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Record W1973854032 · doi:10.1002/chp.1340200109

Continuing medical education-driven skills acquisition and impact on improved patient outcomes in family practice setting

2000· article· en· W1973854032 on OpenAlexaboutno aff
Nicholas Bellamy, Laurence D. Goldstein, Rory A. Tekanoff

Bibliographic record

VenueJournal of Continuing Education in the Health Professions · 2000
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal Disorders and Rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePreceptorPsychological interventionCurriculumIntervention (counseling)Physical therapyWOMACContinuing medical educationMedical educationFamily medicineInclusion (mineral)NursingPsychologyAlternative medicineContinuing educationOsteoarthritis

Abstract

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BACKGROUND: An abundance of educational theory, design, and delivery of continuing medical education (CME) learning interventions, including their impact on learners, are described in the health and social sciences literature. However, establishing a direct correlation between the acquisition of new skills by learners and patient outcomes as a result of a planned CME learning intervention has been difficult to demonstrate. METHODS: The learning intervention described here tested the impact of an injection skills-acquisition program for family physicians treating osteoarthritis of the knee by measuring patient outcomes using the pain and function subscales of the Western Ontario and McMaster (WOMAC) 3.0 osteoarthritis index, a standardized and fully validated patient-centered outcome measurement. It was hypothesized that patients of family physicians who participated in this skills-acquisition CME program would benefit from treatment administered by their physician during the time between injection skills acquisition to 6 weeks post-injection. Inclusion of a validated health status measure administered pre- and post-injection in addition to more traditional faculty and participant program evaluations was deemed necessary to test this hypothesis. Rheumatology, orthopedic surgery, and family medicine specialists from across Canada were invited to contribute to the planning, curriculum elaboration, and delivery of the viscosupplement injector preceptorship (VIP) program. Thirty-nine orthopedic and rheumatology specialists agreed to serve as expert faculty and participated in training 474 Canadian family and general practitioners over 8 months. The learning intervention involved a review of pertinent literature by a local preceptor and a summary of recommendations of the planning committee, followed by demonstration of injector skills and then supervised practice with patients, who received hylan G-F 20 (Synvisc, Ridgefield, NJ) usually in the offices of the family physicians. The pain and function subscales of the WOMAC 3.0 questionnaire were self-administered to each patient in their physician's office, prior to receiving their joint injection and again at or near 6-weeks post-injection. Data were analyzed in the Department of Epidemiology and Biostatistics at The University of Western Ontario, London, ON. RESULTS: Clinically important statistically significant improvements in pain and physical function were noted in patients who received viscosupplementation treatment from family physicians who had recently acquired the necessary injection skills. Approximately three-quarters of the patients experienced a reduction in pain and an improvement in physical function of at least 20%. IMPLICATIONS: These results suggest a positive relationship between acquisition of a new skill by learners and improved patient outcomes as a result of this planned CME learning intervention.

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)0.002
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.006
GPT teacher head0.389
Teacher spread0.383 · 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 designObservational
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

Citations36
Published2000
Admission routes1
Has abstractyes

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