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Record W2782418152 · doi:10.1136/bmjopen-2017-018837

Physician engagement in hospitals: a scoping review protocol

2018· review· en· W2782418152 on OpenAlexaffabout
Tyrone Perreira, Laure Perrier, Melissa Prokopy, Anthony Jonker

Bibliographic record

VenueBMJ Open · 2018
Typereview
Languageen
FieldHealth Professions
TopicPatient Satisfaction in Healthcare
Canadian institutionsOntario Medical AssociationOntario Council of University LibrariesUniversity of Toronto
Fundersnot available
KeywordsMedicineProtocol (science)Health services researchPublic healthFamily medicineAlternative medicineMedical educationNursingPathology

Abstract

fetched live from OpenAlex

INTRODUCTION: Literature on healthcare reforms highlights the importance of physician engagement, suggesting that it is a critical factor for lowering costs while improving efficiency, quality of care, patient safety, physician satisfaction and retention. As a result, many hospitals have adopted physician engagement as a top strategic priority, but little is known about the actual evidence, making it difficult for hospital leadership to identify relationships between true physician 'work engagement' and work outcomes. The aim of this scoping review is to identify factors associated with, and tools used to measure, physician engagement. METHODS AND ANALYSIS: This scoping review will be conducted as per Arksey and O'Malley (2005). The electronic databases that will be searched from inception onwards include MEDLINE, EMBASE and Cochrane Central Register of Controlled Trials. Grey literature will be searched via websites of relevant agencies such as Agency for Healthcare Research and Quality. Conferences and abstracts will be viewed and full paper requests made as required. Supplementary articles may be obtained by contacting field experts and searching references of relevant articles. All quantitative and qualitative study designs will be eligible that describe factors associated with, and tools used to measure, hospital physician engagement. After a small calibration exercise, screening and abstraction will be completed separately by two individuals, with discrepancies resolved by a third. Quantitative (frequencies) and qualitative analyses (generation of descriptives) will be conducted. Thematic analysis will be used to evaluate and categorise study findings. IMPLICATIONS AND DISSEMINATION: This project is part of the Ontario Hospital Association's (OHA) initiative to improve its understanding of physician engagement. The review findings will be shared with all Ontario hospitals. Dissemination will occur through peer-reviewed publications and to the OHA membership through the OHA Learning and Engagement team.

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)0.126
metaresearch head score (Gemma)0.083
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.126
Threshold uncertainty score0.669

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1260.083
Meta-epidemiology (narrow)0.0060.008
Meta-epidemiology (broad)0.0150.014
Bibliometrics0.0230.019
Science and technology studies0.0060.006
Scholarly communication0.0100.010
Open science0.0080.008
Research integrity0.0110.009
Insufficient payload (model declined to judge)0.0950.022

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 head0.519
GPT teacher head0.677
Teacher spread0.158 · 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 designNot applicable
Domainnot available
GenreProtocol

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

Citations10
Published2018
Admission routes2
Has abstractyes

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