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Record W48881790

The status of accreditation in primary care.

2013· article· en· W48881790 on OpenAlexaff
Maeve O'Beirne, Karen Zwicker, Pam D Sterling, Jana Lait, Helen Robertson, Nelly D. Oelke

Bibliographic record

VenuePubMed · 2013
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Quality and Management
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAccreditationHealth careGovernment (linguistics)MedicineNursingMedical educationPrimary careQuality (philosophy)Family medicineBusinessPublic relationsPolitical science
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: One method utilised to improve the quality of health care is accreditation. Although accreditation has been extensively used in the acute care sector, its presence in primary care is limited and so is our understanding of its nature, uptake and associated outcomes. Because acute care and primary care environments are vastly different, our understanding of acute care accreditation cannot simply be translated to primary care. AIM: The purpose of this paper was to explore the current state of primary care accreditation. METHODS: An extensive search was completed examining peer-reviewed and grey literature. In addition, interviews with key stakeholders involved in primary care accreditation were undertaken. RESULTS: From the 501 reviewed abstracts, 62 papers were used in this review in addition to 72 sources from grey literature. Eight interviews were also held with key informants. CONCLUSIONS: In this review of the available literature of accreditation within primary care, it was found that accreditation in this sector is generally non-government funded and voluntary with some countries offering financial incentives. It was evident that there is a dearth of research on the nature and uptake of accreditation in this sector, along with how accreditation affects outcomes of care, whether it is an effective method to improve quality, perceptions of care, healthcare utilisation and costs. These findings imply that further research is required to examine the possible impact accreditation may have on health care within primary care.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.924
Threshold uncertainty score0.741

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.106
GPT teacher head0.396
Teacher spread0.290 · 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 teacher head, 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

Citations43
Published2013
Admission routes1
Has abstractyes

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