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Record W4249461325 · doi:10.1093/pch/pxy054.125

THE PAEDIATRICIAN AS A LEADER: AN EDUCATIONAL INTERVENTION FOR HIGH-VALUE CARE

2018· article· en· W4249461325 on OpenAlexaboutno aff
Jessica L. Foulds, Hasu Rajani, Karen Forbes

Bibliographic record

VenuePaediatrics & Child Health · 2018
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare cost, quality, practices
Canadian institutionsnot available
Fundersnot available
KeywordsMedical educationThematic analysisHealth careMedicineAction planPsychologyNursingQualitative researchManagementPolitical science

Abstract

fetched live from OpenAlex

Abstract BACKGROUND The CanMEDS framework for physician competency defines necessary competencies of medical practice, laying the foundation for medical education and subsequent practice in Canada to meet patient needs. The role of Leader highlights the importance of quality improvement, stewardship, health care resource allocation and ability to apply evidence and management processes to facilitate cost-appropriate care. Educational innovations in this domain have not previously been described. OBJECTIVES To evaluate the impact of an educational intervention developed to foster stewardship of health care resources for paediatricians in training. DESIGN/METHODS An educational workshop on high-value care was created for general paediatric residents. Prior to workshop development, the study team procured local costing information from microbiology, general chemistry/laboratory, pharmacy, and radiology. During the workshop, individual, small group and interactive activities were used to explore clinical decision making and associated costs, radiation dosing, and non-monetary implications of care. A pocket-card reference was developed for use during the exercises. To assess the impact of the workshop, participants completed a post-workshop reflection asking them to identify lessons learned and an action plan for providing high-value care. Qualitative exploration of statements was conducted using thematic analysis; individual responses were coded and grouped into three overarching themes for both lessons learned and action plan. RESULTS Forty-three learners participated in the workshop. Post-workshop reflections yielded 93 lessons learned statements, and 67 action plan statements. Lessons learned were grouped into three themes: Scope, Content and Judgement Statements. Within Scope, most statements were general (80%) versus specific. Content areas most frequently cited included cost (61%), diagnostic imaging (28%) including radiation exposure (14%), and non-monetary costs of care (17%). Inferences about aspects of learnings, such as those referring to expense, value or waste, were labelled as Judgement Statements, and were present in 50% of the responses. Action plan statements were grouped into themes of Scope, Content and Action Words. Responses were again generally focused (87%). Most frequent Content subtheme responses were: tests (37%), non-monetary costs of care (21%), and diagnostic imaging (12%). Action words were grouped into seven categories as depicted in Figure 1, with Consider as most frequent (46%). CONCLUSION Reflections on non-monetary costs and action plans that consider how investigations might change management seemed to resonate with our single centre paediatric trainees. Longitudinal follow-up may help identify most impactful components of this educational workshop.

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)0.007
metaresearch head score (Gemma)0.016
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 score0.009
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0020.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.263
GPT teacher head0.526
Teacher spread0.263 · 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".

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Citations0
Published2018
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