Evaluating interaction between internal hospital supply chain performance indicators: a rough-DEMATEL-based approach
Why this work is in the frame
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Bibliographic record
Abstract
Purpose Previous studies on hospital supply chain performance have attempted to measure the performance of the hospital supply chain either by the measurement of performance indicators or the performance of specific activities. This paper attempts to measure the internal hospital supply chain's performance indicators to find their interdependencies to understand the relationship among them and identify the key performance indicators for each of those aspects of the logistics process toward improvement. Design/methodology/approach In this research, a systematic assessment and analysis method under vagueness is proposed to assess, analyze and measure the internal health care performance aspects (HCPA). The proposed method combines the group Decision-Making and Trial Evaluation Laboratory (DEMATEL) method and rough set theory. Findings The study results indicate that the most critical aspects of hospital supply chain performance are completeness of treatment, clinical care process time and no delay in treatment. Originality/value The causal relationship from rough-DEMATEL can advise management officials that to improve the completeness of treatment toward patient safety, clinical care process time should be addressed initially and with it, patient safety aspects such as free from error, clinical care productivity, etc. should be improved as well. Improvement of these aspects will improve the other aspects they are related to.
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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 | 0.002 | 0.000 |
| 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 | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 it