Introduction

Simulation, defined broadly, refers to an artificial representation of a real-world object, event or process [1, 2]. The representation of organ systems and pathology through art, literature and theatre, can be viewed as the earliest predecessors to medical simulation [3].

The majority of studies to date discuss the impact of medical simulation in regard to education and training. Simulations [Figure 1] are increasingly supplanting didactic methods as a means of both learning and assessment. Professor Gaba, in the vanguard of ‘simulation-based medical education’ (SBE), has categorised the types of technology used [4][Figure 1].

Simulation-based medical education (SBE) is a fairly nascent field. In contrast, the field of medical research has long utilised simulation techniques (i.e. animal models, tissue cultures). Recently, some have attempted to define ‘simulation-based medical research’ (SBR) as a distinct research strategy [5, 6].

Simulations can also be therapeutic, which, for the purposes of this essay, will be termed ‘simulation-based medical treatment’ (SBT). Like SBE, SBT is also just emerging and its impact has yet to be ascertained. 

To assess the impact that SBR, SBE and SBT will have in advancing medicine it is helpful to understand the impact they have had thus far. Delineating these trends is important as immersive, high fidelity, integrated, AI-driven experiences erase our ‘banana peel suturing’ past [7, 8].

Figure 1: Types of technology used in simulation-based medical education (SBE). Data extracted from Gaba 2004, The future vision of simulation in healthcare [4].

What impact can simulation-based research (SBR) have in advancing medicine?

The aforementioned definition of simulation can be problematic when assessing its impact on medical research. Under this definition, seminal in vivo [9, 10] and in vitro studies [11] that constitute medical first principles, even the use of computational tools [12], would all be considered ‘simulation’. By this logic, nearly all medical research would fall under the umbrella of SBR, rendering this category obsolete. 

Nevertheless, recent studies have attempted to argue for SBR as a distinct research strategy, and to characterise its various designs [5, 6].  Although these design distinctions work adequately when applied to healthcare processes, and closely mirror the types identified by Gaba [Figure 1], they fail to encompass the array of simulations available (animal models, cell lines) when applied more generally to medical research. These difficulties in distinction are reflected in SBR reviews to date; definitions for SBR are nebulous and the rationale underlying the selection criteria for an ‘SBR study’ is obscure [5, 6].  

It can be argued that properly characterising SBR is important given its profound potential for streamlining healthcare processes. An example of SBR in action is the ‘SIMUL8 for Healthcare’ simulation software currently used, by John Hopkins [13] and the NHS [14] etc., to audit processes and test change. Yet it is nigh impossible for SBR to account for the inordinate number of variables that occur in reality, as such, results from SBR will rarely be conclusive.

 

What impact can simulation-based education (SBE) have in advancing medicine?

The first known use of patient actors for SBE was in 1963. Initially, Barrow’s use of standardised patients (SPs) to evaluate trainee performance was met with derision, making headlines: “Hollywood Invades USC Medical School” [15]. However, contemporaneous advances in andragogy [16], and the desertion of Locke’s ‘tabula rasa’ theory [17], led to rapidly growing support for experiential learning/deliberate practice [18].

Now, SBE has become a fundamental component of medical training, as dictated in ‘Outcomes for Graduates’ [19]. The 2014 ASPiH summary report found 60% of hospitals and 81% of higher education institutions use SPs [20]. 77% of hospitals and 80% of higher education institutions use simulator manikins[20]. Approximately half of all hospitals and higher education institutions possess an advanced sim suite [20]. 

The impacts of SBE [Table 1] in advancing medicine are often taken for granted, as demonstrated by a dearth of evidence in the literature. Additionally, heterogeneity in reporting, in simulation methods, in debriefing designs and in teaching topics has impeded data pooling for systematic review [21-24]. Nevertheless, outcomes are generally positive [21, 22].

 

Table 1: Impacts of SBE (simulation-based medical education) on stakeholders.

 

Increasing fidelity drives the evolution of SBE – manikins [32], ever more realistic, are now giving way to high-fidelity, virtual reality (VR) clinical settings, replete with interactive staff and patients.  HEE East of England mandates that all foundation year doctors receive VR training [33] and delivery is expanding to a further 18 NHS Trusts [31]. 

OMS (oxford medical simulation) is providing clinical training scenarios using VR, complete with automated, personal feedback. OMS is currently available in 80% of NHS trusts with 100,000+ sessions run in 2020 [34]. Moreover, OMS costs merely a tenth of traditional simulation methods [34]. 

Yet VR, like traditional means of simulation [Figure 1], requires the pre-empting of dialogue to script scenarios. These limitations can be largely overcome through the incorporation of artificial intelligence (AI). AI speech engines can communicate naturally with the user, responding to countless variations in questioning [35].  AI can also give highly granular feedback, e.g. on stethoscope placement, micro-expressions, and decision time [36, 37]. However, AI black box phenomena, whereby complex algorithms outpace us, are the latest concern [38].

 

What impact can simulation-based treatment (SBT) have in advancing medicine?

SBT is the use of simulation, namely VR, as a means of treatment. Arguably, the ‘placebo effect’ (can be therapeutic, although often unintended [39]), is its primitive ancestor.  

VR/simulation treatments are now being rolled out across NHS Trusts, heralding a novel field of care. One NHS pilot is offering VR treatment to patients suffering from acrophobia [40] following the results of a 2018 RCT demonstrating VR’s effectiveness [41]. Other pilots include VR use in youth mental health facilities [42] and in patients undergoing ‘awake’ limb surgery [43].  

 

Conclusion

The unforeseeable uptake of simulation in the 60s led to radical changes in medical education, yet heterogeneity in methods has made assessing the lasting impact difficult. Now, actors and manikins are being replaced by VR/AI technologies, the latter providing high-fidelity scenarios, lower costs, and quality feedback.

Although the epistemology underlying simulation is strong, quality evidence on impact is required. This can be somewhat resolved by reaching a consensus on terminology and selection criteria for SBR, SBE and the burgeoning field of SBT.
 

Bibliography

1. Al-Elq AH. Simulation-based medical teaching and learning. J Family Community Med. 2010;17(1):35-40.

2. Chakravarthy B. Medical Simulation in EM Training and Beyond. Academic Resident Newsletter of the Society of Academic Emergency Medicine. 2006.

3. Rosen KR. The history of medical simulation. Journal of Critical Care. 2008;23(2):157-66.

4. Gaba DM. The future vision of simulation in health care. Quality and Safety in Health Care. 2004;13(suppl_1):i2-i10.

5. Lamé G, Dixon-Woods M. Using clinical simulation to study how to improve quality and safety in healthcare. BMJ Simulation and Technology Enhanced Learning. 2020;6(2):87-94.

6. Vemuri S, Hynson J, Gillam L, Williams K. Simulation-Based Research: A Scoping Review. Qualitative Health Research. 2020;30(14):2351-60.

7. Benjamin L. Training in surgical skills. Community Eye Health. 2002;15(42):19-20.

8. Wagner GN, Cooke SJ. Methodological Approaches and Opinions of Researchers Involved in the Surgical Implantation of Telemetry Transmitters in Fish. Journal of Aquatic Animal Health. 2005;17(2):160-9.

9. Cossart Y. Tissue culture: unlocking the mysteries of viruses and cancer. 2007;334(suppl 1):s18-s.

10. Ericsson AC, Crim MJ, Franklin CL. A brief history of animal modeling. Mo Med. 2013;110(3):201-5.

11. Schwiening CJ. A brief historical perspective: Hodgkin and Huxley. The Journal of Physiology. 2012;590(11):2571-5.

12. Garcia P. Computer simulations and experiments: in vivo–in vitro conditions in biochemistry. Foundations of Chemistry. 2015;17(1):49-65.

13. Hamrock E, Paige K, Parks J, Scheulen J, Levin S. Relieving emergency department crowding: Simulating the effects of improving patient flow over time. Journal of Hospital Administration. 2014;4(1):43.

14. NHS Fife. Planning for Integrated Care11/07/2021 [cited 2021:[3 p.]. Available from: https://www.simul8healthcare.com/case-studies/SIMUL8-NHS-Fife-case-study.pdf.

15. Wallace P. Following the threads of an innovation: the history of standardized patients in medical education. Caduceus (Springfield, Ill). 1997;13(2):5-28.

16. Knowles MS. The Modern Practice of Adult Education, Andragogy versus Pedagogy. New York: Association Press; 1970. 376 p.

17. Locke J. An Essay Concerning Human Understanding. London: Oxford University Press; 1689.

18. Walker A, Leary H, Hmelo-Silver CE, Ertmer PA. Essential Readings in Problem-Based Learning. Exploring and Extending the Legacy of Howard S. Barrows: Purdue University Press; 2015.

19. General Medical Council. Outcomes for Graduates: Practical skills and procedures2019. Available from: https://www.gmc-uk.org/-/media/documents/practical-skills-and-procedures-a4_pdf-78058950.pdf?la=en&hash=9585CB5CA3DA386B768F70DAD3F62170C2E987E5.

20. Anderson, Baxendale, Scott, Mossley, Glover. The National Simulation Development Project: Summary Report. Association for Simulated Practice in Healthcare; 2014.

21. Kim J, Park JH, Shin S. Effectiveness of simulation-based nursing education depending on fidelity: a meta-analysis. BMC Med Educ. 2016;16:152.

22. Chernikova O, Heitzmann N, Stadler M, Holzberger D, Seidel T, Fischer F. Simulation-Based Learning in Higher Education: A Meta-Analysis. Review of Educational Research. 2020;90(4):499-541.

23. Zendejas B, Wang AT, Brydges R, Hamstra SJ, Cook DA. Cost: the missing outcome in simulation-based medical education research: a systematic review. Surgery. 2013;153(2):160-76.

24. Hippe DS, Umoren RA, McGee A, Bucher SL, Bresnahan BW. A targeted systematic review of cost analyses for implementation of simulation-based education in healthcare. SAGE Open Med. 2020;8:2050312120913451.

25. Lorello GR, Cook DA, Johnson RL, Brydges R. Simulation-based training in anaesthesiology: a systematic review and meta-analysis. Br J Anaesth. 2014;112(2):231-45.

26. Hong SJ, Bae HJ, Bang HL, Ferencsik L. Effects of Simulation-Based Education in Nursing Care for Stroke Patients. International Journal of Science and Research. 2019;8(11):1820 - 5.

27. Singer BD, Corbridge TC, Schroedl CJ, Wilcox JE, Cohen ER, McGaghie WC, et al. First-Year Residents Outperform Third-Year Residents After Simulation-Based Education in Critical Care Medicine. Simulation in Healthcare: The Journal of the Society for Simulation in Healthcare. 2013;8(2):67-71.

28. Shear TD, Greenberg SB, Tokarczyk A. Does training with human patient simulation translate to improved patient safety and outcome? Curr Opin Anaesthesiol. 2013;26(2):159-63.

29. Chang C-H. Medical simulation is needed in anesthesia training to achieve patient's safety. Korean Journal of Anesthesiology. 2013;64(3):204.

30. Balcombe J. The use of animals in higher education. Problems, Alternatives & Recommendations. Washington DC: Humane Society Press; 2000. Available from: https://www.humanesociety.org/sites/default/files/docs/use-of-animals-higher-education.pdf.

31. Pottle J. Virtual reality and the transformation of medical education. Future Healthc J. 2019;6(3):181-5.

32. Denson JS, Abrahamson S. A computer-controlled patient simulator. JAMA. 1969;208(3):504-8.

33. NHS Health Education England. Virtual Reality Simulation for Foundation Training East of England2020 12/07/2021:[11 p.]. Available from: https://heeoe.hee.nhs.uk/sites/default/files/virtual_reality_simulation_across_east_of_england_-_november_2020.pdf.

34. McKean M, Pottle J. NHS Innovation Accelerator Oxford Medical Simulation [Internet]2021. Available from: https://nhsaccelerator.com/portfolio/oxford-medical-simulation/.

35. Dolianiti F, Tsoupouroglou I, Antoniou P, Konstantinidis S, Anastasiades S, Bamidis P, editors. Chatbots in Healthcare Curricula: The Case of a Conversational Virtual Patient. Brain Function Assessment in Learning; 2020 2020//; Cham: Springer International Publishing.

36. Chan KS, Zary N. Applications and Challenges of Implementing Artificial Intelligence in Medical Education: Integrative Review. JMIR Medical Education. 2019;5(1):e13930.

37. Costiuc N. 2021 18/02/2021. [cited 2021]. Available from: https://www.healthysimulation.com/30417/ai-simulation-technology/.

38. Paranjape K, Schinkel M, Nannan Panday R, Car J, Nanayakkara P. Introducing Artificial Intelligence Training in Medical Education. JMIR Medical Education. 2019;5(2):e16048.

39. Beecher HK. The powerful placebo. J Am Med Assoc. 1955;159(17):1602-6.

40. NHS Oxford Health. Virtual reality treatment to be offered to NHS patients in Buckinghamshire and Oxfordshire2019 12/07/2021. Available from: https://www.oxfordhealth.nhs.uk/news/virtual-reality-treatment-to-be-offered-to-nhs-patients-in-buckinghamshire-and-oxfordshire/.

41. Freeman D, Haselton P, Freeman J, Spanlang B, Kishore S, Albery E, et al. Automated psychological therapy using immersive virtual reality for treatment of fear of heights: A single-blind, parallel-group, randomised controlled trial. The Lancet Psychiatry. 2018;5(8):625-32.

42. VanDerEyken L. Virtual reality treatment at new CAHMS unit2019 12/07/2021. Available from: https://www.cornwallft.nhs.uk/news/virtual-reality-treatment-at-new-cahms-unit-3027/.

43. NHS Northumbria Healthcare. The health trust using immersive experiences to guide patients through surgery2020 12/07/2021. Available from: https://www.northumbria.nhs.uk/the-health-trust-using-immersive-experiences-to-guide-patients-through-surgery/#b70a9e1b.

 

 

Image by Antonio Corigliano from Pixabay