The Outcome and Challenges of Application of Pressure Ulcer Prevention Project in King Fahad Hospital Jeddah – 2023
Bibliographic record
Abstract
BACKGROUND: A pressure ulcer (PU), also known as bedsore, pressure injury, or decubitus ulcer, is a localized injury brought on by sustained pressure applied to the skin and underlying soft tissue over an extended length of time. This study aimed to identify the outcome and challenges of the application of pressure ulcer prevention project focus to clarify the findings of the application of the project, to highlight the challenges met by the team who apply the project, to know the prevalence state during the application period, and to identify the adherence of nurses to their role. Through Improved nursing education, improve adherence to a policy of pressure ulcer prevention, being sure all equipment is in adequate working condition, Monitoring high-risk patients. METHODOLOGY: This is a retrospective hospital-based study, which monitored the pressure ulcer prevention project’s (PUPP) results from 2019 to 2021 for 3 years. Data on 21400 patients were gathered from several departments of a hospital in the west region of Saudi Arabia. The project’s main goals were the installation of a wound care team, hospital staff education, ongoing data monitoring, and follow-up visits for inpatient units. RESULTS: This current study showed that the pressure ulcer prevention project was successful showing a statistically significant reduction of hospital-acquired pressure ulcers (HAPUs) from 1.97% in 2018 to 1.4% in 2019 to 0.53% in 2020 to 0.14% in 2021. CONCLUSION: The research concluded the percentage of cases of pressure ulcers was successfully decreased by the PUPP. The project can be expanded and carried out in additional 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".