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Record W2568462745 · doi:10.1177/0844562116686491

The Productive Ward Program™

2017· article· en· W2568462745 on OpenAlexvenueno aff
Peter Van Bogaert, Danny Van heusden, Martijn Verspuy, Kristien Wouters, Stijn Slootmans, Johnny Van der Straeten, Paul Van Aken, Mark White

Bibliographic record

VenueCanadian Journal of Nursing Research · 2017
Typearticle
Languageen
FieldHealth Professions
TopicPatient Satisfaction in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsWorkloadBurnoutScale (ratio)Quality (philosophy)NursingQuality managementJob satisfactionHealth careSocial capitalPsychologyMedicineApplied psychologyBusinessMarketingComputer scienceSocial psychologyClinical psychology

Abstract

fetched live from OpenAlex

Aim To investigate the impact of the quality improvement program "Productive Ward - Releasing Time to Care™" using nurses' and midwives' reports of practice environment, burnout, quality of care, job outcomes, as well as workload, decision latitude, social capital, and engagement. Background Despite the requirement for health systems to improve quality and the proliferation of quality improvement programs designed for healthcare, the empirical evidence supporting large-scale quality improvement programs impacting patient satisfaction, staff engagement, and quality care remains sparse. Method A longitudinal study was performed in a large 600-bed acute care university hospital at two measurement intervals for nurse practice environment, burnout, and quality of care and job outcomes and three measurement intervals for workload, decision latitude, social capital, and engagement between June 2011 and November 2014. Results Positive results were identified in practice environment, decision latitude, and social capital. Less favorable results were identified in relation to perceived workload, emotional exhaustion. and vigor. Moreover, measures of quality of care and job satisfaction were reported less favorably. Conclusion This study highlights the need to further understand how to implement large-scale quality improvement programs so that they integrate with daily practices and promote "quality improvement" as "business as usual."

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 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)0.005
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.463
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0160.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0000.000

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 head0.492
GPT teacher head0.638
Teacher spread0.145 · 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 teacher head, not a consensus.

Study designObservational
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

Citations19
Published2017
Admission routes1
Has abstractyes

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