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Record W2034726657 · doi:10.1111/acem.12155

Milestones: Quo Vadis?

2013· letter· en· W2034726657 on OpenAlexaff
Felix Ankel, Doug Franzen, Jason R. Frank

Bibliographic record

VenueAcademic Emergency Medicine · 2013
Typeletter
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMilestoneAccreditationGraduate medical educationContext (archaeology)MedicineStakeholderMedical educationPolitical sciencePublic relations

Abstract

fetched live from OpenAlex

Graduate medical education (GME) worldwide is undergoing a fundamental transition from a knowledge-based to a competency-based medical education (CBME) system.1 In the United States, the Next Accreditation System (NAS) of the Accreditation Council for Graduate Medical Education (ACGME) is using defined competency endpoints with intermediate milestones as the framework for CBME.2 Four articles in this month's issue of Academic Emergency Medicine illustrate the historical context of emergency medicine (EM) milestone development,3 describe the validation study used to refine the EM milestones,4 give us an example of how a multiorganizational group of stakeholders provides a roadmap for one milestone (PC-12),5 and remind us that GME milestones are on a continuum of development from undergraduate medical education, to GME, to continuing medical education.6 Milestones are descriptors of the expected abilities of physicians at defined stages of expertise development. Milestones are essential to a competency-based approach and are under development in many countries at this time. Beeson et al.3 describe the historical context of the EM milestone development. Representatives of eight stakeholder organizations comprised the EM milestone-working group (EM MWG). In a relatively short time, the EM MWG developed the first draft of milestones, and through collaboration with the ACGME Review Committee in Emergency Medicine, was able to incorporate EM milestones in the EM core program requirements. As an early adopter of NAS, EM has set the standard for the design, alignment, and integration of milestones into the educational framework of the future and can serve as a model for other specialties. Korte et al.4 describe the survey used as a validation study of the EM draft milestones. Despite a short 16-day survey period, the study received responses from over 60% of residencies on 24 EM subcompetencies and 255 milestones. Based on the results, the EM MWG eliminated one subcompetency and changed the number of subcompetency milestones to 227. Lewiss et al.5 describe the efforts of a multiorganizational committee composed of representatives from four stakeholder organizations to address EM milestone PC-12 (goal-directed focused ultrasound). This comprehensive article describes the historical perspective of emergency ultrasound (EUS) training, a description of core EUS skills needed by graduating EM residents, suggested blueprints for residency training, and a description of assessment tools. Santen et al.6 remind us that the NAS is on a continuum of professional development from medical student, to resident, to practicing physician. In their provocative article, the authors indicate that graduating medical students have not been fully taught or assessed on the Level 1 EM milestones requisite for entering EM residencies. The authors propose that responsibilities for Level 1 milestones be shared between medical schools and residencies. This, however, creates other challenges: how will medical school and residency obligations be determined for Level 1 milestone assessment? Will all medical schools coordinate among themselves with minimum Level 1 milestone requirements? How can program directors assure that incoming interns have met the Level 1 milestones at medical school graduation, unless standardized assessment tools exist for graduating medical students? Is there a need to develop entry-to-residency “bootcamps,” as other specialties have done?7 The Postgraduate Orientation Assessment (POA) is one potential approach.8 The POA is a tool to assess incoming residents in general competencies common to all specialties. In our opinion, pairing the general POA with specialty-specific assessment tools can ensure that all residents are at Level 1 milestones when starting residencies. Until medical schools develop reliable assessment tools for graduating medical students for Level 1 milestones for all specialties, we propose the adoption of a general POA tool plus specialty-specific Level 1 milestone assessments at the local residency institution as a key component of residency orientation. Where are we going? The future of CBME will require significant changes in the learning environment, resident assessment frequency, and faculty development. The learning environment will need to evolve to be based on outcomes and focused on the learner and be nonhierarchical.9 Assessment of professional competence will need to be based on multiple assessment methods, each with a minimum of 8 to 10 observations to ensure reliable inferences.10 Faculty will have to take on new roles to coach residents progressing through the milestones and assess their achievements.11 Effective faculty performance will be measured on the assessment skill set they demonstrate as much as the knowledge or procedural skills they may have.12 These changes will result in the transformation of education from a hierarchy focused on the teacher to a network focused on the learner. The resulting energy released by this transformation will serve as fuel for innovative networks of educators involved in CBME. EM has the room with a view on the changing health care system.13 It can also serve as the canary in the coal mine for the NAS's journey into CBME.

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)0.020
metaresearch head score (Gemma)0.062
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: Editorial · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.062
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0060.023
Scholarly communication0.0140.031
Open science0.0040.011
Research integrity0.0070.017
Insufficient payload (model declined to judge)0.0190.007

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 head0.055
GPT teacher head0.385
Teacher spread0.329 · 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
GenreEditorial

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

Citations8
Published2013
Admission routes1
Has abstractyes

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