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Record W2766190576 · doi:10.1093/eurpub/ckx187.272

Improving quality and efficiency in healthcare. The Lean Thinking strategy

2017· article· en· W2766190576 on OpenAlexaboutno aff
Valerio Mogini, Paolo Campanella, Eleonora Moraca, Ornela Makishti, Walter Ricciardi, Maria Lucia Specchia

Bibliographic record

VenueEuropean Journal of Public Health · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicQuality and Supply Management
Canadian institutionsnot available
Fundersnot available
KeywordsQuality (philosophy)Health careLean manufacturingBusinessProcess managementPsychologyMarketingEconomicsPhilosophy

Abstract

fetched live from OpenAlex

Background Lean Thinking is a philosophy originated from Toyota Production Systems that emphasize eliminating non-value added activities while delivering quality products on time at least cost with greater efficiency. It has been adapted and expanded by a wide range of industries, including logistics and distribution, services, retail, government, construction, maintenance and even healthcare. The first hospital that implemented the Lean Thinking was Virginia Mason Hospital. Some successful examples of Lean implementation in health care settings are: Johns Hopkins – Baltimore, John Radcliffe – Oxford, Mount Sinai - New York, New Karolinska Solna – Stockholm and Erasmus Medical Centre – Rotterdam. Methods To assess the impact of Lean Thinking implementation in healthcare in terms of volume of services, time, personnel, quality, safety and costs we conducted a systematic review. PubMed, Scopus and Cochrane CINAHL databases were searched to identify studies that evaluate the impact of Lean Thinking implementation. Two reviewers screened all identified citations and extracted data according to the MOOSE guidelines. Quality of the studies was evaluated using the New Castle – Ottawa scale. Results Of the 635 articles identified, 27 studies were included. All included studies showed a positive impact of Lean Thinking implementation. For example, following the adoption of Lean principles and tools in an Emergency Department, it was found a statistically significant reduction (p < 0.05) for the waiting time, triage and waiting for the medical examination. In operating rooms, it has been reported a better management of stocks of materials within the warehouse with a reduction in inventories and the order process time. Other studies have showed also a statistically significant reduction (p < 0.05) in 30-day mortality and in 3-day mortality, as well as improvement in other clinical outcomes. Conclusions Lean methodology seems an appropriate strategy of management in healthcare. Key messages: Lean Thinking is a methodology that can be widely adapted to health services reorganization. Lean Thinking implementation is generally associated with outcome improvement.

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)0.049
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.904
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0490.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.152
GPT teacher head0.341
Teacher spread0.189 · 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

Citations3
Published2017
Admission routes1
Has abstractyes

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