Do virtual patients prepare medical students for the real world? Development and application of a framework to compare a virtual patient collection with population data

M Urresti-Gundlach, D Tolks, C Kiessling, M Wagner-Menghin, A Härtl, I Hege, M Urresti-Gundlach, D Tolks, C Kiessling, M Wagner-Menghin, A Härtl, I Hege

Abstract

Background: An important aspect of virtual patients (VPs), which are interactive computer-based patient scenarios, is authenticity. This includes design aspects, but also how a VP collection represents a patient population and how a patient is presented in a VP scenario. Therefore, our aim was to analyze VP scenarios integrated into the combined internal medicine and surgery curriculum at the University of Munich (LMU) and compare the results with data from the population in Germany.

Method: We developed a coding framework with four main categories: patient data, patient representation, diagnoses, and setting. Based on the framework we analyzed 66 VP and compared the results with data from the German healthcare system.

Results: Especially in the categories of patient data and patient representation, the VPs presented an unrealistic image of the real world; topics such as unemployment, disability, or migration background were almost non-existent. The diagnoses of the VPs and the onset of diseases were comparable with the healthcare data.

Conclusions: An explanation for the lack of representativeness of the patient data and representation might be a trend to create VPs based on fictional patient stories with VP authors trying to minimize complexity and cognitive load for the students. We suggest raising awareness among VP authors concerning personalized representations of patients without overwhelming their students. Our framework can support educators to assess the authenticity and diversity of a VP collection.

Keywords: Authenticity; Healthcare system; Medical education; Virtual patients.

Conflict of interest statement

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
Age distribution of VPs (n = 61) and the German population in 2010 [38]
Fig. 2
Fig. 2
Overview of the average Body-Mass-Index (BMI) of the VPs and the German population (sample census 2013) [39]

References

    1. Effective Use of Educational Technology in Medical Education . Summary Report of the 2006 AAMC colloquium on educational technology. Washington, DC: Association of American Medical Colleges; 2007.
    1. Simonsohn A, Fischer M. Evaluation eines fallbasierten computergestützten Lernsystems (CASUS) im klinischen Studienabschnitt. Dtsch Med Wochenschr. 2004;129:552–556. doi: 10.1055/s-2004-820543.
    1. Posel N, McGee JB, Fleiszer DM. Twelve tips to support the development of clinical reasoning skills using virtual patient cases. Med Teach. 2015;37(9):813–818. doi: 10.3109/0142159X.2014.993951.
    1. Edelbring S, Broström O, Henriksson P, Vassiliou D, Spaak J, Dahlgren LO, Fors U, Zary N. Integrating virtual patients into courses: follow-up seminars and perceived benefit. Med Educ. 2012;46:417–425. doi: 10.1111/j.1365-2923.2012.04219.x.
    1. Forsberg E, Ziegert K, Hult H, Fors U. Assessing progression of clinical reasoning through virtual patients: an exploratory study. Nurse Educ Pract. 2016;16(1):97–103. doi: 10.1016/j.nepr.2015.09.006.
    1. Cook DA, Triola MM. Virtual patients: a critical literature review and proposed next steps. Med Educ. 2009;43:303–311. doi: 10.1111/j.1365-2923.2008.03286.x.
    1. Hege I, Kononowicz AA, Tolks D, Edelbring A, Kuehlmeyer K. A qualitative analysis of virtual patient descriptions in healthcare education based on a systematic literature review. BMC Med Educ. 2016;16(1):146. doi: 10.1186/s12909-016-0655-8.
    1. Salminen H, Zary N, Björklund K, Toth-Pal E, Leanderson C. Virtual patients in primary care: developing a reusable model that fosters reflective practice and clinical reasoning. J Med Internet Res. 2014;16(1):e3. doi: 10.2196/jmir.2616.
    1. Cook DA, Erwin PJ, Triola MM. Computerized virtual patients in health professions education: a systematic review and meta-analysis. Acad Med. 2010;85:1589–1602. doi: 10.1097/ACM.0b013e3181edfe13.
    1. Huwendiek S, Reichert F, Bosse HM, de Leng BA, van der Vleuten CPM, Haag M, Hoffmann GF, Tönshoff B. Design principles for virtual patients: a focus group study among students. Med Educ. 2009;43:580–588. doi: 10.1111/j.1365-2923.2009.03369.x.
    1. Kononowicz AA, Hege I. Virtual patients as a practical realisation of the e-learning idea in medicine. INTECH Open Access Publisher; 2010. Available from: .
    1. Shaffer D, Resnick M. “Thick” authenticity: new media and authentic learning. J Interact Learn Res. 1999;10(2):195–215.
    1. McBee E, Ratcliffe T, Picho K, Artino AR, Schuwirth L, Kelly W, et al. Consequences of contextual factors on clinical reasoning in resident physicians. Adv Health Sci Educ. 2015;20(5):1225–1236. doi: 10.1007/s10459-015-9597-x.
    1. Graber ML, Franklin N, Gordon R. Diagnostic error in internal medicine. Arch Intern Med. 2005;165(13):1493–1499. doi: 10.1001/archinte.165.13.1493.
    1. Martin JR. What should we do with a hidden curriculum when we find one? Curric Inq. 1976;6:135–151. doi: 10.1080/03626784.1976.11075525.
    1. Turbes S, Krebs E, Axtell S. The hidden curriculum in multicultural medical education: the role of case examples. Acad Med. 2002;77(3):209–216. doi: 10.1097/00001888-200203000-00007.
    1. Fischer M, Aulinger B, Kopp V. Implementierung von Computerlernfällen in das Curriculum der Inneren Medizin. GMS Z Med Ausbild. 2005;22(1):Doc12.
    1. Hege I, Radon K, Dugas M, Scharrer E, Nowak D. Web-based training in occupational medicine. Int Arch Occup Health. 2003;76:50–54.
    1. CASUS Virtual Patient System. . Accessed 22 Feb 2017.
    1. Statistical Federal Office. Distribution of age and nationality in the German population. 2015. . Accessed 22 Feb 2017.
    1. Survey in Germany about sexual orientation. . Accessed 22 Feb 2017.
    1. Statistical Federal Office. Disability based on age and gender. 2013. . Accessed 22 Feb 2017.
    1. Federal Employment Agency. Official report of the Federal Employment Agency 2014; 62(2). . Accessed 22 Feb 2017.
    1. Statistical Federal Office. Population based on migration background and gender. 2014. . Accessed 22 Feb 2017.
    1. Federal Goverment’s Commissioner on drug abuse. Drug and Addiciton report 2015. . Accessed 22 Feb 2017.
    1. Kohler M, Ziese T. Beiträge zur Gesundheitsberichterstattung des Bundes. Telefonischer Gesundheitssurvey des Robert Koch-Instituts zu chronischen Krankheiten und ihren Bedingungen. Berlin, 2004. . Accessed 22 Feb 2017.
    1. Robert Koch-Institut (2014) Chronisches Kranksein. Faktenblatt zu GEDA 2012: Ergebnisse der Studie "Gesundheit in Deutschland aktuell 2012" 2014, Berlin. . Accessed 22 Feb 2017.
    1. Gesundheitsberichterstattung des Bundes. Diagnostic data of the hospitals starting from 2000 (cases/deaths, days of care, average length of stay). Classification: years, place of treatment, age, sex, length of stay, ICD10. . Accessed 22 Feb 2017.
    1. Kim S, Phillips WR, Pinsky L, Brock D, Phillips K, Keary J. A conceptual framework for developing teaching cases: a review and synthesis of the literature across disciplines. Med Educ. 2006;40:867–876. doi: 10.1111/j.1365-2929.2006.02544.x.
    1. Pattison S, Dickenson D, Parker M, Heller T. do Case studies mislead about the nature of reality? J Med Ethics. 1999;25(1):42–46. doi: 10.1136/jme.25.1.42.
    1. Kamnin C, O'Sullivan P, Deterding R, Younger M. A comparison of critical thinking in groups of third-year medical students in text, video, and virtual PBL case modalities. Acad Med. 2003;78:204–211. doi: 10.1097/00001888-200302000-00018.
    1. Kenny NP, Beagan BL. The patient as text: a challenge for problem-based learning. Med Educ. 2004;38:1071–1079. doi: 10.1111/j.1365-2929.2004.01956.x.
    1. Posel N, Fleiszer D, Shore BM. 12 tips: guidelines for authoring virtual patient cases. Medical Teacher. 2009;31(8):701–708. doi: 10.1080/01421590902793867.
    1. Begg M. Virtual patients: practical advice for clinical authors using LABYRINTH. Clin Teach. 2010;7:202–205. doi: 10.1111/j.1743-498X.2010.00382.x.
    1. Electronic Virtual Patients (eViP). . Accessed 22 Feb 2017.
    1. World Health Organization. International Statistical Classification of Diseases and Related Health Problems 10th Revision. 2015. . Accessed 22 Feb 2017.
    1. Fiuncane P, Balakrishnan N. Is there a problem with the problems in problem-based learning? Med Educ. 2002;36(3):279–281. doi: 10.1046/j.1365-2923.2002.01150.x.
    1. Federal Agency for Political Education. German population based on age and gender. 2010. . Accessed 22 Feb 2017.
    1. Statistical Federal Office. Body-Mass-Index of the German population based on age and gender. 2013. . Accessed 22 Feb 2017.

Source: PubMed

Sponsorer och medarbetare

Medicinska tillstånd

Läkemedelsinterventioner

3
Prenumerera