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Clinical Problem Solving and the Clinical Presentation Curriculum

2000· letter· en· W2061672965 on OpenAlexaboutno aff
Henry Mandin, Peter H. Harasym, Wayne Woloschuk

Bibliographic record

VenueAcademic Medicine · 2000
Typeletter
Languageen
FieldMedicine
TopicClinical Reasoning and Diagnostic Skills
Canadian institutionsnot available
Fundersnot available
KeywordsProblem statementPresentation (obstetrics)Schema (genetic algorithms)CurriculumScheme (mathematics)Subject (documents)Computer scienceMedical diagnosisStatement (logic)Mathematics educationPsychologyMedicineManagement scienceEpistemologyMathematicsPedagogyInformation retrieval

Abstract

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The article “Clinical Problem Analysis (CPA): A Systematic Approach to Teaching Complex Medical Problem Solving”1 attracted our attention because of our own interest in the subject of teaching problem solving to medical students.2–6 The first of our publications2 is referenced by the authors as a representative presentation of “standard schemas for constructing a differential diagnosis.” The authors conclude their discussion of schemes with the statement that “differential diagnoses should be constructed mindfully and … inclusion of a disease or condition should always be justified on firmer grounds than merely because the schema says so.” This comment reveals that our advancement of scheme-based problem solving may have been misunderstood and requires further elaboration. Although the particular publication referenced by Custers et al. is devoted almost exclusively to a description of the “clinical presentation” curriculum, not problem solving, we summarize the purpose of “schemes” as follows: “Faculty experts organized and composed the terminal objectives in a manner designed to reveal to the students the scheme or road map useful in resolving the clinical presentations…. By arranging all necessary elements together with a scheme, the student can start linking clinical findings to each other with basic science explanations and use the scheme derived or suggested by the faculty experts to differentiate one cause from another.” The intent was for students to use schemes not only for solving problems, but initially to organize learning. In a subsequent article,3 which was not cited, we more extensively discussed the purpose of schemes: “The schemes, which are provided to Calgary's students in the ‘clinical presentation’ curriculum, indeed serve as a structure around which relevant clinical and basic science information is organized and learned…. Since the same scheme is utilized for both the inquiry process and the organization of the knowledge just acquired, the problem solving process reinforces the retention in long-term memory of the organization of the knowledge relevant to the specific problem.” We anticipated that readers of this second article would discern the dual purpose of schemes: first to organize learning and, second, to solve clinical problems. Even more important, we wanted to differentiate scheme-driven problem solving from hypothetico-deductive reasoning. That is, “Each problem requires a specific problem solving or search strategy. Methods for teaching problem solving cannot be based on the assumption of a universal, generic process.”3 The position that teaching cannot be based on the assumption of a universal, generic problem-solving strategy leads to an important difference between the “CPA's methodical approach” and the problem-solving strategy advocated in the clinical presentation curriculum. According to Elstein, Shulman, and Sprafka7 and others,8 problem solving is not content-independent. On the contrary, “organization of knowledge in memory is relevant. Diagnostic accuracy depends more on mastery of knowledge domain than problem solving strategy.” Yet, Custers et al. state, “CPA is an explicit analytic and systematic approach to clinical problem solving in the sense that it makes optimal use of content-independent (methodical) aspects of problem solving.” We are unaware of any evidence that suggests that a content-independent approach to problem solving may be advantageous to students' development of diagnostic competency. Although we agree with the authors that any process intended for the use of medical students should be explicit, the problem-solving strategy we believe to be most effective is knowledge-dependent. As we have stated elsewhere, “the decision was made to make [schemes] explicit simply because they do direct attention … provide scaffolding for assimilation, [and] therefore make learning possible.…”4 In summary, “[the] process presents a unique scheme at the beginning of each clinical presentation to guide acquisition of knowledge and problem resolution.”3 Similarly, Glaser9 recommends that novices use an organizational scheme as a scaffold to add new information and to provide a basis for problem solving. Students need separate and distinct strategies or schemes for each problem area (clinical presentation) because clinical problem solving is case-specific.7,8 Additional support for the use of knowledge-dependent, case-specific schemes was provided by Kushniruk et al., who found that experts used efficient strategies for discriminating among alternative hypotheses in an organized stepwise fashion while non-experts typically generated large numbers of possible diagnostic hypotheses belonging to widely different disease categories.10 As we have already stated, schemes have a dual purpose: to aid both learning and problem solving. Making them explicit is essential for both purposes. Although CPA is an explicit analytic approach, it is knowledge- and problem-independent. Thus, students are expected to develop expert knowledge structures and an expert approach to clinical case solving after repeated experience with CPA. Eventually, after repeated exposures, they would recognize patient problems immediately (pattern recognition). Given the theoretical, speculative basis of the CPA approach, we wonder whether students who are taught a process-directed and content-independent strategy to problem solving will be inclined to rely on the same strategy for all similar clinical problems rather than embracing the organized approach actually used by experts. In the clinical presentation model, all possible patient presentations are identified and listed beforehand. The knowledge structures and expert approaches to clinical case solving are made explicit. Practice of scheme-driven strategy is an integral part of the clinical presentation curriculum, but the schemes used for problem solving are already available for learning purposes in the first instance. Our research has shown that students respond very favorably to the use of scheme-based problem solving.11 The goals of CPA and scheme-driven inquiry in the clinical presentation curriculum may be similar. However, our belief that schemes or compiled knowledge structures are useful for both problem solving and learning resulted in a completely different curricular structure and problem-solving approach than that described by Custers et al.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.052
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.052
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.008
Scholarly communication0.0080.007
Open science0.0030.010
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0140.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.062
GPT teacher head0.432
Teacher spread0.370 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations11
Published2000
Admission routes1
Has abstractyes

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