. R., & Arulampalam, T. (2016). Virtual reality training in laparoscopic surgery: a systematic review & meta-analysis. International Journal of Surgery, 29, 85–94.

    Google Scholar 

  • Badash, I., Burtt, K., Solorzano, C. A., & Carey, J. N. (2016). Innovations in surgery simulation: a review of past, current and future techniques. Annals of Translational Medicine, 4(23).

    Google Scholar 

  • Barsuk, J. H., McGaghie, W. C., Cohen, E. R., O’leary, K. J., & Wayne, D. B. (2009a). Simulation-based mastery learning reduces complications during central venous catheter insertion in a medical intensive care unit. Critical care medicine, 37(10), 2697–2701.

    Google Scholar 

  • Barsuk, J. H., Cohen, E. R., Feinglass, J., McGaghie, W. C., & Wayne, D. B. (2009b). Use of simulation-based education to reduce catheter-related bloodstream infections. Archives of internal medicine, 169(15), 1420–1423.

    Google Scholar 

  • Barsuk, J. H., McGaghie, W. C., Cohen, E. R., Balachandran, J. S., & Wayne, D. B. (2009c). Use of simulation based mastery learning to improve the quality of central venous catheter placement in a medical intensive care unit. Journal of Hospital Medicine, 4(7), 397–403.

    Google Scholar 

  • Barsuk, J. H., Cohen, E. R., Potts, S., Demo, H., Gupta, S., Feinglass, J., & Wayne, D. B. (2014). Dissemination of a simulation-based mastery learning intervention reduces central line-associated bloodstream infections. BMJ quality & safety, 23(9), 749–756.

    Google Scholar 

  • Beyer, L., De Troyer, J., Mancini, J., Bladou, F., Berdah, S. V., & Karsenty, G. (2011). Impact of laparoscopy simulator training on the technical skills of future surgeons in the operating room: a prospective study. The American Journal of Surgery, 202(3), 265–272.

    Google Scholar 

  • Beyer-Berjot, L., Berdah, S., Hashimoto, D. A., Darzi, A., & Aggarwal, R. (2016). A Virtual Reality Training Curriculum for Laparoscopic Colorectal Surgery. Journal of Surgical Education, 73(6), 932–941.

    Google Scholar 

  • Bonnetain, E., Boucheix, J. M., Hamet, M., & Freysz, M. (2010). Benefits of computer screen based simulation in learning cardiac arrest procedures. Medical education, 44(7), 716–722.

    Google Scholar 

  • Bradley, P. (2006). The history of simulation in medical education and possible future direc-tions. Medical education, 40(3), 254–262.

    Google Scholar 

  • Brydges, R., Hatala, R., Zendejas, B., Erwin, P. J., & Cook, D. A. (2015). Linking simulation-based educational assessments and patient-related outcomes: a systematic review and meta-analysis. Academic Medicine, 90(2), 246–256.

    Google Scholar 

  • Capella, J., Smith, S., Philp, A., Putnam, T., Gilbert, C., Fry, W., & Ranson, S. (2010). Teamwork training improves the clinical care of trauma patients. Journal of surgical education, 67(6), 439–443.

    Google Scholar 

  • Cartwright, M. S., Reynolds, P. S., Rodriguez, Z. M., Breyer, W. A., & Cruz, J. M. (2005). Lumbar puncture experience among medical school graduates: the need for formal proce-dural skills training. Medical education, 39(4), 437–437.

    Google Scholar 

  • Centers for Disease Control and Prevention. (2011). Vital signs: central line–associated blood stream infections—United States, 2001, 2008, and 2009. Annals of Emergency Medicine, 58(5), 447–450.

    Google Scholar 

  • Chang, J., Banaszek, D. C., Gambrel, J., & Bardana, D. (2016). Global rating scales and motion analysis are valid proficiency metrics in virtual and benchtop knee arthroscopy simulators. Clinical Orthopaedics and Related Research®, 474(4), 956–964.

    Google Scholar 

  • Cohen, J., Cohen, S. A., Vora, K. C., Xue, X., Burdick, J. S., Bank, S., & Greenwald, D. (2006). Multicenter, randomized, controlled trial of virtual-reality simulator training in acquisition of competency in colonoscopy. Gastrointestinal endoscopy, 64(3), 361–368.

    Google Scholar 

  • Cohen, E. R., Feinglass, J., Barsuk, J. H., Barnard, C., O’donnell, A., McGaghie, W. C., & Wayne, D. B. (2010). Cost savings from reduced catheter-related bloodstream infection after simulation-based education for residents in a medical intensive care unit. Simulation in healthcare, 5(2), 98–102.

    Google Scholar 

  • Cook, D. A., Erwin, P. J., & Triola, M. M. (2010). Computerized virtual patients in health professions education: a systematic review and meta-analysis. Academic Medicine, 85(10), 1589–1602.

    Google Scholar 

  • Cook, D. A., Hatala, R., Brydges, R., Zendejas, B., Szostek, J. H., Wang, A. T., & Hamstra, S. J. (2011). Technology-enhanced simulation for health professions education: a systematic review and meta-analysis. Jama, 306(9), 978–988.

    Google Scholar 

  • Cook, D. A., Brydges, R., Hamstra, S. J., Zendejas, B., Szostek, J. H., Wang, A. T., & Hatala, R. (2012). Comparative effectiveness of technology-enhanced simulation versus other instructional methods: a systematic review and meta-analysis. Simulation in Healthcare, 7(5), 308–320.

    Google Scholar 

  • Cook, D. A., Hamstra, S. J., Brydges, R., Zendejas, B., Szostek, J. H., Wang, A. T., & Hatala, R. (2013a). Comparative effectiveness of instructional design features in simulation-based education: systematic review and meta-analysis. Medical teacher, 35(1), e867-e898.

    Google Scholar 

  • Cook, D. A., Brydges, R., Zendejas, B., Hamstra, S. J., & Hatala, R. (2013b). Technology-enhanced simulation to assess health professionals: a systematic review of validity evidence, research methods, and reporting quality. Academic Medicine, 88(6), 872–883.

    Google Scholar 

  • Cooper, J. B., & Taqueti, V. (2004). A brief history of the development of mannequin simulators for clinical education and training. Quality and Safety in Health Care, 13(suppl 1), i11–i18.

    Google Scholar 

  • Cooper, K., Davies, R., Roderick, P., Chase, D., & Raftery, J. (2002). The development of a simulation model of the treatment of coronary heart disease. Health care management science, 5(4), 259–267.

    Google Scholar 

  • Day, T. E., Al-Roubaie, A. R., & Goldlust, E. J. (2012). Decreased length of stay after addition of healthcare provider in emergency department triage: a comparison between computer-simulated and real-world interventions. Emergency Medicine Journal, emermed-2012.

    Google Scholar 

  • Day, T. E., Sarawgi, S., Perri, A., & Nicolson, S. C. (2015). Reducing postponements of elective pediatric cardiac procedures: analysis and implementation of a discrete event simulation model. The Annals of thoracic surgery, 99(4), 1386–1391.

    Google Scholar 

  • Dehmer, S. P., Baker-Goering, M. M., Maciosek, M. V., Hong, Y., Kottke, T. E., Margolis, K. L., & Thomas, A. J. (2016). Modeled health and economic impact of team-based care for hypertension. American journal of preventive medicine, 50(5), S34-S44.

    Google Scholar 

  • De Mauro, A., Greco, M., & Grimaldi, M. (2015, February). What is big data? A consensual definition and a review of key research topics. In G. Giannakopoulos, D. P. Sakas, & D. Kyriaki-Manessi (Eds.), AIP conference proceedings (Vol. 1644, No. 1, pp. 97–104). AIP.

    Google Scholar 

  • DeRienzo, C. M., Shaw, R. J., Meanor, P., Lada, E., Ferranti, J., & Tanaka, D. (2016). A discrete event simulation tool to support and predict hospital and clinic staffing. Health informatics journal, 1460458216628314.

    Google Scholar 

  • Deutsch, E. S., Dong, Y., Halamek, L. P., Rosen, M. A., Taekman, J. M., & Rice, J. (2016). Leveraging Health Care Simulation Technology for Human Factors Research: Closing the Gap Between Lab and Bedside. Human factors, 58(7), 1082–1095.

    Google Scholar 

  • Draycott, T. J., Crofts, J. F., Ash, J. P., Wilson, L. V., Yard, E., Sibanda, T., & Whitelaw, A. (2008). Improving neonatal outcome through practical shoulder dystocia training. Obstetrics & Gynecology, 112(1), 14–20.

    Google Scholar 

  • Duncan, D. R., Morgenthaler, T. I., Ryu, J. H., & Daniels, C. E. (2009). Reducing iatrogenic risk in thoracentesis: establishing best practice via experiential training in a zero-risk environment. CHEST Journal, 135(5), 1315–1320.

    Google Scholar 

  • Endo, K., Sata, N., Ishiguro, Y., Miki, A., Sasanuma, H., Sakuma, Y., & Yasuda, Y. (2014). A patient-specific surgical simulator using preoperative imaging data: an interactive simulator using a three-dimensional tactile mouse. Journal of Computational Surgery, 1(1), 10.

    Google Scholar 

  • Evans, C. H., & Schenarts, K. D. (2016). Evolving educational techniques in surgical training. Surgical Clinics of North America, 96(1), 71–88.

    Google Scholar 

  • Feher, M., Harris-St John, K., & Lant, A. (1991). Blood pressure measurement by junior hospital doctors–a gap in medical education?. Health trends, 24(2), 59–61.

    Google Scholar 

  • Feldman, L. S., Sherman, V., & Fried, G. M. (2004). Using simulators to assess laparoscopic competence: ready for widespread use?.

    Google Scholar 

  • Ferraro, N. M., Reamer, C. B., Reynolds, T. A., Howell, L. J., Moldenhauer, J. S., & Day, T. E. (2015). Capacity Planning for Maternal–Fetal Medicine Using Discrete Event Simulation. American journal of perinatology, 32(08), 761–770.

    Google Scholar 

  • Gaba, D. M. (2004). The future vision of simulation in health care. Quality and safety in Health care, 13(suppl 1), i2-i10.

    Google Scholar 

  • Gaba, D. M., & DeAnda, A. (1988). A comprehensive anesthesia simulation environment: re-creating the operating room for research and training. Anesthesiology, 69(3), 387–394.

    Google Scholar 

  • Gaba, D. M., Howard, S. K., Fish, K. J., Smith, B. E., & Sowb, Y. A. (2001). Simulation-based training in anesthesia crisis resource management (ACRM): a decade of experience. Simulation & Gaming, 32(2), 175–193.

    Google Scholar 

  • Gallagher, A. G., & Cates, C. U. (2004). Virtual reality training for the operating room and cardiac catheterisation laboratory. The Lancet, 364(9444), 1538–1540.

    Google Scholar 

  • General Medical Council. Education Committee. (1993). Tomorrow’s doctors: recommenda-tions on undergraduate medical education. London: General Medical Council.

    Google Scholar 

  • Gerolemou, L., Fidellaga, A., Rose, K., Cooper, S., Venturanza, M., Aqeel, A., & Khouli, H. (2014). Simulation-based training for nurses in sterile techniques during central vein catheterization. American Journal of Critical Care, 23(1), 40–48.

    Google Scholar 

  • Gettman, M. T., Blute, M. L., Chow, G. K., Neururer, R., Bartsch, G., & Peschel, R. (2004). Robotic-assisted laparoscopic partial nephrectomy: technique and initial clinical experience with DaVinci robotic system. Urology, 64(5), 914–918.

    Google Scholar 

  • Gordon, M. S. (1974). Cardiology patient simulator: development of an animated manikin to teach cardiovascular disease. The American journal of cardiology, 34(3), 350–355.

    Google Scholar 

  • Gordon, M. S., Forker, A. D., Gessner, I., McGuire, C., Mayer, J. W., Sajid, D. P. A., & Waugh, R. A. (1980). Teaching bedside cardiologic examination skills using “Harvey”, the cardiology patient simulator. Medical Clinics of North America, 64(2), 305–313.

    Google Scholar 

  • Gorman, L., Castiglioni, A., Hernandez, C., Asmar, A., Cendan, J., & Harris, D. (2015). Using preclinical high-fidelity medical simulations to integrate pharmacology and physiology with clinical sciences. Medical Science Educator, 25(4), 521–532.

    Google Scholar 

  • Gordon, J. A., Brown, D. F., & Armstrong, E. G. (2006). Can a simulated critical care encounter accelerate basic science learning among preclinical medical students? A pilot study. Simulation in healthcare, 1(Inaugural), 13–17.

    Google Scholar 

  • Grenvik, A., & Schaefer, J. (2004). From Resusci-Anne to Sim-Man: the evolution of simulators in medicine. Critical care medicine, 32(2), S56-S57.

    Google Scholar 

  • Griswold-Theodorson, S., Ponnuru, S., Dong, C., Szyld, D., Reed, T., & McGaghie, W. C. (2015). Beyond the simulation laboratory: a realist synthesis review of clinical outcomes of simulation-based mastery learning. Academic Medicine, 90(11), 1553–1560.

    Google Scholar 

  • Harden, R. M., & Gleeson, F. A. (1979). Assessment of clinical competence using an objective structured clinical examination (OSCE). Medical education, 13(1), 39–54.

    Google Scholar 

  • Hoot, N. R., LeBlanc, L. J., Jones, I., Levin, S. R., Zhou, C., Gadd, C. S., & Aronsky, D. (2008). Forecasting emergency department crowding: a discrete event simulation. Annals of emergency medicine, 52(2), 116–125.

    Google Scholar 

  • Hripcsak, G., Bakken, S., Stetson, P. D., & Patel, V. L. (2003). Mining complex clinical data for patient safety research: a framework for event discovery. Journal of biomedical informatics, 36(1), 120–130.

    Google Scholar 

  • Huang, G. C., McSparron, J. I., Balk, E. M., Richards, J. B., Smith, C. C., Whelan, J. S., & Smetana, G. W. (2016). Procedural instruction in invasive bedside procedures: a systematic review and meta-analysis of effective teaching approaches. BMJ quality & safety, 25(4), 281–294.

    Google Scholar 

  • Huang, T., Lan, L., Fang, X., An, P., Min, J., & Wang, F. (2015). Promises and challenges of big data computing in health sciences. Big Data Research, 2(1), 2–11.

    Google Scholar 

  • Hunt, E. A., Shilkofski, N. A., Stavroudis, T. A., & Nelson, K. L. (2007). Simulation: translation to improved team performance. Anesthesiology clinics, 25(2), 301–319.

    Google Scholar 

  • Ilgen, J. S., Ma, I. W., Hatala, R., & Cook, D. A. (2015). A systematic review of validity evidence for checklists versus global rating scales in simulation based assessment. Medical education, 49(2), 161–173.

    Google Scholar 

  • Isern, D., & Moreno, A. (2016). A systematic literature review of agents applied in healthcare. Journal of medical systems, 40(2), 43.

    Google Scholar 

  • Issenberg, SB., Mcgaghie, W. C., Petrusa, E. R., Lee Gordon, D., & Scalese, R. J. (2005). Features and uses of high-fidelity medical simulations that lead to effective learning: a BEME systematic review. Medical teacher, 27(1), 10–28.

    Google Scholar 

  • Johnson, O. A., Hall, P. S., & Hulme, C. (2016). NETIMIS: Dynamic Simulation of Health Economics Outcomes Using Big Data. PharmacoEconomics, 34(2), 107–114.

    Google Scholar 

  • Khanduja, V., Lawrence, J. E., & Audenaert, E. (2016). Testing the Construct Validity of a Virtual Reality Hip Arthroscopy Simulator. Arthroscopy: The Journal of Arthroscopic & Related Surgery.

    Google Scholar 

  • Keifenheim, K. E., Teufel, M., Ip, J., Speiser, N., Leehr, E. J., Zipfel, S., & Herrmann-Werner, A. (2015). Teaching history taking to medical students: a systematic review. BMC medical education, 15(1), 159.

    Google Scholar 

  • Kimura, T., Morita, A., Nishimura, K., Aiyama, H., Itoh, H., Fukaya, S., & Ochiai, C. (2009). Simulation of and training for cerebral aneurysm clipping with 3Dimensional models. Neurosurgery, 65(4), 719–726.

    Google Scholar 

  • Klevens, R. M., Edwards, J. R., Richards, C. L., Horan, T. C., Gaynes, R. P., Pollock, D. A., & Cardo, D. M. (2007). Estimating health care-associated infections and deaths in US hospitals, 2002. Public health reports, 122(2), 160–166.

    Google Scholar 

  • Kneebone, R. (2005). Evaluating clinical simulations for learning procedural skills: a theory-based approach. Academic medicine, 80(6), 549–553.

    Google Scholar 

  • Kohn, L. T., Corrigan, J. M., & Donaldson, M. S. (2002). To err is human: building a safer health system. National Academy of Science, Institute of Medicine, 6.

    Google Scholar 

  • Kolominsky-Rabas, P. L., Kriza, C., Djanatliev, A., Meier, F., Uffenorde, S., Radeleff, J., & Adamson, P. B. (2016). Health economic impact of a pulmonary artery pressure sensor for heart failure telemonitoring: a dynamic simulation. Telemedicine and e-Health, 22(10), 798–808.

    Google Scholar 

  • Konge, L., Arendrup, H., von Buchwald, C., & Ringsted, C. (2011). Virtual reality simulation of basic pulmonary procedures. Journal of bronchology & interventional pulmonology, 18(1), 38–41.

    Google Scholar 

  • Kotsis, S. V., & Chung, K. C. (2013). Application of See One, Do One, Teach One Concept in Surgical Training. Plastic and reconstructive surgery, 131(5), 1194.

    Google Scholar 

  • Larsen, C. R., Oestergaard, J., Ottesen, B. S., & Soerensen, J. L. (2012). The efficacy of virtual reality simulation training in laparoscopy: a systematic review of randomized trials. Acta obstetricia et gynecologica Scandinavica, 91(9), 1015–1028.

    Google Scholar 

  • Lind, B. (2007). The birth of the resuscitation mannequin, Resusci Anne, and the teaching of mouth to mouth ventilation. Acta Anaesthesiologica Scandinavica, 51(8), 1051–1053.

    Google Scholar 

  • Makiyama, K., Nagasaka, M., Inuiya, T., Takanami, K., Ogata, M., & Kubota, Y. (2012). Development of a patient specific simulator for laparoscopic renal surgery. International Journal of Urology, 19(9), 829–835.

    Google Scholar 

  • Marshall, D. A., Burgos-Liz, L., Pasupathy, K. S., Padula, W. V., IJzerman, M. J., Wong, P. K., & Osgood, N. D. (2016). Transforming healthcare delivery: Integrating dynamic simulation modelling and big data in health economics and outcomes research. PharmacoEconomics, 34(2), 115–126.

    Google Scholar 

  • McGaghie, W. C., Issenberg, S. B., Petrusa, E. R., & Scalese, R. J. (2010). A critical review of simulation based medical education research: 2003–2009. Medical education, 44(1), 50–63.

    Google Scholar 

  • McGaghie, W. C., Draycott, T. J., Dunn, W. F., Lopez, C. M., & Stefanidis, D. (2011a). Evaluating the impact of simulation on translational patient outcomes. Simulation in healthcare: journal of the Society for Simulation in Healthcare, 6(Suppl), S42.

    Google Scholar 

  • McGaghie, W. C., Issenberg, S. B., Cohen, M. E. R., Barsuk, J. H., & Wayne, D. B. (2011b). Does simulation-based medical education with deliberate practice yield better results than traditional clinical education? A meta-analytic comparative review of the evidence. Academic medicine: journal of the Association of American Medical Colleges, 86(6), 706.

    Google Scholar 

  • McGinnis, J. M., Stuckhardt, L., Saunders, R., & Smith, M. (Eds.). (2013). Best care at lower cost: the path to continuously learning health care in America. National Academies Press.

    Google Scholar 

  • Michelson, J. D., & Manning, L. (2008). Competency assessment in simulation-based procedural education. The American Journal of Surgery, 196(4), 609–615.

    Google Scholar 

  • Moorthy, K., Vincent, C., & Darzi, A. (2005). Simulation based training.

    Google Scholar 

  • Morey, J. C., Simon, R., Jay, G. D., Wears, R. L., Salisbury, M., Dukes, K. A., & Berns, S. D. (2002). Error reduction and performance improvement in the emergency department through formal teamwork training: evaluation results of the MedTeams project. Health services research, 37(6), 1553–1581.

    Google Scholar 

  • Nestel, D., Groom, J., Eikeland-Husebø, S., & O’donnell, J. M. (2011). Simulation for learning and teaching procedural skills: the state of the science. Simulation in Healthcare, 6(7), S10-S13.

    Google Scholar 

  • Newble, D. (2004). Techniques for measuring clinical competence: objective structured clinical examinations. Medical education, 38(2), 199–203.

    Google Scholar 

  • Opoku-Anane, J., Misa, N. Y., Li, M., Vargas, M. V., Chidimma, E., Robinson, J. K., & Moawad, G. (2015). Simulation Based Robotics Training to Test Skill Acquisition and Retention. Journal of Minimally Invasive Gynecology, 22(6), S33.

    Google Scholar 

  • Owen, H. (2012). Early use of simulation in medical education. Simulation in Healthcare, 7(2), 102–116.

    Google Scholar 

  • Park, J., MacRae, H., Musselman, L. J., Rossos, P., Hamstra, S. J., Wolman, S., & Reznick, R. K. (2007). Randomized controlled trial of virtual reality simulator training: transfer to live patients. The American journal of surgery, 194(2), 205–211.

    Google Scholar 

  • Passiment, M., Sacks, H., & Huang, G. (2011). Medical simulation in medical education: results of an AAMC survey. Washington, DC: Association of American Medical Colleges.

    Google Scholar 

  • Patrício, M. F., Julião, M., Fareleira, F., & Carneiro, A. V. (2013). Is the OSCE a feasible tool to assess competencies in undergraduate medical education?. Medical teacher, 35(6), 503–514.

    Google Scholar 

  • Pennathur, P. R., Cao, D., Sui, Z., Lin, L., Bisantz, A. M., Fairbanks, R. J., & Wears, R. L. (2010). Development of a simulation environment to study emergency department information technology. Simulation in healthcare: journal of the Society for Simulation in Healthcare, 5(2), 103.

    Google Scholar 

  • Phipps, M. G., Lindquist, D. G., McConaughey, E., O’brien, J. A., Raker, C. A., & Paglia, M. J. (2012). Outcomes from a labor and delivery team training program with simulation component. American journal of obstetrics and gynecology, 206(1), 3–9.

    Google Scholar 

  • Riley, W., Davis, S., Miller, K., Hansen, H., Sainfort, F., & Sweet, R. (2011). Didactic and simulation nontechnical skills team training to improve perinatal patient outcomes in a community hospital. The Joint Commission Journal on Quality and Patient Safety, 37(8), 357–364.

    Google Scholar 

  • Riojas, M., Feng, C., Hamilton, A., & Rozenblit, J. (2011). Knowledge elicitation for performance assessment in a computerized surgical training system. Applied Soft Computing, 11(4), 3697–3708.

    Google Scholar 

  • Rosen, K. R., McBride, J. M., & Drake, R. L. (2009). The use of simulation in medical education to enhance students’ understanding of basic sciences. Medical Teacher, 31(9), 842–846.

    Google Scholar 

  • Rodriguez-Paz, J., Kennedy, M., Salas, E., Wu, A. W., Sexton, J. B., Hunt, E. A., & Pronovost, P. J. (2009). Beyond “see one, do one, teach one”: toward a different training paradigm. Quality and Safety in Health Care, 18(1), 63–68.

    Google Scholar 

  • Rogers, G. M., Oetting, T. A., Lee, A. G., Grignon, C., Greenlee, E., Johnson, A. T., & Carter, K. (2009). Impact of a structured surgical curriculum on ophthalmic resident cataract surgery complication rates. Journal of Cataract & Refractive Surgery, 35(11), 1956–1960.

    Google Scholar 

  • Rotter, T., Kinsman, L., James, E., Machotta, A., Willis, J., Snow, P., & Kugler, J. (2012). The effects of clinical pathways on professional practice, patient outcomes, length of stay, and hospital costs: Cochrane systematic review and meta-analysis. Evaluation & the health professions, 35(1), 3–27.

    Google Scholar 

  • Rozenblit, J., & Sametinger, J. (2015, April). Models in healthcare simulation: typology and security issues. In Proceedings of the Symposium on Modeling and Simulation in Medicine (pp. 31–35). Society for Computer Simulation International.

    Google Scholar 

  • Rutherford-Hemming, T. (2012). Simulation methodology in nursing education and adult learning theory. Adult Learning, 23(3), 129–137.

    Google Scholar 

  • Ryan, J. R., Almefty, K. K., Nakaji, P., & Frakes, D. H. (2016). Cerebral aneurysm clipping surgery simulation using patient-specific 3D printing and silicone casting. World neurosurgery, 88, 175–181.

    Google Scholar 

  • Sametinger, J., & Rozenblit, J. (2016). Security Scores for Medical Devices. In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2016)-Volume (Vol. 5, pp. 533–541).

    Google Scholar 

  • Sant’Ana, G. M., Cavalini, W., Negrello, B., Bonin, E. A., Dimbarre, D., Claus, C., & Salvalaggio, P. R. (2016). Retention of laparoscopic skills in naive medical students who underwent short training. Surgical Endoscopy, 1–8.

    Google Scholar 

  • Sawyer, T., White, M., Zaveri, P., Chang, T., Ades, A., French, H., & Kessler, D. (2015). Learn, see, practice, prove, do, maintain: an evidence-based pedagogical framework for procedural skill training in medicine. Academic Medicine, 90(8), 1025–1033.

    Google Scholar 

  • Schijven, M. P., Jakimowicz, J. J., Broeders, I. A. M. J., & Tseng, L. N. L. (2005). The Eindhoven laparoscopic cholecystectomy training course—improving operating room performance using virtual reality training: results from the first EAES accredited virtual reality trainings curriculum. Surgical Endoscopy and other Interventional Techniques, 19(9), 1220–1226.

    Google Scholar 

  • Schout, B. M. A., Hendrikx, A. J. M., Scheele, F., Bemelmans, B. L. H., & Scherpbier, A. J. J. A. (2010). Validation and implementation of surgical simulators: a critical review of present, past, and future. Surgical endoscopy, 24(3), 536–546.

    Google Scholar 

  • Schwid, H. A., Rooke, G. A., Michalowski, P., & Ross, B. K. (2001). Screen-based anesthesia simulation with debriefing improves performance in a mannequin-based anesthesia simulator. Teaching and learning in medicine, 13(2), 92–96.

    Google Scholar 

  • Scott, D. J. (2006). Patient safety, competency, and the future of surgical simulation. Simulation in Healthcare, 1(3), 164–170.

    Google Scholar 

  • Seymour, N. E. (2008). VR to OR: a review of the evidence that virtual reality simulation improves operating room performance. World journal of surgery, 32(2), 182–188.

    Google Scholar 

  • Sedlack, R. E., & Kolars, J. C. (2004). Computer simulator training enhances the competency of gastroenterology fellows at colonoscopy: results of a pilot study. The American journal of gastroenterology, 99(1), 33–37.

    Google Scholar 

  • Shewokis, P. A., Shariff, F. U., Liu, Y., Ayaz, H., Castellanos, A., & Lind, D. S. (2016). Acquisition, retention and transfer of simulated laparoscopic tasks using fNIR and a contextual interference paradigm. The American Journal of Surgery.

    Google Scholar 

  • Sinha, N., Dauwels, J., Kaiser, M., Cash, S. S., Westover, M. B., Wang, Y., & Taylor, P. N. (2016). Predicting neurosurgical outcomes in focal epilepsy patients using computational modelling. Brain, aww299.

    Google Scholar 

  • Steinemann, S., Berg, B., Skinner, A., DiTulio, A., Anzelon, K., Terada, K., & Speck, C. (2011). In situ, multidisciplinary, simulation-based teamwork training improves early trauma care. Journal of surgical education, 68(6), 472–477.

    Google Scholar 

  • Vakharia, V. N., Vakharia, N. N., & Hill, C. S. (2016). Review of 3-dimensional printing on cranial neurosurgery simulation training. World neurosurgery, 88, 188–198.

    Google Scholar 

  • Zafari, Z., Bryan, S., Sin, D. D., Conte, T., Khakban, R., & Sadatsafavi, M. (2016). A Systematic Review of Health Economics Simulation Models of Chronic Obstructive Pulmonary Disease. Value in Health.

    Google Scholar 

  • Zeigler, B. P. (1976). Theory of modelling and simulation.

    Google Scholar 

  • Zendejas, B., Brydges, R., Wang, A. T., & Cook, D. A. (2013). Patient outcomes in simulation-based medical education: a systematic review. Journal of general internal medicine, 28(8), 1078–1089.

    Google Scholar 

  • Zendejas, B., Ruparel, R. K., & Cook, D. A. (2016). Validity evidence for the Fundamentals of Laparoscopic Surgery (FLS) program as an assessment tool: a systematic review. Surgical endoscopy, 30(2), 512–520.

    Google Scholar 

  • Zhu, Z., Hoon Hen, B., & Liang Teow, K. (2012). Estimating ICU bed capacity using discrete event simulation. International Journal of health care quality assurance, 25(2), 134–144.

    Google Scholar 

  • Ziv, A., Wolpe, P. R., Small, S. D., & Glick, S. (2003). Simulation based medical education: an ethical imperative. Academic Medicine, 78(8), 783–788.

    Google Scholar 

  • Ziv, A., Ben-David, S., & Ziv, M. (2005). Simulation based medical education: an opportunity to learn from errors. Medical teacher, 27(3), 193–199.

    Google Scholar 

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Prescher, H., Hamilton, A.J., Rozenblit, J.W. (2017). Systems Design, Modeling, and Simulation in Medicine. In: Mittal, S., Durak, U., Ören, T. (eds) Guide to Simulation-Based Disciplines. Simulation Foundations, Methods and Applications. Springer, Cham. https://doi.org/10.1007/978-3-319-61264-5_10

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