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Record W6969322610 · doi:10.5281/zenodo.840165

Cross-Specialty Training In The Era Of Competency-Based Education.

2015· article· en· W6969322610 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2015
Typearticle
Languageen
FieldMedicine
TopicSurgical Simulation and Training
Canadian institutionsnot available
Fundersnot available
KeywordsSpecialtyTraining (meteorology)CurriculumArgument (complex analysis)Process (computing)AccreditationPublicationMedical knowledgeOrder (exchange)

Abstract

fetched live from OpenAlex

An article discussing a proposed curriculum to provide surgical training to family physicians is included in this issue of the journal.1 We decided to publish it with accompanying commentaries for and against the proposal in order to facilitate an informed debate. The argument for enhancing the surgical skills of family physicians is that they could provide surgical care for patients in remote locations, where surgeons may not be based.2 Those against the proposal question its premise; patients in remote areas have remarkably good access to surgical care and they expect the same standard of care as patients elsewhere.3 The proposal comes at a time when specialty training is undergoing change. Rather than designing a training program as a time-based process for the sequential acquisition of knowledge and skill, it is suggested that progression of surgical training should depend on the acquisition of defined competencies. The Royal College of Physicians and Surgeons of Canada has given this transformation the name "competence by design" (CBD). While CBD implementation currently deals with postgraduate medical education (residency), the intention is to include the postcertification career training currently referred to as "continuing professional development" (CPD). One promised aspect of CBD is that it will permit surgeons to tailor their education to fit the practice required in their particular situations. Some surgeons will restrict their practices to areas of special interest (e.g., arthroplasty, hepatobiliary surgery); others will undertake cross-specialty training to expand their competencies (e.g., cesarian section performed by general surgeons). Where then does this proposal to train family physicians to undertake major surgery fit in the era of CBD? Competence by design removes the element of time but does not alter the other fundamentals of training. All course modules have 4 elements: prerequisites, a learning phase, testing and maintenance of competence. Currently, the prerequisites for a trainee to undertake advanced surgical training is successful completion of the Principles of Surgery (POS) course and examination. While some credit should be given to certified family physicians, the proposal would need to include additional training and testing in the fundamentals of surgery to meet the validated prerequisite standard. Competence by design will accommodate a practising surgeon learning a new procedure where established surgical skills facilitate the acquisition of new skills. On the other hand, there is no reason to believe that nonsurgeons, even if they have completed POS, would become competent more quickly than residents in training. If this is true, the curriculum for enhanced surgical skills cannot be completed within a year. More likely it would take the same effort and time as a conventional surgical training program — without the determined checks and balances of a certified training program. Patients and regulatory authorities expect physicians with surgical privileges to have passed standard tests of competence. Testing of cross-specialty competencies should remain within the responsibility of the subspecialty. Testing the wide range of competencies proposed in this curriculum will be logistically difficult. Training and testing within the time frame proposed is impossible. Finally, maintenance of competence has 3 elements: practice of the specific skill, practice of related skills and CPD. The premise of the proposal is that insufficient volumes of work are available in remote areas to maintain conventionally trained surgeons. In this situation, the family physician will be unable to maintain competence by practice of the specific or related skills and will have to spend an inordinate amount of time undertaking coursebased CPD. Provision of surgical services in a country as large as Canada requires collaboration between several levels of government, hospital authorities and several medical specialties. While the lack of a surgeon is often cited as the reason why a patient has to be transferred, the true logistical evaluation is always more complex. Surgeons who undertake care have to be prepared to deal with unexpected, difficult intraoperative findings and complex postoperative courses. Adages such as "preparing for the worst is better than hoping for the best" and "the last thing a surgeon learns is when not to operate" have stood the test of time. Good care of residents of remote areas must include close collaboration and

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)0.017
metaresearch head score (Gemma)0.039
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.039
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.006
Scholarly communication0.0050.009
Open science0.0020.007
Research integrity0.0090.011
Insufficient payload (model declined to judge)0.0080.001

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 head0.091
GPT teacher head0.330
Teacher spread0.240 · 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
GenreEmpirical

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

Citations0
Published2015
Admission routes1
Has abstractyes

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