From Virtual Patients to AI-Powered Training: The Evolution of Medical Simulation

From Virtual Patients to AI-Powered Training: The Evolution of Medical Simulation

Carlos Enrique Mawyin-Muñoz ¹, Francisco Javier Salmerón-Escobar ²,
Javier Aquiles, Hidalgo-Acosta *³

1 Universidad de Granada/España; cmawyin10@hotmail.com.

2 Universidad de Granada/España; fsalmeron@ugr.es.

3 Universidad de Guayaquil/Ecuador;.

*Corresponding author: jahidalgoacosta@hotmail.com

ABSTRACT

Simulation is a learning technique or tool that allows medical professionals to have dynamic training for diagnosing and treating clinical-surgical pathologies. It can also be employed on the patient as a distraction to reduce pain and anxiety using virtual reality. The objective of this research was to determine the usefulness of medical simulation and its current advances, for which a bibliographic search was carried out of 58 medical articles obtained from databases such as PubMed, ScienceDirect, Mendeley, Latindex, published in the last 5 years that included observational studies, randomized studies, systematic reviews and meta-analyses referring to the research topic. It is concluded that the advances of simulation in medicine and the vast majority of medical specialties recommend implementing this technique for teaching, diagnosis, and treatment. In addition, it can also be used through virtual reality, artificial intelligence, and mixed reality to reduce stress in patients, being an advance in development; however, it was found that there are areas where the help of expert evaluators is indispensable, in topics such as resuscitation and physical rehabilitation where simulation did not surpass conventional treatment.

Keywords: Patient simulation; Training Simulation; Faculties of Medicine; Coroner; Medical Specialties.

INTRODUCTION

Simulation is a learning technique or tool that allows medical professionals to provide dynamic training for diagnosing and treating clinical-surgical pathologies, aiming to perfect technical skills and competencies necessary for health care. ^{1, 2}

Simulation can be used in medical learning and the evolution of the patient with positive results, ^{3, 4}for example, when virtual reality is used on the patient as a distraction to reduce pain and anxiety. ⁵

Simulation is developed in several high-tech fields such as artificial intelligence (AI), virtual reality, mixed reality (MR), intelligent robotics, cybersecurity, and virtualization, which can be applied in the medical field, ^{6, 7}improving clinical-surgical practices with a level of superiority compared to traditional education, ⁸ reducing the period of cognitive learning, skills or technical skills, enhancing the effectiveness of learning.⁹

Models with 3D printing are an innovation that allows the operator to generate safe practices, decreasing the risk of error and developing a better experience for the doctor. ^{10, 11,}and preparing him to treat a medical complication promptly.^{12, 13}

Training for managing diseases such as stroke can be carried out through simulation around diagnostic imaging and in the application of surgical medical procedures, mainly ^14-17in neurosurgery, whose simulated skills are of great importance for their continuous practices. ¹⁸ However, simulation can be used at any level of medicine, contributing to improving the processes of teaching, learning, evaluation, safety of care, and quality control, ^{19, 20}providing students and health professionals with the opportunity to learn about new advances and procedures, favoring the search for various areas with deficiencies in competencies, providing powerful intervention tools, to improve skills that require more training such as intensive care, cardiology, anesthesiology, hospitalization, delivery rooms, operating room, emergency room among others. ^{21, 22}

In situations of medical emergencies such as stroke, status epilepticus, coma, or respiratory failure, simulation is used to avoid errors during the administration of medications, resuscitation, management, diagnosis of seizures, and diagnostic imaging. ^{23, 24}

Among the advantages are the possibility of doing repetitions during the practice as many times as necessary, using the mistake virtually to the last consequences without ethical and legal repercussions, and allowing you to learn from the error without causing harm. It makes up for the lack of clinical experience and the failures of team coordination. It will enable learning in different circumstances or environments, from the simplest to the most complex, from the most common to the least frequent, and to receive real-time feedback. ^{25, 26}

Augmented reality in simulation is a technology that allows the operator to explore and manipulate three-dimensional multimedia environments, natural or artificial, generated by a computer to improve the knowledge and skills of health professionals and thus reduce the complications of highly complex procedures.^{27, 28}

OBJECTIVES: To determine the usefulness of medical simulation and its current advances.

METHODOLOGY

A structured review of articles was carried out with the research question: What is the usefulness of medical simulation and its current advances? Keywords and databases such as PubMed, ScienceDirect, Mendeley, Latindex, WOS, and Global Index Medicus, with articles published in the last 5 years, were used for the bibliographic search. Observational studies, randomized studies, systematic reviews, and meta-analyses referring to the research topic were chosen for the selection. A sub-analysis of the randomized clinical trials was carried out to improve the results of the available high-quality evidence that reported the P value with statistical significance in favor or against the medical simulation. Methodological quality was variable in the studies, some without conclusive results, heterogeneous populations, different techniques implemented, a comprehensive assessment enhanced with sub-analysis of randomized trials obtained from the search to suppress selection bias in the publication studies with reported positive and negative results, the heterogeneity observed in the medical simulation studies and the results obtained as well as the technological tools, diverse range of applications, environments and technologies affect the generalization of the results of the research, statistical heterogeneity was eliminated using the P value as the final variable.

RESULTS

The results of Tables 1 and 2 demonstrate the usefulness of simulation in procedures such as out-of-hospital cardiopulmonary resuscitation, otoscopy, endotracheal intubation of adults and neonates, ^29-31cricothyrotomy, training courses such as ACLS, and for clinical examinations presented a statistically significant benefit. Traditional methods such as expert mentoring or physical rehabilitation simulation need human presence.

Table 1. Medical Utilities of Simulation Practice. Research on simulation for medical training shows examples of how otoscopy, resuscitation, or intubation is performed. ^29-31

Figure 1. Types of simulators used in medical training. In panels a and b, you can see the animated lung that simulates the entry of air employing a mechanical ventilator, measures the values, and simulates a lung; this allows you to have an approximate vision of the entry and exit of air from the lungs, the simulation in mechanical ventilation is part of the training in critical medicine. Panel c operator interface and machine simulating a person's breathing on a mechanical ventilator, panel d training equipment for challenging airway simulation.

Table 2. Comparative studies on the usefulness of medical simulation.

Table 2 describes types of teaching with simulation, such as virtual reality, artificial intelligence, and mixed reality, compared to traditional methods. ^32-40

The results show that simulation is part of current medicine both in continuing medical education, diagnosis, treatment, after-hospital care, and patient education in pathologies in which simulation recreates complex scenarios; more research is needed on artificial intelligence, mixed reality or virtual reality and its application in certain areas where classical teaching is still necessary. The simulation of the quality of patient care demonstrated greater patient satisfaction and subsequent care in the intensive care unit. ⁴¹

In-hospital cardiopulmonary resuscitation simulation improves resuscitation performance in pediatric intensive care; training aspects included chest compressions, intra-arrest hemodynamics, and mechanics of cardiopulmonary resuscitation. ⁴²

Artificial intelligence (AI)-assisted on-screen simulations compared to breast self-examination simulations had a higher score (p < 0.05) for breast self-examination compared to AI training in participants with breast cancer, ⁴³showed that simulation with hybrid training of longer duration improves participants' skills in breast self-examination. ⁴⁴

In a study conducted in China on primiparous women who were given education with simulation of childbirth compared to regular prenatal care, they found that sham-based childbirth reduced fear of childbirth. ⁴⁵also observed that virtual reality simulation for visualizing green spaces reduces the physiological stress of pregnant women during labor. ⁴⁶

In surgery, combined training of both techniques, consisting of a mixture of traditional and simulation training, obtained better results (p < 0.0001). ⁴⁷In robotic surgery, simulation with virtual reality is helpful in training subspecialty robotic techniques. ⁴⁸

In patients operated on knee arthroplasty, simulation was performed with physiotherapy, with a higher percentage of falls, 19.4%, compared to classic physiotherapy, 14.6%. The simulation did not have good results; it could not overcome conventional methods. ⁴⁹

The simulation centers in university centers, which are included in the study program, give great importance to training in health sciences, ^{50, 51} which suggests an integration of simulation in specialized health training, mainly in laparoscopic surgery, simulating with non-biological material, providing good results in appendectomy and cholecystectomy. ⁵²

A systematic review observed that simulation provides the future professional with a look at what professional life means, gives him a physical representation of the complexity of certain vital situations, and offers the opportunity to refine medical techniques. ^{53, 54}

The relationship between stress-producing factors such as the external environment can be annulled by virtual reality techniques that act on the psychological state and suppress the stressor of error in medical practice, improving performance and making it an essential tool in medicine. ^{55, 56}

Simulation has been implemented in several countries for difficult situations, for example, in emergencies and disasters, managing to improve four domains of risk management that fail: 1) adequate personnel, 2) adequate material, 3) spaces, and 4) prepared warning systems. ⁵⁷

In a study conducted on patients during the preoperative period, simulation safely and effectively reduced anxiety. ⁵⁸

Figure 2. Randomized studies on medical simulation. Studies of high methodological quality that investigated medical simulation and its practical applications

Critical analysis of the evidence from all studies analyzed demonstrates statistical benefits in medical practice, e.g., learning, resuscitation training, examination, case analysis, feedback from learning, error reduction, and stress reduction, in various medical areas such as surgery, pediatrics, internal medicine, ophthalmology, emergency medicine, etc. no studies reported benefits or effects on mortality despite improving all the surgical skills of the participants, no data on reduction of operative complications were found. In addition, simulation technologies, such as artificial intelligence, mixed reality, or robotic technology, are still under development, and their impact on improving the quality of care is still unknown. More high-quality studies are needed with the real benefit of simulation; no benefits have been reported in reducing mortality since simulation does not replace usual medical training with actual practices. The ethical implications of medical simulation, patient safety, and data privacy could provide insight into the future of medical simulation, highlighting technologies such as artificial intelligence, virtual reality, and mixed reality and their potential to revolutionize healthcare education and training.

DISCUSSION

The analysis of high-quality evidence demonstrates that simulation provides significant benefits across various medical disciplines. As shown in Tables 1 and 2, simulation proves helpful in resuscitation, otoscopy, intubation, and cricothyrotomy, offering a statistically significant advantage over traditional methods like expert tutoring, which often require human presence. Simulation is becoming increasingly integral to modern medicine, aiding in continuing education, diagnosis, treatment, post-hospital care, and patient education by recreating complex scenarios.

Specifically, simulation has been shown to reduce anxiety³ and enhance learning in various contexts, including neurological examinations ⁷, anatomy education ⁹, and endoscopic discectomy. Furthermore, it facilitates skill acquisition in direct ophthalmoscopy and otoscopy, leading to fewer attempts and shorter intubation times in neonatal simulations. Notably, a mobile application for simulated pediatric cardiopulmonary resuscitation training significantly decreased errors.

Advanced simulation technologies, such as mixed reality for case practice and systems for clinical decision visualization, have shown promise in advanced cardiac life support by reducing medication delivery times. Artificial intelligence has also demonstrated the potential to improve sepsis team training and enhance patient satisfaction and post-ICU care. Moreover, virtual reality interventions have been beneficial for critically ill COVID-19 patients and have been shown to reduce cesarean section rates in obstetrics ⁴⁵.

While the evidence largely favors simulation, it's crucial to acknowledge certain limitations. Notably, the reviewed studies did not demonstrate a direct impact on mortality or operative complications. This highlights the need for further high-quality research to explore the full potential of simulation, particularly in areas where it has not yet reached statistical significance. Additionally, the ongoing development of simulation technologies, such as AI, mixed reality, and robotics, necessitates continued investigation into their impact on healthcare quality. Ethical considerations surrounding patient safety and data privacy must also be addressed as these technologies evolve.

CONCLUSIONS

Currently, advances in simulation in medicine and most medical specialties recommend implementing this technique for teaching, diagnosis, and treatment. It can also be used through virtual reality, artificial intelligence, and mixed reality to reduce stress in patients, being an advance in development; however, it was found that there are areas where the help of expert evaluators is indispensable, in topics such as resuscitation and physical rehabilitation where simulation did not surpass conventional treatment.

The review provides a comprehensive and critical overview of medical simulation in the digital age, contributing to the advancement of this rapidly evolving field, to effectively integrate medical simulation into practice, the economic costs of medical simulation, benefits of different simulation modalities and its impact on the allocation of healthcare resources is hindered by the little evidence to reduce mortality, complications, hospital times, reducing sepsis, which are the significant remains of these emerging technologies in medicine, factors such as infrastructure, training and the integration of new research plans need to be improved.

Constant feedback leads to improved technical skills and increased confidence, teaching surgical skills over time and participation in real-world scenarios, with the disadvantages of insufficient preparation time or surgical risks predominating, described by different researchers. In this situation, with scientific and technical development, the benefits of using simulators are that they minimize risks and offer safety to professionals. The simulator allows for unlimited and constant repetition, improving technical skills and increasing confidence even for the patient.

Contributions from Authors: All authors contributed to this manuscript: "Conceptualization, MC, ND, HJ; methodology, MC, ND, HJ; software, MC, ND, HJ; validation, MC, ND, HJ; formal analysis, MC, ND, HJ; research, HJ; resources, MC; data curation, MC; drafting: preparation of the original draft, HJ; writing: revision and editing, HJ; visualization, MC; supervision, SF; project management, MC; Acquisition of funds, HJ All authors have read and agree with the published version of the manuscript."

Funding: This research did not receive external funding; it was carried out with the authors' own resources.

Institutional Review Board Statement: Not applicable.

Informed Consent Statement: Not applicable.

Data Availability Statement: Research data are available from the corresponding author, databases, or web pages consulted through the DOI.

Acknowledgments: special thanks to the general teaching coordination of the HTMC.

Conflicts of interest: The authors declare no conflict of interest in the research.

REFERENCES

1.- Kyaw BM, Saxena N, Posadzki P, Vseteckova J, Nikolaou CK, George PP, Divakar U, Masiello I, Kononowicz AA, Zary N, Tudor Car L. Virtual Reality for Health Professions Education: Systematic Review and Meta-Analysis by the Digital Health Education Collaboration. J Med Internet Res. 2019 Jan 22;21(1):e12959. doi: 10.2196/12959.

2.- Zafar Z, Umair M, Faheem F, Bhatti D, Kalia JS. Medical Education 4.0: A Neurology Perspective. Cureus. 2022 Nov 19;14(11):e31668. doi: 10.7759/cureus.31668.

3.- Burmeister J, Dominello MM, Soulliere R, Baran G, Dess K, Loughery B, Jang H, Kim S, Jelich M, Laszewski P, Zelko C, Hamel LM. A Direct Patient-Provider Relationship With the Medical Physicist Reduces Anxiety in Patients Receiving Radiation Therapy. Int J Radiat Oncol Biol Phys. 2023 Jan 1;115(1):233-243. doi: 10.1016/j.ijrobp.2022.10.011.

4.- Plackett R, Kassianos AP, Kambouri M, Kay N, Mylan S, Hopwood J, Schartau P, Gray S, Timmis J, Bennett S, Valerio C, Rodrigues V, Player E, Hamilton W, Raine R, Duffy S, Sheringham J. Online patient simulation training to improve clinical reasoning: a feasibility randomised controlled trial. BMC Med Educ. 2020 Jul 31;20(1):245. doi: 10.1186/s12909-020-02168-4.

5.- Yalamanchili A, Sengupta B, Song J, et al. Quality of Large Language Model Responses to Radiation Oncology Patient Care Questions. JAMA Network Open. 2024 Apr;7(4):e244630. DOI: 10.1001/jamanetworkopen.2024.4630.

6.- Wu Q, Wang Y, Lu L, Chen Y, Long H, Wang J. Virtual Simulation in Undergraduate Medical Education: A Scoping Review of Recent Practice. Front Med (Lausanne). 2022 March 30;9:855403. doi: 10.3389/fmed.2022.855403.

7.- Han SG, Kim YD, Kong TY, Cho J. Virtual reality-based neurological examination teaching tool(VRNET) versus standardized patient in teaching neurological examinations for the medical students: a randomized, single-blind study. BMC Med Educ. 2021 Sep 15;21(1):493. doi: 10.1186/s12909-021-02920-4.

8.- Scott H, Griffin C, Coggins W, Elberson B, Abdeldayem M, Virmani T, Larson-Prior LJ, Petersen E. Virtual Reality in the Neurosciences: Current Practice and Future Directions. Front Surg. 2022 February 18;8:807195. doi: 10.3389/fsurg.2021.807195.

9.- Zhao J, Xu X, Jiang H, Ding Y. The effectiveness of virtual reality-based technology on anatomy teaching: a meta-analysis of randomized controlled studies. BMC Med Educ. 2020 Apr 25;20(1):127. doi: 10.1186/s12909-020-1994-z.

10.- Pergakis MB, Chang WW, Tabatabai A, Phipps MS, Neustein B, Podell JE, Parikh G, Badjatia N, Motta M, Lerner DP, Morris NA. Simulation-Based Assessment of Graduate Neurology Trainees' Performance Managing Acute Ischemic Stroke. Neurology. 2021 Dec 14;97(24):e2414-e2422. doi: 10.1212/WNL.0000000000012972.

11.- McCloskey K, Turlip R, Ahmad HS, Ghenbot YG, Chauhan D, Yoon JW. Virtual and Augmented Reality in Spine Surgery: A Systematic Review. World Neurosurg. 2023 May;173:96-107. doi: 10.1016/j.wneu.2023.02.068.

12.- Morris NA, Chang W, Tabatabai A, Gutierrez CA, Phipps MS, Lerner DP, Bates OJ, Tisherman SA. Development of Neurological Emergency Simulations for Assessment: Content Evidence and Response Process. Neurocrit Care. 2021 Oct;35(2):389-396. doi: 10.1007/s12028-020-01176-y.

13.- Yanni DS, Ozgur BM, Louis RG, Shekhtman Y, Iyer RR, Boddapati V, Iyer A, Patel PD, Jani R, Cummock M, Herur-Raman A, Dang P, Goldstein IM, Brant-Zawadzki M, Steineke T, Lenke LG. Real-time navigation guidance with intraoperative CT imaging for pedicle screw placement using an augmented reality head-mounted display: a proof-of-concept study. Neurosurg Focus. 2021 Aug;51(2):E11. doi: 10.3171/2021.5.FOCUS21209.

14.- Ghaednia H, Fourman MS, Lans A, Detels K, Dijkstra H, Lloyd S, Sweeney A, Oosterhoff JHF, Schwab JH. Augmented and virtual reality in spine surgery, current applications and future potentials. Spine J. 2021 Oct;21(10):1617-1625. doi: 10.1016/j.spinee.2021.03.018.

15.- Aljuwaiser S, Abdel-Fattah AR, Brown C, Kane L, Cooper J, Mostafa A. Evaluating the effects of simulation training on stroke thrombolysis: a systematic review and meta-analysis. Adv Simul (Lond). 2024 Feb 29;9(1):11. doi: 10.1186/s41077-024-00283-6.

16.- Ajmi SC, Advani R, Fjetland L, Kurz KD, Lindner T, Qvindesland SA, Ersdal H, Goyal M, Kvaløy JT, Kurz M. Reducing door-to-needle times in stroke thrombolysis to 13 min through protocol revision and simulation training: a quality improvement project in a Norwegian stroke centre. BMJ Qual Saf. 2019 Nov;28(11):939-948. doi: 10.1136/bmjqs-2018-009117.

17.- Casolla B. Simulation for Neurology training: Acute setting and beyond. Rev Neurol (Paris). 2021 Dec;177(10):1207-1213. doi: 10.1016/j.neurol.2021.03.008.

18.- Calleo V, Anderson J, Curtin P, Paolo W. High-fidelity simulation scenario: pediatric sulfonylurea overdose and treatment. MedEdPORTAL.2020;16:10965. https://doi.org/10.15766/mep_2374-8265.10965.

19.- Bedi MS, Raheja A, Katiyar V, Mishra S, Garg K, Narwal P, Ganeshkumar A, Sharma R, Tandon V, Milani D, Servadei F, Suri A, Kale SS. SimSpine: A Cost-Effective Spinal Endoscopy Training Prototype for Neurosurgical Residents Skills Training. World Neurosurg. 2023 May; 173:e683-e698. doi: 10.1016/j.wneu.2023.02.133.

20.- Tadlock MD, Olson EJ, Gasques D, Champagne R, Krzyzaniak MJ, Belverud SA, Ravindra V, Kerns J, Choi PM, Deveraux J, Johnson J, Sharkey T, Yip M, Weibel N, Davis K. Mixed reality surgical mentoring of combat casualty care related procedures in a perfused cadaver model: Initial results of a randomized feasibility study. Surgery. 2022 Nov; 172(5):1337-1345. DOI: 10.1016/J.Surg.2022.06.034.

21.- Dekhtyar M, Park YS, Kalinyak J, Chudgar SM, Fedoriw KB, Johnson KJ, Knoche CF, Martinez L, Mingioni N, Pincavage AT, Salas R, Sanfilippo F, Sozio SM, Weigle N, Wood S, Zavodnick J, Stern S. Use of a structured approach and virtual simulation practice to improve diagnostic reasoning. Diagnosis (Berl). 2021 Jul 12; 9(1):69-76. DOI: 10.1515/DX-2020-0160.

22.- Howell GL, Chavez G, McCannel CA, Quiros PA, Al-Hashimi S, Yu F, Fung S, DeGiorgio CM, Huang YM, Straatsma BR, Braddock CH, Holland GN. Prospective, Randomized Trial Comparing Simulator-based versus Traditional Teaching of Direct Ophthalmoscopy for Medical Students. Am J Ophthalmol. 2022 Jun;238:187-196. doi: 10.1016/j.ajo.2021.11.016.

23.- Aljuwaiser S, Abdel-Fattah AR, Brown C, Kane L, Cooper J, Mostafa A. Evaluating the effects of simulation training on stroke thrombolysis: a systematic review and meta-analysis. Adv Simul (Lond). 2024 Feb 29; 9(1):11. DOI: 10.1186/S41077-024-00283-6.

24.- Gough, M., Solomou, G., Khan, DZ et al. The Evolution of an SBNS-Accredited NANSIG Simulated Skills Workshop for Aspiring Neurosurgery Trainees: An Analysis of Qualitative and Quantitative Data. Acta Neurochir 162, 2323–2334 (2020). https://doi.org/10.1007/s00701-020-04325-6

25.- Zimmerman W, Pergakis M, Gorman E, Morris N. Scoping Review: Innovations in Clinical Neurology Education (S34.008). Neurology. 2022; 98: 18th https://doi.org/10.1212/WNL.98.18_supplement.1071

26.- Toro J et al. A Simulated Hospital in a COVID-19 Pandemic Environment for Undergraduate Neurology Students. (P12-6.003). Neurology. 2022; 98: 18. https://doi.org/10.1212/WNL.98.18_supplement.954

27.- Ishrat S, Chaurasia A, Husain Khan M. Computer simulation and practice of oral medicine and radiology [Internet]. Numerical Modeling and Computer Simulation. IntechOpen; 2020. Available in: http://dx.doi.org/10.5772/intechopen.90082

28.- Ganeshkumar A, Katiyar V, Singh P, Sharma R, Raheja A, Garg K, Mishra S, Tandon V, Garg A, Servadei F, Kale SS. Innovations in craniovertebral junction training: harnessing the power of mixed reality and head-mounted displays. Neurosurg Focus. 2024 Jan; 56(1):E13. DOI: 10.3171/2023.10.FOCUS23613.

29.- Tsai BM, Sun JT, Hsieh MJ, Lin YY, Kao TC, Chen LW, Ma MH, Wen-Chu C. Optimal paramedic numbers in the resuscitation of patients with out-of-hospital cardiac arrest: A randomized controlled study in a simulation setting. PLoS One. 2020 Dec 17;15(12):e0244400. doi: 10.1371/journal.pone.0244400.

30.- Fieux M, Zaouche S, Philouze P, Truy E, Hermann R, Tringali S. Low-fidelity otoscopy simulation and anatomy training: A randomized controlled trial. Eur Ann Otorhinolaryngol Head Neck Dis. 2021 Sep;138(4):231-234. doi: 10.1016/j.anorl.2020.09.010.

31.- Gizicki E, Assaad MA, Massé É, Bélanger S, Olivier F, Moussa A. Just-In-Time Neonatal Endotracheal Intubation Simulation Training: A Randomized Controlled Trial. J Pediatr. 2023 Oct;261:113576. doi: 10.1016/j.jpeds.2023.113576.

32.- Aldinc H, Gun C, Yaylaci S, Senuren CO, Guven F, Sahiner M, Kayayurt K, Turkmen S. Comparison of self versus expert-assisted feedback for cricothyroidotomy training: a randomized trial. BMC Med Educ. 2022 Jun 14;22(1):455. doi: 10.1186/s12909-022-03519-z.

33.- Siebert JN, Bloudeau L, Combescure C, Haddad K, Hugon F, Suppan L, Rodieux F, Lovis C, Gervaix A, Ehrler F, Manzano S; Pediatric Accurate Medication in Emergency Situations (PedAMINES) Prehospital Group. Effect of a Mobile App on Prehospital Medication Errors During Simulated Pediatric Resuscita-tion: A Randomized Clinical Trial. JAMA Netw Open. 2021 Aug 2;4(8):e2123007. doi: 10.1001/jamanetworkopen.2021.23007.

34.- Lacour M, Bloudeau L, Combescure C, Haddad K, Hugon F, Suppan L, Rodieux F, Lovis C, Gervaix A, Ehrler F, Manzano S, Siebert JN; PedAMINES Prehospital Group. Impact of a Mobile App on Para-medics' Perceived and Physiologic Stress Response During Simulated Prehospital Pediatric Cardiopul-monary Resuscitation: Study Nested Within a Multicenter Randomized Controlled Trial. JMIR Mhealth Uhealth. 2021 Oct 7;9(10):e31748. doi: 10.2196/31748.

35.- Malik R, Abbas JR, Jayarajah C, Bruce IA, Tolley N. Mixed Reality Enhanced Otolaryngology Case-Based Learning: A Randomized Educational Study. Laryngoscope. 2023 Jul;133(7):1606-1613. doi: 10.1002/lary.30364.

36.- Crabb DB, Hurwitz JE, Reed AC, Smith ZJ, Martin ET, Tyndall JA, Taasan MV, Plourde MA, Beattie LK. Innovation in resuscitation: A novel clinical decision display system for advanced cardiac life support. Am J Emerg Med. 2021 May;43:217-223. doi: 10.1016/j.ajem.2020.03.007.

37.- Stefanidis D, Aggarwal R, Rush RM Jr, Lee G, Blair PG, Hananel D, Park YS, Sweet RM, Wisbach GG, Sachdeva AK. Advanced Modular Manikin and Surgical Team Experience During a Trauma Simulation: Results of a Single-Blinded Randomized Trial. J Am Coll Surg. 2021 Aug;233(2):249-260.e2. doi: 10.1016/j.jamcollsurg.2021.04.029.

38.- Agana M, Vos D, Williams M, Baumgartner H, Soares N. Using Simulation in Training Pediatric Residents on Neonatal Abstinence Syndrome Scoring: An Experimental Study. Adv Neonatal Care. 2020 Oct;20(5):E85-E92. doi: 10.1097/ANC.0000000000000713.

39.- Liaw SY, Tan JZ, Bin Rusli KD, Ratan R, Zhou W, Lim S, Lau TC, Seah B, Chua WL. Artificial Intelligence Versus Human-Controlled Doctor in Virtual Reality Simulation for Sepsis Team Training: Randomized Controlled Study. J Med Internet Res. 2023 July 26;25:e47748. doi: 10.2196/47748.

40.- Liaw SY, Sutini, Chua WL, Tan JZ, Levett-Jones T, Ashokka B, Te Pan TL, Lau ST, Ignacio J. Desktop Virtual Reality Versus Face-to-Face Simulation for Team-Training on Stress Levels and Performance in Clinical Deterioration: a Randomised Controlled Trial. J Gen Intern Med. 2023 Jan;38(1):67-73. doi: 10.1007/s11606-022-07557-7.

41.- Vlake JH, van Bommel J, Wils EJ, Bienvenu J, Hellemons ME, Korevaar TI, Schut AF, Labout JA, Schreuder LL, van Bavel MP, Gommers D, van Genderen ME. Intensive Care Unit-Specific Virtual Reality for Critically Ill Patients With COVID-19: Multicenter Randomized Controlled Trial. J Med Internet Res. 2022 Jan 31;24(1):e32368. doi: 10.2196/32368.

42.- Cashen K, Sutton RM, Reeder RW, Ahmed T, Bell MJ, Berg RA, Bishop R, Bochkoris M, Burns C, Carcillo JA, Carpenter TC, Wesley Diddle J, Federman M, Fink EL, Franzon D, Frazier AH, Friess SH, Graham K, Hall M, Hehir DA, Horvat CM, Huard LL, Maa T, Manga A, McQuillen PS, Morgan RW, Mourani PM, Nadkarni VM, Naim MY, Notterman D, Palmer CA, Pollack MM, Sapru A, Schneiter C, Sharron MP, Srivastava N, Viteri S, Wolfe HA, Yates AR, Zuppa AF, Meert KL; Eunice Kennedy Shriver National Institute of Child Health and Human Development Collaborative Pediatrics Critical Care Research Network (CPCCRN); National Heart Lung and Blood Institute ICU-RESUScitation Project Investigators. Association of CPR simulation program characteristics with simulated and actual performance during paediatric in-hospital cardiac arrest. Resuscitation. 2023 Oct;191:109939. doi: 10.1016/j.resuscitation.2023.109939.

43.- Simsek-Cetinkaya S, Cakir SK. Evaluation of the effectiveness of artificial intelligence assisted interactive screen-based simulation in breast self-examination: An innovative approach in nursing students. Nurse Educ Today. 2023 Aug;127:105857. doi: 10.1016/j.nedt.2023.105857.

44.- Özdemir A, Ünal E. The effect of breast self-examination training on nursing students by using hybrid-based simulation on knowledge, skills, and ability to correctly evaluate pathological findings: Randomized Controlled Study. Nurse Educ Pract. 2023 Jan;66:103530. doi: 10.1016/j.nepr.2022.103530.

45.- Dai L, Shen Q, Redding SR, Ouyang YQ. Simulation-based childbirth education for Chinese primiparas: A pilot randomized controlled trial. Patient Educ Couns. 2021 Sep;104(9):2266-2274. doi: 10.1016/j.pec.2021.02.036.

46.- Sun Y, Li F, He T, Meng Y, Yin J, Yim IS, Xu L, Wu J. Physiological and affective responses to green space virtual reality among pregnant women. Environ Res. 2023 Jan 1;216(Pt 1):114499. doi: 10.1016/j.envres.2022.114499.

47.- Gholinejadzirmanlou M, Aghazadeh Attari AM, Sheikhalipour Z, Lotfi M, Ghaffarifar S, Qayumi K. An appropriate simulation-based training for surgical technology students. Nurse Educ Pract. 2023 Jul;70:103680. doi: 10.1016/j.nepr.2023.103680.

48.- Raison N, Harrison P, Abe T, Aydin A, Ahmed K, Dasgupta P. Procedural virtual reality simulation training for robotic surgery: a randomised controlled trial. Surg Endosc. 2021 Dec;35(12):6897-6902. doi: 10.1007/s00464-020-08197-w.

49.- Prvu Bettger J, Green CL, Holmes DN, Chokshi A, Mather RC 3rd, Hoch BT, de Leon AJ, Aluisio F, Seyler TM, Del Gaizo DJ, Chiavetta J, Webb L, Miller V, Smith JM, Peterson ED. Effects of Virtual Exercise Rehabilitation In-Home Therapy Compared with Traditional Care After Total Knee Arthroplasty: VERITAS, a Randomized Controlled Trial. J Bone Joint Surg Am. 2020 Jan 15;102(2):101-109. doi: 10.2106/JBJS.19.00695.

50.- Ramos G, Ardila Botero D. Percepción de la simulación clínica como didáctica en la enseñanza de hemorragia postparto en el Grado en Medicina. Rev Esp Edu Med [Internet]. 26 de enero de 2022 [citado 13 de julio de 2024];3(1). Disponible en: https://revistas.um.es/edumed/article/view/501861

51.- Padilla MJ, González J, Sarmiento F, Tripoloni D, Cohen Arazi L. Simulación clínica: Validación de encuesta de calidad y satisfacción en un grupo de estudiantes de Medicina. Rev Esp Edu Med [Internet]. 1 de diciembre de 2023 [citado 14 de julio de 2024];5(1). Disponible en: https://revistas.um.es/edumed/article/view/591511

52.- Flores-Funes D, Pellicer-Franco E, Flores-Pastor B, Moreno-Cascales M, Fernández-Villacañas-Marín M Ángel, Aguayo-Albasini JL. Una experiencia de integración de la Formación Sanitaria Especializada con la Universitaria de Posgrado: Entrenamiento por etapas en cirugía laparoscópica. Rev Esp Edu Med [Internet]. 27 de noviembre de 2020 [citado 14 de julio de 2024];1(2):82-9. Disponible en: https://revistas.um.es/edumed/article/view/454671.

53.- Escobar Suárez CA, Robalino Guerrero RA, Escobar Suárez MT, Terán Bejarano MJ. Simulación médica, enfoques al paciente híbrido. MedicienciasUTA [Internet]. 1 de enero de 2023 [citado 13 de julio de 2024];7(1):2-8. Disponible en: https://revistas.uta.edu.ec/erevista/index.php/medi/article/view/1923

54.- Yépez Yerovi F. Beneficios de la Simulación para el Perfeccionamiento Quirúrgico: Hacia una Formación más Eficaz y Segura. MedicienciasUTA [Internet]. 1 de abril de 2024 [citado 13 de julio de 2024];8(2):1. Disponible en: https://revistas.uta.edu.ec/erevista/index.php/medi/article/view/2405

55.- Finseth TT, Smith B, Van Steenis AL, Glahn DC, Johnson M, Ruttle P, Shirtcliff BA, Shirtcliff EA. When virtual reality becomes psychoneuroendocrine reality: A stress(or) review. Psychoneuroendocrinology. 2024 Aug;166:107061. doi: 10.1016/j.psyneuen.2024.107061.

56.- Eijlers R, Utens EMWJ, Staals LM, de Nijs PFA, Berghmans JM, Wijnen RMH, Hillegers MHJ, Dierckx B, Legerstee JS. Systematic Review and Meta-analysis of Virtual Reality in Pediatrics: Effects on Pain and Anxiety. Anesth Analg. 2019 Nov;129(5):1344-1353. doi: 10.1213/ANE.0000000000004165.

57.- Hasan MK, Nasrullah SM, Quattrocchi A, Arcos González P, Castro-Delgado R. Hospital surge capacity preparedness in disasters and emergencies: a systematic review. Public Health. 2023 Dec;225:12-21. doi: 10.1016/j.puhe.2023.09.017.

58.- Chiu PL, Li H, Yap KY, Lam KC, Yip PR, Wong CL. Virtual Reality-Based Intervention to Reduce Preoperative Anxiety in Adults Undergoing Elective Surgery: A Randomized Clinical Trial. JAMA Netw Open. 2023 Oct 2;6(10):e2340588. doi: 10.1001/jamanetworkopen.2023.40588.

Received: July 14, 2024 / Accepted: November 1, 2024 / Published: December 15, 2024

Citation: Mawyin, C.; Salmerón, F.; Hidalgo A. From Virtual Patients to AI-Powered Training: The Evolution of Medical Simulation. Bionatura Journal 2024; 1 (4) 7. http://dx.doi.org/10.70099/BJ/2024.01.04.7

Additional information Correspondence should be addressed to jahidalgoacosta@hotmail.com

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