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Record W4390631672 · doi:10.1136/bmjoq-2023-002522

Decision-maker roles in healthcare quality improvement projects: a scoping review

2024· review· en· W4390631672 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBMJ Open Quality · 2024
Typereview
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversité de Sherbrooke
FundersFonds de Recherche du Québec - SantéFonds de recherche du Québec
KeywordsHealth careDecision analysisDelegationQuality (philosophy)Knowledge managementMEDLINEBusinessPsycINFOPublic relationsPsychologyPolitical scienceManagement scienceMedicineEngineeringComputer science

Abstract

fetched live from OpenAlex

OBJECTIVES: Evidence suggests that healthcare quality improvement (QI) projects are more successful when decision-makers are involved in the process. However, guidance regarding the engagement of decision-makers in QI projects is lacking. We conducted a scoping review to identify QI projects involving decision-makers published in the literature and to describe the roles decision-makers played. METHODS: Following the Joanna Briggs Institute framework for scoping reviews, we systematically searched for all types of studies in English or French between 2002 and 2023 in: EMBASE, MEDLINE via PubMed, PsycINFO, and the Cumulative Index to Nursing and Allied Health Literature. Criteria for inclusion consisted of literature describing health sector QI projects that involved local, regional or system-level decision-makers. Descriptive analysis was performed. Drawing on QI and participatory research literature, the research team developed an inductive data extraction grid to provide a portrait of QI project characteristics, decision-makers' contributions, and advantages and challenges associated with their involvement. RESULTS: After screening and review, we retained 29 references. 18 references described multi-site projects and 11 were conducted in single sites. Local decision-makers' contributions were documented in 27 of the 29 references and regional decision-makers' contributions were documented in 12. Local decision-makers were more often active participants in QI processes, contributing toward planning, implementation, change management and capacity building. Regional decision-makers more often served as initiators and supporters of QI projects, contributing toward strategic planning, recruitment, delegation, coordination of local teams, as well as assessment and capacity building. Advantages of decision-maker involvement described in the retained references include mutual learning, frontline staff buy-in, accountability, resource allocation, effective leadership and improved implementation feasibility. Considerations regarding their involvement included time constraints, variable supervisory expertise, issues concerning centralised leadership, relationship strengthening among stakeholders, and strategic alignment of frontline staff and managerial priorities CONCLUSIONS: This scoping review provides important insights into the various roles played by decision-makers, the benefits and challenges associated with their involvement, and identifies opportunities for strengthening their engagement. The results of this review highlight the need for practical collaboration and communication strategies that foster partnership between frontline staff and decision-makers at all levels.

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)0.088
metaresearch head score (Gemma)0.025
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.526
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0880.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0030.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.004

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 head0.908
GPT teacher head0.832
Teacher spread0.076 · 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