Adoption of Six Sigma’s DMAIC to Reduce Complications in IntraLase Surgeries
Bibliographic record
Abstract
Purpose: To show how a private eye care center in Turkey initiated Six Sigma principles to reduce the number of complications encountered during and after femtosecond laser-assisted LASIK (IntraLase) surgeries. Method: Data were collected for five years. To analyse the complications among 448 surgeries, main tools of Six Sigma’s Define-Measure-Analyze-Improve-Control (DMAIC) improvement cycle such as SIPOC table, Fishbone Diagram and, Failure, Mode and Effect Analysis were implemented. Sources and root causes of seventeen types of complications were identified and reported. Results: For a successful IntraLase surgery, experience of the refractive surgeon, patient’s anatomy and calibration of laser power were determined to be the “critical few” factors whereas, patient’s psychology, sterilization and hygiene, and suction-ring’s pressure were found to be the “trivial many” factors. The most frequently occurring complication was found to be subconjunctival haemorrhage. Conclusion: The process sigma level of the process was measured to be 3.3547. The surgical team concluded that sixteen complications (out of seventeen) should be significantly reduced by taking the necessary preventive measures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".