Lean management approach in hospitals: a systematic review
Bibliographic record
Abstract
Purpose In the recent few years, the Lean management has made significant improvements in providing quality service to patients in many health-care centers. Thus, this study aims to systematically review features and results of conducted studies using a lean management approach in hospitals. Design/methodology/approach In this systematic review, eight databases, including PubMed, Web of Knowledge, Google Scholar, Scopus, Iranmedex, SID, Magiran and Medlib, were searched using keywords including “Lean principles,” “Lean Six Sigma,” “Lean Process SID,” “Lean thinking,” “Lean Methodology,” “Toyota Production System lean processing,” “lean techniques” and “hospital,” as well as their Persian equivalents. Required data were extracted using an extraction table and were analyzed using content analysis method. Findings Out of 967 identified articles, 48 articles were included in the study. Most of the studies have been conducted in developed countries such as America, Britain, The Netherlands and Canada. The highest number of studies has been conducted in the overall hospital and emergency departments. Lean Six Sigma and Lean methodology were the most frequent terms used for lean management. The five-phase Six Sigma methodology was one of the most important methods used for the implementation of the Lean management. Performing the process at the first time (timing) and length of stay had the highest frequencies among indicators assessed in the studies. All indicators assessed in the studies have improved after the implementation of Lean management. Among 150 assessed indicators, 69 were meaningfully improved (p < 0.05) and 12 indicators did not have a meaningful improvement (p > 0.05) and 69 indicators did not show any meaningful changes. Practical implications A number of implications are drawn out to aid academics, practitioners and policymakers in improving knowledge and skills. The elimination of production wastes is the most important principle of Lean thinking and paying attention to the clients and increasing the value. This will significantly improve quality of services to the patients and reduce costs and losses through preventing wastes. Suitable metrics in Lean management need to be established. A move to placing greater emphasis on understanding the contexts in which theory is implemented is another application. Research/limitation The limitation of this study is selection of studies in English and Persian language, excluding gray literatures and unpublished studies and relying on a relatively limited number of databases for the identification of potentially eligible studies. In addition, because of the enormous heterogeneity in the methods and results of the studies, performing a meta-analysis in this study was not possible. Originality/value The results of this study show that there were many dispersions and heterogeneities in the way of implementation and content of Lean management in hospitals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.050 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.024 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".