P360: Materiovigilance and improvement of the maintenance of the biomedical equipment by the implementation of strategies for the use of equipment: case study of the hospital Gabriel Touré of Mali
Bibliographic record
Abstract
To make the inventory of current practices for the use of the large equipment at the hospital Gabriel Touré and to bring solutions for an improvement of the use and productivity of the equipment. This was a cross-sectional study using the method of problem resolution by quality improvement. It was conducted in 2004in two engineering departments of the hospital Gabriel Touré. 38 users of the equipment were concerned with the investigations. Of 38 surveyed persons only two doctors could operate the echograph. 3 persons of 38 (7.89%) were abele to select the right parameters for the use of the equipment. Test of use is not carried out by 20 agents (52.63%), including 11 persons that manipulate equipment of sterilization and medical imagery. 14 agents carry out the act badly including 5 technicians’ that manipulate radiograpies what explains the important loss of simages. Only 8 agents (21.05%) turn the equipment off after work. 18 agents do not carry out maintenance of the material after use including 9 users of radiography and echography. The problem of maintenance at the hospital Gabriel Touré is a crucial question. The constraints related to the management of the large equipment at the hospital Gabriel Touré relate to several spects: the deficit of information, the absence of supervision and framing, the insufficiency of sensibilzation, the deficit of the actors implied in information and adapted know-how, the weakness of financial means and material allocated, the insufficiency of clear and codified directives fixing the conditions of use of the equipment. We recommend an internal reorganization of the service of maintenance, the programming of regular supervision, the development and the implementation of the management tools of maintenance.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".