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TeachMed Clinical reasoning learning with simulated patients Guy Bisson M.D., Faculté de médecine Froduald Kabanza Ph.D., Faculté des sciences, département.

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Presentation on theme: "TeachMed Clinical reasoning learning with simulated patients Guy Bisson M.D., Faculté de médecine Froduald Kabanza Ph.D., Faculté des sciences, département."— Presentation transcript:

1 TeachMed Clinical reasoning learning with simulated patients Guy Bisson M.D., Faculté de médecine Froduald Kabanza Ph.D., Faculté des sciences, département d'informatique

2 ‘ Indeed, the prime function of the physician is clinical reasoning ’ Kassirer

3 Plan Clinical reasoning : * what is it ? * what are the important components ? Simulations in medical education : why ? TeachMed

4 What? Complex process that incorporates elements of cognition, knowledge and metacognition To solve ill defined and often complex clinical problems

5 Models proposed in the litterature Hypothetico-deductive reasoning Pattern recognition Knowledge-reasoning integration

6 Hypothetico-deductive Generation of hypotheses based on clinical data and knowledge ( Inductive reasoning : specific to general ) Testing of these hypotheses through further inquiry ( Deductive reasoning : general to a particular case ) Backward reasonning of Patel,Groen and also Arocha. Use to solve complex case ( atypical or difficult ) Slower, more demanding and more detailed process

7 Pattern recognition Direct automatic retrieval of information from a well-structured knowledge base Enables conclusions to be reached in the face of imprecise data and limited premises Based mostly on categorization ( grouping ) and the use of prototype model ( construction of abstract associations ) ► based on experience Used in familiar cases by experienced clinicians Characterized by speed and efficiency

8 Knowledge-reasoning integration Clinical reasoning is not a separate skill that can be developed independantly of relevant professional knowledge and other clinical skills There is increasing evidence to support the importance of domain-specific knowledge and an organized knowledge base in clinical problem-solving expertise Domain-specific knowledge and skills in cognition ( critical, creative, reflective and logical/analytical thinking ) and metacognition are essential for effective thinking and problem solving

9 First important component: a well organized clinical knowledge base.

10 Lots of theories to explain how knowledge is organized and structured ( categories, prototypes, schemas, network,… ) Maturation through experience via metacognition Boshuizen and Schmidt: emphasize the parallel development of knowledge acquisition and clinical reasoning expertise ► cognitive maturation process where knowledge structure changes ( from a biomedical knowledge to structuring of knowledge around scripts ) ► increasing expertise in clinical reasoning Gruppen and Frohna: experts use their clinical knowledge a lot more than their bio-medical knowledge VS novices

11 Second important component : rapid generation of working hypotheses

12 Serve an essential function since they form a context within which further information gathering takes place Only a small number remain active at any given time ►take into account the limitations of the working memory ( prevent information overload ) Their quality is important since it is a strong predictor of a successfull resolution of the problem.

13 Third important component: problem formulation ‘ The role of problem formulation is the artful part of medicine ’ Pople 1982

14 The representation of the clinical problem changes throughout the clinical reasoning process and the initial representation may differ substantially from the final representation. Shares some important features with hypothesis generation : a mean of limiting the amount of information and knowledge that needs to be dealt with, another chief determinants of success in clinical reasoning. Once additional information has been acquired, it is integrated into the revised problem representation or ignored.

15 ‘ Although no one would doubt that cognitive skills are the basis of these tasks, medicine has developped few methods to enhance the acquisition and development of these problem solving skills ’ Kassirer

16 ‘ Facilitation of the clinical reasoning process for medical students therefore presents an educational challenge. How can students be assisted in developing their knowledge base in ill structured domains and how can the application of this knowledge base be facilitated ? ’ Bryce et al. Facilitating clinical reasoning through computer based learning and feedback, 1997

17 Teaching methods Clinical exposure : direct supervision, bedside, rounds Case presentation Lectures CRA Simulations

18 Most of the more effective methods are very time consuming and so very demanding on faculty availability

19 CRA Important teaching method in our institution One tutor, 8 students, 2 hrs, 2 / week Standardized cases in all major fields of medicine ( ~ 20 )

20 Limitations Low number of sessions Limitations in the number of variant that can be analyzed so the experience gain is limited

21 Simulations ‘ Changes in medical practice that limit patient availability and instructors’ time have resulted in poor physical diagnosis skills by learners at all levels. Advanced simulation technology, including the use of sophisticated multimedia systems, helps to address this problem ’ Issenberg, Simulation and new learning technologies Medical Teacher, 2001

22 Lots of interests Near real life situations Can make mistakes and learn from it Safe for patients Integration of declarative-procedural-conditionnal knowledge Can evaluate competencies

23 TeachMed Main educational objectives : * Standardized approach to CR * Help the construction of a well organized clinical knowledge base through feedback * Give exposure to more variant of a clinical case ( experience acquisition ) Complement the CRA sessions ( variants of the same cases ) Autonomous mode

24 TeachMed architecture Explicit cognitive actions


26 Cognitive interface



29 Future work Free text recognition for a full explicit cognitive trace


31 Links with knowledge base Links with a real CDR for data/case retrieval Real EHR as a GUI



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