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Record W2891390842 · doi:10.1186/s13643-018-0800-z

The sustainability of Lean in pediatric healthcare: a realist review

2018· review· en· W2891390842 on OpenAlexaff
Rachel Flynn, Amanda S. Newton, Thomas Rotter, Dawn Hartfield, Sarah Walton, Michelle Fiander, Shannon D. Scott

Bibliographic record

VenueSystematic Reviews · 2018
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicQuality and Supply Management
Canadian institutionsQueen's UniversityUniversity of Alberta
Fundersnot available
KeywordsSustainabilityLean manufacturingProcess managementHealth careMedicineQuality managementContext (archaeology)Lean project managementLean Six SigmaOperations managementKnowledge managementNursingManagement scienceSix SigmaBusinessComputer scienceEngineering

Abstract

fetched live from OpenAlex

BACKGROUND: Lean is a quality improvement management system from the Toyota manufacturing industry. Since the early 2000's, Lean has been used as an intervention for healthcare improvement. Lean is intended to reduce costs and improve customer value through continuous improvement. Despite its extensive use, the contextual factors and mechanisms that influence the sustainability of Lean in healthcare have not been well studied. Realist synthesis is one approach to "unpack" the causal explanations of how and why Lean is sustained or not in healthcare. We conducted a realist synthesis using the context (C) + mechanim (M) = outcome (O) heuristic, to further develop and refine an initial program theory with seven CMO hypotheses, on the sustainability of Lean efforts across pediatric healthcare. METHODS: Our search strategy was multi-pronged, iterative, and purposeful in nature, consisting of database, gray literature, and contact with three healthcare organizations known for Lean implementation. We included primary research studies, published and unpublished case studies or reports, if they included Lean implementation with a pediatric focus and sustainability outcome. We used the Normalization Process Theory and the National Health Services Sustainability Model, an operational definition for Lean and a comprehensive definition for sustainability as guidance for data extraction and analysis. Our initial program theory with was refined using a blend of abductive and retroductive analytical processes. RESULTS: We identified six published primary research studies, two published quality improvement case studies, and three unpublished quality improvement case reports. Five CMO hypotheses from our initial program theory were substantially supported after synthesis, "sense-making and value congruency," "staff engagement and empowerment," and the "ripple effect" or causal pathway between Lean implementation outcomes that served as facilitating or hindering contexts for sustainability. Overall, there was variation with the conceptualization and measurement of sustainability. CONCLUSIONS: This study is the first to examine Lean sustainability in pediatric healthcare using realist methods. Future research should examine whether the predictors of implementation are the same or different to sustainability and evaluate the underlying mechanisms that influence the sustainability of Lean. There is also a need for research to develop and test conceptual models and frameworks on sustainability. SYSTEMATIC REVIEW REGISTRATION: PROSPERO-CRD42015032252 .

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)0.019
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: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.083
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0140.015
Science and technology studies0.0010.002
Scholarly communication0.0040.005
Open science0.0030.003
Research integrity0.0020.002
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 head0.104
GPT teacher head0.370
Teacher spread0.266 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations65
Published2018
Admission routes1
Has abstractyes

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