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Abstract P9: Pressure Ulcer Prevention: How Do Perceptions On Prevention And Current Initiatives Relate To Actual Pressure Ulcer Prevalence?

2017· article· en· W2608146905 on OpenAlexaff
Alison Wong, Gurjot S. Walia, Ricardo J. Bello, Carla Aquino, Justin M. Sacks

Bibliographic record

VenuePlastic & Reconstructive Surgery Global Open · 2017
Typearticle
Languageen
FieldHealth Professions
TopicPressure Ulcer Prevention and Management
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicineLikert scalePerioperativeFamily medicineHealth careDocumentationPerceptionInstitutional review boardNursingPsychologyPsychiatrySurgery

Abstract

fetched live from OpenAlex

PURPOSE: Hospital acquired pressure ulcers (HAPUs) remain a significant problem, despite implementation of numerous prevention initiatives. We aimed to assess the relationship between healthcare professionals’ (nurses, residents, and attending physicians) perceptions of the importance of HAPU prevention and actual HAPU prevalence. Additionally, we were interested in their perception of the effectiveness of existing prevention initiatives and devices, as well as their satisfaction with the same. We hypothesized that perceptions of the importance of pressure ulcer prevention would not be correlated with pressure ulcer prevalence. We also hypothesized that there would be low perceived effectiveness for, and satisfaction with, existing initiatives. METHODS: An online survey was developed using the 11 questions from the AHRQ’s Views on Pressure Ulcer Prevention validated survey. Additionally, participants were asked to rate their perceived effectiveness and satisfaction on: education, visual tools, skin care, repositioning, pressure-offloading bandages, pressure-offloading mattress pads, air mattresses, and documentation of patient movement. All questions used a 5 point Likert scale. The survey was distributed to nurses, residents and attending physicians across all inpatient and perioperative departments through a human resources mailing list, with approval by our Institutional Review Board. The results of the survey were then compared to quarterly pressure ulcer prevalence data by inpatient unit (medical, surgical, oncology, ICU) to assess for any significant correlation. Statistical analysis using ANOVAs and linear regression was done using Stata. RESULTS: In total 839 healthcare professionals completed the survey (579 nurses, 131 residents, 119 attending physicians), representing all inpatient units as well as perioperative and emergency departments. The mean score for the AHRQ survey was 42.5 out of 55, above the cut-off score of 40 denoting positive perceptions on the importance of prevention. There was a statistically significant difference between professions (P < 0.01; nurses = 43.3, nurse practitioners = 44.6, residents = 40.3, attending physicians = 41.3) and no interaction between profession and department or unit (P = 0.462). Repositioning was felt to be the most effective intervention (4.54 ± 0.64), followed by skin care (4.21 ± 0.75) and pressure-offloading mattress pads (4.20 ± 0.73). Posters were felt to be the least effective (3.31 ± 0.99). Respondents generally rated satisfaction much lower, with no single initiative significantly better than the others (range 3.21–3.79). Perceived effectiveness and satisfaction were all positively correlated. HAPU prevalence ranged from 1–29% (medical = 3, surgical = 1, oncology = 1, ICU = 29). There was not a significant correlation between AHRQ scores and prevalence of HAPUs by unit (r = -0.60, P = 0.402). CONCLUSION: Despite an overall positive perception of the importance of pressure ulcer prevention, HAPUs continue to be a major problem. Contrary to our hypothesis, many current initiatives are felt to be effective. There was no correlation between perceptions on the importance of prevention and HAPU prevalence, suggesting that prevention methods are not as effective as thought or they are not being used as widely as they should. Further research should take advantage of these positive attitudes by prospectively investigating novel interventions, especially in the ICU setting.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0210.003

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.

Opus teacher head0.074
GPT teacher head0.413
Teacher spread0.339 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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