Features and Results of Conducted Studies Using a Lean Management Approach in Emergency Department in Hospital: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: To perform a systematic review of the properties and results of the studies that their approaches are lean management in emergency departments and the factors which influence on their performance. METHOD: The necessary information in the first stage was collected by searching these keywords: "Lean principles" "Lean Six Sigma", "Lean Process", "Lean thinking", "Lean Methodology", "Toyota Production System lean processing", "lean techniques", "emergency department", "emergency medicine", "emergency room" and "emergency care " . And in the next stage the keywords such as "lean management" and "emergency" was collected from SID, Medlib, IranDoc, Google Scholar, MagIran, IranMedex data bases. For extracting the data data-extracting forms was prepared. The information we got from the forms was organized in information-extracting forms and was analyzed manually. The diagrams were drawn in Excel: 2010. RESULTS: Finally, 26 essays have been included. Most of the studies were accomplished in Canada and U.S.A. only in one of the cases, the authors used the control group. Each of these terms, "lean techniques" and "lean principals", with five times repetitions had the highest frequency. The most important team of implementation of lean management included: hospital management team or the manager of Emergency department, physicians, nurses, staffs and external counselors. Generally, 51 indicators were studied which among them the length of stay and the timing had the most frequency. After implementation of lean management, almost all studied indicators have significantly improved. 14 barriers, 14 facilitators and 10 effective factors were recognized in implementing the lean management. CONCLUSION: According to the studies, responsibility of organization's senior management and his/her supports; increasing the knowledge of the characteristics and dimension of lean among the providers of health service; and decreasing the resistance and consulting with external counselors can have great effect on the success of lean management.
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 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 | 0.030 | 0.106 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.047 | 0.038 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| 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".