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Enregistrement W2608146905 · doi:10.1097/01.gox.0000516666.93739.35

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

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

Notice bibliographique

RevuePlastic & Reconstructive Surgery Global Open · 2017
Typearticle
Langueen
DomaineHealth Professions
ThématiquePressure Ulcer Prevention and Management
Établissements canadiensDalhousie University
Organismes subventionnairesnon disponible
Mots-clésMedicineLikert scalePerioperativeFamily medicineHealth careDocumentationPerceptionInstitutional review boardNursingPsychologyPsychiatrySurgery

Résumé

récupéré en direct d'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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,003
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Études des sciences et des technologies, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,280
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,003
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0020,000
Communication savante0,0010,002
Science ouverte0,0010,002
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0050,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,074
Tête enseignante GPT0,413
Écart entre enseignants0,339 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2017
Routes d'admission1
Résumé présentoui

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