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Record W6958977362 · doi:10.6084/m9.figshare.c.5935319

Determinants of the de-implementation of low-value care: a multi-method study

2022· other· en· W6958977362 on OpenAlexaff

Bibliographic record

VenueFigshare · 2022
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicWheat and Barley Genetics and Pathology
Canadian institutionsAlberta Health ServicesDalhousie UniversityUniversity of TorontoUniversity of AlbertaUniversity of CalgaryUniversity of Ottawa
Fundersnot available
KeywordsFacilitatorThematic analysisContent analysisGrey literatureHealth careSystematic reviewMEDLINERaw data

Abstract

fetched live from OpenAlex

Abstract Background There is an urgent need to understand the determinants (i.e., barriers and facilitators) of de-implementation. The purpose of this study was to develop a comprehensive list of determinants of the de-implementation of low-value care from the published literature and to compare this list to determinants identified by a group of stakeholders with lived experience with de-implementation. Methods This was a two-phase multi-method study. First, a systematic review examined published barriers and facilitators to de-implementation. Articles were identified through searches within electronic databases, reference lists and the grey literature. Citations were screened independently and in duplicate and included if they were: 1) written in English; and 2) described a barrier or facilitator to de-implementation of any clinical practice in adults (age ≥ 18 years). ‘Raw text’ determinants cited within included articles were extracted and synthesized into a list of representative determinants using conventional content analysis. Second, semi-structured interviews were conducted with decision-makers (unit managers and medical directors) and healthcare professionals working in adult critical care medicine to explore the overlap between the determinants found in the systematic review to those experienced in critical care medicine. Thematic content analysis was used to identify key themes emerging from the interviews. Results In the systematic review, reviewers included 172 articles from 35,368 unique citations. From 437 raw text barriers and 280 raw text facilitators, content analysis produced 29 distinct barriers and 24 distinct facilitators to de-implementation. Distinct barriers commonly cited within raw text included ‘lack of credible evidence to support de-implementation’ (n = 90, 21%), ‘entrenched norms and clinicians’ resistance to change (n = 43, 21%), and ‘patient demands and preferences’ (n = 28, 6%). Distinct facilitators commonly cited within raw text included ‘stakeholder collaboration and communication’ (n = 43, 15%), and ‘availability of credible evidence’ (n = 33, 12%). From stakeholder interviews, 23 of 29 distinct barriers and 20 of 24 distinct facilitators from the systematic review were cited as key themes relevant to de-implementation in critical care. Conclusions The availability and quality of evidence that identifies a clinical practice as low-value, as well as healthcare professional willingness to change, and stakeholder collaboration are common and important determinants of de-implementation and may serve as targets for future de-implementation initiatives. Trial registration The systematic review was registered in PROSPERO CRD42016050234 .

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)0.109
metaresearch head score (Gemma)0.135
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.109
Threshold uncertainty score0.575

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1090.135
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0090.008
Science and technology studies0.0020.002
Scholarly communication0.0040.004
Open science0.0020.003
Research integrity0.0020.001
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 head0.036
GPT teacher head0.325
Teacher spread0.289 · 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 designQualitative
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

Citations0
Published2022
Admission routes1
Has abstractyes

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