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Record W7028380365

FACTORS OF A PHYSICIAN QUALITY IMPROVEMENT LEADERSHIP COALITION THAT INFLUENCE PHYSICIAN BEHAVIOUR

2022· dissertation· en· W7028380365 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueQSpace (Queen's University Library) · 2022
Typedissertation
Languageen
FieldMathematics
TopicProbability and Statistical Research
Canadian institutionsnot available
Fundersnot available
KeywordsEnablingQuality managementTest (biology)WorkflowQuality (philosophy)Intervention (counseling)Physician assistantsQualitative research
DOInot available

Abstract

fetched live from OpenAlex

This manuscript-style thesis investigated the Strategic Clinical Improvement Committee (SCIC), a physician-led coalition that developed a provincial laboratory-test ordering overuse (LTOO) initiative aimed at reducing blood urea nitrogen (BUN) test ordering across hospital medicine (MED) units and emergency departments (ED) in Alberta, Canada. Two studies in three separate manuscripts contributed to the mixed methods aim of identifying coalition factors that enable MED and ED physicians to lead, participate in, and influence appropriate BUN test ordering. Manuscript 1 is a scoping review; it resulted in a synthesis of 11 articles representing nine distinct physician-led approaches that incorporate learning the science of improvement. From these, 20 enabler strategies were described, which were grouped to generate eight overarching themes that may enable physician quality improvement (QI) capability, participation, and leadership. Manuscript 2 is a qualitative exploration of the physician experience; interviews with 12 physicians from seven participating hospitals generated textual data. A content analysis was completed that identified nine overarching themes and 11 change techniques that may encourage physician QI involvement and appropriate laboratory test ordering. Manuscript 3 is a combination of the quantitative (total monthly BUN test data for six participating hospitals) and qualitative findings. BUN testing was reduced significantly in five of six hospitals and resulted in cost avoidance. Physicians had similar perceptions of the characteristics that enabled their QI involvement, which included a simple initiative linked to a coalition physician leader and/or member, credibility, mentorship, support personnel, QI education and hands-on training, minimal physician effort, and no clinical workflow disruption. Implementing person- and system-focused intervention components, and communication from a trusted local physician were factors influencing appropriate BUN test ordering. The SCIC was found to be an effective physician QI engagement strategy. Results from these studies deepen understanding of the behavioural characteristics and strategies that motivate physician behaviour for QI involvement and appropriate BUN test ordering, reducing LTOO. Researchers, policymakers, physicians, and health organization leaders may use these findings to establish, deliver, and promote physician-led QI beyond a single context.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.577
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.080
GPT teacher head0.315
Teacher spread0.235 · 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