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Record W2006775114 · doi:10.1186/s12913-014-0571-8

A mechanism for revising accreditation standards: a study of the process, resources required and evaluation outcomes

2014· article· en· W2006775114 on OpenAlexaff
David Greenfield, Mike Civil, Andrew Donnison, Anne Hogden, Reece Hinchcliff, Johanna Westbrook, Jeffrey Braithwaite

Bibliographic record

VenueBMC Health Services Research · 2014
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Quality and Management
Canadian institutionsInstitute on Governance
FundersRoyal Australian College of General Practitioners
KeywordsAccreditationStakeholderHealth careMedicineStakeholder engagementGovernment (linguistics)Agency (philosophy)Certification and AccreditationResource (disambiguation)Process (computing)Medical educationProcess managementBusinessPublic relationsPolitical scienceComputer scienceSociology

Abstract

fetched live from OpenAlex

BACKGROUND: The study objective was to identify and describe the process, resources and expertise required for the revision of accreditation standards, and report outcomes arising from such activities. METHODS: Secondary document analysis of materials from an accreditation standards development agency. The Royal Australian College of General Practitioners' (RACGP) documents, minutes and reports related to the revision of the accreditation standards were examined. RESULTS: The RACGP revision of the accreditation standards was conducted over a 12 month period and comprised six phases with multiple tasks, including: review methodology planning; review of the evidence base and each standard; new material development; constructing field trial methodology; drafting, trialling and refining new standards; and production of new standards. Over 100 individuals participated, with an additional 30 providing periodic input and feedback. Participants were drawn from healthcare professional associations, primary healthcare services, accreditation agencies, government agencies and public health organisations. Their expertise spanned: project management; standards development and writing; primary healthcare practice; quality and safety improvement methodologies; accreditation implementation and surveying; and research. The review and development process was shaped by five issues: project expectations; resource and time requirements; a collaborative approach; stakeholder engagement; and the product produced. The RACGP evaluation was that participants were positive about their experience, the standards produced and considered them relevant for the sector. CONCLUSIONS: The revision of accreditation standards requires considerable resources and expertise, drawn from a broad range of stakeholders. Collaborative, inclusive processes that engage key stakeholders helps promote greater industry acceptance of the standards.

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)0.436
metaresearch head score (Gemma)0.684
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.564
Threshold uncertainty score0.696

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4360.684
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0100.007
Science and technology studies0.0070.010
Scholarly communication0.0180.016
Open science0.0040.010
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.286
GPT teacher head0.616
Teacher spread0.330 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designQualitative
DomainEvaluation
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

Citations22
Published2014
Admission routes1
Has abstractyes

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