Human factors evaluation of an innovative wound care technology
Notice bibliographique
Résumé
Pressure injuries and other chronic wounds, such as diabetic foot ulcers and venous leg ulcers, can cause significant pain, increased morbidity and mortality for patients, and result in substantial costs for both the patients and the healthcare system. In the Canadian province of Alberta, a provincial point prevalence audit found one in six patients in acute care facilities had a pressure injury, with 71 % of those deemed hospital-acquired (Alberta Health Services, 2021). As such, the provincial healthcare delivery provider, Alberta Health Services (AHS), wanted to identify an innovative solution to address this problem. In response to this need, NanoSALV Catalytic Advanced Wound Care Treatment Matrix, a Health Canada-approved medical device, was identified by AHS as a promising technology to support wound healing. To help inform decision-making regarding the adoption of this innovative wound care technology, evidence regarding the implementation feasibility of NanoSALV into current practice was needed. The project team conducted a human factors evaluation, gathering perspectives from patients and providers across various environments where these wounds are often treated, including long-term care, in-patient care, outpatient clinics, and patient’s homes. This evaluation was conducted concurrently with a clinical trial assessing NanoSALV's effectiveness in healing chronic wounds unresponsive to current state dressings. The human factors evaluation consisted of observations and interviews, and included 20 participants from multiple roles, including healthcare providers in long-term care, in-patient, and outpatient settings, and patients and family caregivers in home settings. A task analysis was conducted based on the wound dressing observations to better understand the implementation feasibility of NanoSALV, compared to a selected current state silver-based dressing, AQUACEL Ag+. Thematic analysis and journey mapping were conducted based on participant interviews to compare the user experience and satisfaction between NanoSALV and the current state from different patient and provider perspectives. The evaluation indicated that the procedures for changing wound dressings, whether using the current state dressing or NanoSALV, followed the same sequence of steps, with NanoSALV requiring fewer subtasks in the application step, demonstrating the feasibility of implementing NanoSALV into clinical practice. Desirability from the perspective of each of the settings (i.e., long-term care, in-patient, outpatient, and at-home management) for NanoSALV adoption included its ease of application and potential to enhance patient independence and participation in wound care. Some areas for improvement include better communication of the appropriate amount of product needed and making the product packaging easier to open. It was found that it was feasible to integrate NanoSALV into existing workflow practices in the wound care pathway and the technology was perceived as a desirable and feasible solution for chronic wound management from the perspective of all potential users.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,023 | 0,050 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».