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Record W2059914898 · doi:10.1186/1472-6963-12-329

The standard of healthcare accreditation standards: a review of empirical research underpinning their development and impact

2012· review· en· W2059914898 on OpenAlexaff
David Greenfield, Marjorie Pawsey, Reece Hinchcliff, Max Moldovan, Jeffrey Braithwaite

Bibliographic record

VenueBMC Health Services Research · 2012
Typereview
Languageen
FieldHealth Professions
TopicHealthcare Quality and Management
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsAccreditationCINAHLHealth careMedicineMedical educationScrutinyHealth administrationNursing researchMEDLINEMultidisciplinary approachHealth services researchHealth informaticsEmpirical researchNursingPublic healthPublic relationsPsychological interventionPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Healthcare accreditation standards are advocated as an important means of improving clinical practice and organisational performance. Standard development agencies have documented methodologies to promote open, transparent, inclusive development processes where standards are developed by members. They assert that their methodologies are effective and efficient at producing standards appropriate for the health industry. However, the evidence to support these claims requires scrutiny. The study's purpose was to examine the empirical research that grounds the development methods and application of healthcare accreditation standards. METHODS: A multi-method strategy was employed over the period March 2010 to August 2011. Five academic health research databases (Medline, Psych INFO, Embase, Social work abstracts, and CINAHL) were interrogated, the websites of 36 agencies associated with the study topic were investigated, and a snowball search was undertaken. Search criteria included accreditation research studies, in English, addressing standards and their impact. Searching in stage 1 initially selected 9386 abstracts. In stage 2, this selection was refined against the inclusion criteria; empirical studies (n = 2111) were identified and refined to a selection of 140 papers with the exclusion of clinical or biomedical and commentary pieces. These were independently reviewed by two researchers and reduced to 13 articles that met the study criteria. RESULTS: The 13 articles were analysed according to four categories: overall findings; standards development; implementation issues; and impact of standards. Studies have only occurred in the acute care setting, predominately in 2003 (n = 5) and 2009 (n = 4), and in the United States (n = 8). A multidisciplinary focus (n = 9) and mixed method approach (n = 11) are common characteristics. Three interventional studies were identified, with the remaining 10 studies having research designs to investigate clinical or organisational impacts. No study directly examined standards development or other issues associated with their progression. Only one study noted implementation issues, identifying several enablers and barriers. Standards were reported to improve organisational efficiency and staff circumstances. However, the impact on clinical quality was mixed, with both improvements and a lack of measurable effects recorded. CONCLUSION: Standards are ubiquitous within healthcare and are generally considered to be an important means by which to improve clinical practice and organisational performance. However, there is a lack of robust empirical evidence examining the development, writing, implementation and impacts of healthcare accreditation 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)0.067
metaresearch head score (Gemma)0.188
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.933
Threshold uncertainty score0.353

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0670.188
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0220.036
Science and technology studies0.0010.006
Scholarly communication0.0090.010
Open science0.0020.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.643
GPT teacher head0.709
Teacher spread0.066 · 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.

Study designSystematic review
DomainMethods
GenreReview

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

Citations123
Published2012
Admission routes1
Has abstractyes

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