MétaCan
Menu
Back to cohort
Record W2143238088 · doi:10.12927/hcq.2009.20979

Role of Champions in the Implementation of Patient Safety Practice Change

2009· article· en· W2143238088 on OpenAlexaff
Stephanie Soo, Whitney Berta, G. Baker

Bibliographic record

VenueHealthcare Quarterly · 2009
Typearticle
Languageen
FieldHealth Professions
TopicPatient Safety and Medication Errors
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsChampionTypologyPatient safetyBest practicePublic relationsPsychological interventionHealth careNursingMedicinePsychologyPolitical scienceSociology

Abstract

fetched live from OpenAlex

Practitioners of patient safety practice change agree that champions are central to the success of implementation. The clinical champion role is a concept that has been widely promoted yet empirically underdeveloped in health services literature. Questions remain as to who these champions are, what roles they play in patient safety practice change and what contexts serve to facilitate their efforts. This investigation used a multiple-case study design to critically examine the role of champions in the implementation of rapid response teams (RRTs), an innovative complex patient safety intervention, in two large urban acute care facilities. An analysis of interviews with key individuals involved in the RRT implementation process revealed a typology of the patient safety practice champion that extended beyond clinical personnel to include managerial and executive staff. Champions engaged to a varying extent in a number of core activities, including education, advocacy, relationship building and boundary spanning. Individuals became champions both through informal emergence and a combination of formal appointment and informal emergence. By identifying and elaborating upon specific features of the champion role, this study aims to expand the dialogue about champions for patient safety practice change.

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)0.022
metaresearch head score (Gemma)0.047
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 score0.022
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.047
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0070.010
Scholarly communication0.0070.005
Open science0.0020.007
Research integrity0.0020.003
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 head0.060
GPT teacher head0.457
Teacher spread0.397 · 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

Citations165
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueHealthcare QuarterlySame topicPatient Safety and Medication ErrorsFrench-language works237,207