Healthy Skin Wins: A Glowing Pressure Ulcer Prevention Program That Can Guide Evidence‐Based Practice
Bibliographic record
Abstract
BACKGROUND: In 2013, an observational survey was conducted among 242 in-patients in a community hospital with a pressure ulcer (PU) prevalence of 34.3%. An evidence-based pressure ulcer prevention program (PUPP) was then implemented including a staff awareness campaign entitled "Healthy Skin Wins" with an online tutorial about PU prevention. AIMS: To determine the effectiveness of the PUPP in reducing the prevalence of PUs, to determine the effectiveness of the online tutorial in increasing hospital staff's knowledge level about PU prevention, and to explore frontline staff's perspectives of the PUPP. METHODS: This was a mixed methods study. A repeat observational survey discerned if the PUPP reduced PU prevalence. A pre-test post-test design was used to determine whether hospital staff's knowledge of PU prevention was enhanced by the online tutorial. Qualitative interviews were conducted with nurses, allied health professionals, and health care aides to explore staff's perspectives of the PUPP. RESULTS: A comparison of initial and repeat observational surveys (n = 239) identified a statistically significant reduction in the prevalence of PU to 7.53% (p < .001). The online tutorial enhanced staff knowledge level with a statistically significantly higher mean post-test score (n = 80). Thirty-five frontline staff shared their perspectives of the PUPP with "it's definitely a combination of everything" and "there's a disconnect between what's needed and what's available" as the main themes. CONCLUSIONS: Incorporating evidence-based PU prevention into clinical practice greatly reduced the prevalence of PUs among hospital in-patients. Due to the small sample size for the pre-test post-test component, the effectiveness of the online tutorial in improving the knowledge level of PU prevention among hospital staff requires further research. LINKING EVIDENCE TO ACTION: Evidence-based PU prevention strategies are facilitated by using a multidisciplinary approach. Educational tools about PU prevention must target all members of the healthcare team including healthcare aides, patients and families.
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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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 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".