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ISO and Lean Quality Management Systems in Healthcare

2021· article· en· W3175268004 on OpenAlexaboutno aff

Bibliographic record

VenueJournal Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicHealthcare Systems and Public Health
Canadian institutionsnot available
Fundersnot available
KeywordsHealth careBusinessLean manufacturingQuality (philosophy)Knowledge managementInformation systemProcess managementComputer scienceMarketingPolitical science

Abstract

fetched live from OpenAlex

Currently, in the healthcare of the Republic of Kazakhstan and many other countries, ISO standards are mandatory, and also in some countries the Lean Production System is used. In the Republic of Kazakhstan, the Ministry of Health issued guidelines for the implementation of lean technologies in healthcare organizations in 2017. However, the introduction of Lean technologies is not yet mandatory and has not become widespread in medical organizations in our country. In this regard, information on Lean technologies, experience of their application and effectiveness in healthcare organizations is useful for our medical managers and workers. Goal. Analysis of literature data on ISO and Lean quality management systems, their comparison, experience of application in healthcare organizations and efficiency. Material and methods. For this analysis, we searched for information on the issue with a depth of up to 20 years. Search for publications on the topic of the review was carried out in the databases of PubMed / MEDLINE, PMC, EMBASE, Web of Since, as well as a broad search through the browsers Google.com and Yahoo.com. The search criteria were combinations of terms: quality management system, healthcare, and lean production. Results and discussion. The description of the main features of the quality management systems ISO and Lean, as well as their comparison have been made. Information on the use of these systems in healthcare organizations is given. Currently, the Lean manufacturing system has been implemented in all healthcare organizations in the province of Saskatchewan (Canada), and a large-scale implementation has begun in the Russian Federation. Many medical organizations are implementing Lean system on their own initiative. Most publications have positive feedback on the Lean application. However, there are also several critical articles that the published positive reports lack a strong evidence base. In addition, it is impossible to compare the reports of different organizations due to the lack of a unified system for evaluating the effectiveness of Lean. Conclusion. The Lean manufacturing system is increasingly being used in healthcare organizations. Mostly positive results of Lean application are reported. However, the issue of its effectiveness in healthcare requires further research, since most of the reports cannot be considered as hard evidence. Keywords: quality management system, quality of care, lean management, customer satisfaction

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)0.007
metaresearch head score (Gemma)0.012
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: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.013
Science and technology studies0.0010.003
Scholarly communication0.0040.005
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.093
GPT teacher head0.432
Teacher spread0.340 · 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
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

Citations0
Published2021
Admission routes1
Has abstractyes

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