1. Faculty of Health, Medicine and Life Sciences
School of Health Professions Education
Prof. dr. Albert Scherpbier
The combination of virtual patients and small
group discussions to promote reflective practice
Bas de Leng, PhD
ICVP London, 26 April 2010
3. Faculty of Health, Medicine and Life Sciences
7
19
28
46
Factors
No fault
Only system
Only cognitive
Both system and
cognitve
Medical errors
Diagnostic errors: 5-15% of medical diagnosis
Taxonomy of diagnostic error (Graber,2005):
– No-fault errors
– System-related errors
– Cognitive errors
Cognitive errors contribute
to 75% of all diagnostic errrors
‘Premature closure’ most
common cognitive error
4. Faculty of Health, Medicine and Life Sciences
Education to prevent cognitive errors
Relationships between reliability and effort of diagnostic
decision making (Graber, 2009)
Effort
Accuracy
Low High
Less
More
Deductive
reasoning
Expert
thinking
Monitoring,
reflection
Expert
thinking
Pre-expert
reasoning:
heuristics
ideas for educational approaches
5. Faculty of Health, Medicine and Life Sciences
Increase expertise
Deliberate practice with coaching and feedback by
more accomplished professionals (Ericsson, 2003)
Access to a large numbers of patients with similar
symptoms for which the correct diagnosis is
validated
Virtual patients can supplement real patient
encounters
6. Faculty of Health, Medicine and Life Sciences
Learn to apply reflective thinking
Learning to:
Recognize and understand the most likely
diagnostic pitfalls (Croskerry, 2003)
Use a checklist for the diagnostic process including
‘reflection’.
7. Faculty of Health, Medicine and Life Sciences
Clinical reasoning sessions
Ingredients:
Virtual patients based on real cases in which ‘premature
closure’ had occurred
Procedure to induce reflective diagnostic reasoning
(Mamede, 2008)
8. Faculty of Health, Medicine and Life Sciences
Clinical reasoning sessions
Procedure:
All residents simultaneously worked out the same virtual
patient
And the end of the work-up they had a moderated
discussion on their clinical reasoning
The logged actions and their notes were starting points for
the discussion
9. Faculty of Health, Medicine and Life Sciences
Evaluation of perceptions
Two student questionnaires:
1. Experiences with the use virtual patients. With 12 statements on:
Authenticity
Professional approach
Coaching
Learning effect
Overall judgment
1. Experiences with the integration of virtual patients. With 20 statements
on:
Teaching presence
Cognitive presence
Social presence
Learning effect
Overall judgment
10. Faculty of Health, Medicine and Life Sciences
Conclusion
Residents perceived a session combining individual virtual
patient workup with small group discussions as a
valuable learning activity for clinical reasoning.
The clinical supervisor found the presented teaching
approach feasible for the medical specialist training at the
workplace.
11. Faculty of Health, Medicine and Life Sciences
Future research
Evaluation of clinical reasoning sessions with VPs on 3rd
and
4th
level of Kirkpatrick:
Do they learn clinical reasoning and reflective practice
from this activity?
Do the learning outcomes transfer to clinics and wards?
Editor's Notes
No fault: deception, missed appointment, atypical disease presentation
Sytem related: communication of test results, expertise unavailable, no or to long procedures, technical failure of equipment.
Cognitive: faulty data gathering, faulty synthesis of information available (verification) , inadequate knowledge or skills is infrequent cause.
So cognitive factors contributed in about 75% of the cases of diagnostic error
Training of communication and team skills. In healthcare there are frequent shift changes. Handoffs from one provider to another are critical moments.
Premature closure is the failure to continue considering reasonable alternatives after an initial diagnosis is reached. With ‘premature closure’ a diagnosis is established early on in the diagnostic process and all subsequent diagnostic efforts (or even thinking) stops.
Novices use knowledge of the basic and clinical sciences for deductive reasoning to solve clinical problems. This costs a lot of effort and is highly error prone.
Expert with extensive knowledge base and experience often apply pattern recognition and solve clinical problems with little effort and high accuracy.
In their grows to the expert level clinicians will use a combination of both and the intermediate levels of effort and accuracy.
Educational by training to reflect, keeping a comprehensive approach and considering alternatives and recognizing the shortcomings of heuristics. And with this checking approach catch errors.
Extensive experience alone is not enough. Extensive practice combined with formative feedback (Ericsson 2008)
They must continuously counteract the tendency towards automaticity and deliberately construct training situations to exceed their current level of performance.
Access to large numbers of patients with similar symptoms for which the correct diagnosis is validated and with immediate expert feedback.
Large library with indexed virtual patients:
Selection of specific cases;
Deliberate sequencing of cases to ensure an ideal case mix;
Revisiting cases from different perspectives.
1) After the investigations they were asked to write down the first diagnosis that came to their mind and after this to go back to the patient record and list findings that:
Supported their diagnosis
Opposed their diagnosis
Would be expected if their diagnosis was true but which were not encountered
2) Subsequently they were asked to list alternative diagnoses and to answer the same 3 questions for each of these
3) Finally they we asked to rank their diagnoses based on the personal analysis
Aggregation tool for logged actions
Students’ questionnaires developed in the e-vip project
1) To evaluate their experiences with virtual patients. It contains twelve 5-point Likert Scale statements on the issues:
Authenticity
Professional approach
Coaching
Learning effect
Overall judgment
b) Students’ questionnaire to evaluate their experiences their experiences with the integration of virtual patients. It contains twenty 5-point Likert Scale statements on the issues:
Teaching presence
Cognitive presence
Social presence
Learning effect
Overall judgment
