Evaluating the Costs and Benefits of Innovations in Chronic Wound Care Products and Practices
Notice bibliographique
Résumé
The management of innovation and change in healthcare can be a major challenge. It has been recognized that a key fac- tor in closing the gap between best practice and common practice is the ability of healthcare providers and organizations to rapidly disseminate innovations. 1 Today's healthcare environment offers a steady stream of innovations, often at a pace that seems much too fast for organizations to evaluate and integrate. Clinicians and administrators can feel overwhelmed and unable to decide which innovations are appropriate and how they might be utilized for optimal outcomes. They face constant pressure to innovate and accelerate the dissemination of innovation. Simultaneously, organizations must ensure the consistent delivery of proven patient care practices at the highest possible quality standards is not compromised in any way as innovations are adopted. This paper reviews the implementation of healthcare innovations in the field of chronic wound care. Two distinct types of innovation are profiled: • Process Innovation: A comprehensive program of clinical best practices focused on the prevention and care of chronic wounds is currently being implemented by a large community care organization providing in-home care services in Canada. The program incorporates a rigorous framework of measurement, monitoring, and benchmarking that tracks outcomes and resource requirements in order to generate continuous feedback on both cost and benefits. • Product Innovation: An innovative medical device—a portable, disposable negative pressure wound therapy (NPWT) system—has been introduced into clinical practice by wound care providers in acute care and community care orga- nizations. This product innovation has been adopted within the context of best practice wound care and prevention programs so tools are available to assess, evaluate, and monitor the utilization of the new technology. Results show 98% of patients reported they were pleased or satisfied with the NPWT device. Anecdotal data from patients described improvements ranging from increased social activities and improved self-esteem to a marked improvement in gen- eral overall wellness. Similarly, 99% of nurses were pleased or satisfied with the device. Only 2% of nurses reported any dif- ficulty with application of the product. Over the course of the evaluation, 68% of wounds treated with the portable negative pressure device were completely closed with a median time to healing of 9 weeks. This rate needs to be considered in the context of the wounds treated, many of which remained unhealed for a significant time before commencing treatment with portable NPWT (average wound duration before treatment was 9 weeks with a range from 1 to 68 weeks). A comparison of the cost of the single-use negative pressure system and traditional negative pressure systems shows that single-use NPWT can substantially reduce the cost per patient, as a result of fewer dressing changes and nurse visits per week. This paper provides qualitative and quantitative data related to the adoption of these innovations in a demanding, real- world clinical environment. The intent is to offer practical insights and describe results to date from innovations within a framework of managed adoption and evaluation that is designed to meet healthcare organizations priorities of high-quality care and improved efficiency.
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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 | 0,057 | 0,243 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,004 |
| Bibliométrie | 0,008 | 0,007 |
| Études des sciences et des technologies | 0,001 | 0,003 |
| Communication savante | 0,007 | 0,008 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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 ».