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Facilitating clinician adherence to guidelines in the intensive care unit: A multicenter, qualitative study*

2007· article· en· W2095179786 on OpenAlexaffabout
Tasnim Sinuff, Mita Giacomini, Daren K. Heyland, Peter Dodek

Bibliographic record

VenueCritical Care Medicine · 2007
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineGuidelinePsychological interventionNursingQualitative researchIntensive care unitGrounded theoryMEDLINEAuditIntensive careFamily medicineIntensive care medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine perceived facilitators and barriers to guideline implementation and clinician adherence to guidelines in the intensive care unit (ICU). DESIGN: Multicenter qualitative study in three university-affiliated ICUs in Canada. METHODS: We conducted individual semistructured interviews of 44 ICU clinicians (12 intensivists, two physician directors, 12 nurses, three nurse educators, three nurse managers, nine respiratory therapists, and three respiratory therapist educators). We elicited attitudes and perceptions regarding the facilitators and barriers to adherence to guidelines in the ICU. We transcribed all interviews and analyzed data in duplicate using grounded theory to identify themes and develop a model to describe clinicians' views. MAIN RESULTS: The presence of a culture within the ICU that enabled guideline implementation and clinician adherence to guidelines was considered essential. Central to this culture was an ICU team that believed guidelines would reduce practice variation, help implement research findings at the bedside, and result in a more rapid implementation of best practice. Effective leadership and positive interprofessional team dynamics were deemed requisites for this culture. Important strategies identified by the participants to overcome potential barriers to clinician adherence to guidelines were: the presence of effective leaders to promote adoption of the guideline and its adherence, education tailored to the learning preferences of different professional groups, and repeated educational interventions, reminders, and audit and feedback. Participants suggested that the use of strategies to select and prioritize guidelines, simple guideline formats, and electronic media to implement guidelines may further contribute to successful guideline programs. CONCLUSIONS: Complex ICU practices and unique interprofessional team dynamics influence clinician adherence to guidelines. Initiatives that employ an approach addressing these issues may optimize guideline uptake and adherence. The optimal approach and its effectiveness may be guideline-dependent and requires further study.

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)0.017
metaresearch head score (Gemma)0.024
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.024
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0070.005
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.546
GPT teacher head0.658
Teacher spread0.112 · 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

Citations161
Published2007
Admission routes2
Has abstractyes

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