Applying the Nonadoption, Abandonment, Scale-Up, Spread, and Sustainability (NASSS) Framework to Adapt the CHAMP App for Pediatric Feeding Tube Weaning: Application and Case Report
Notice bibliographique
Résumé
Background: Evidence-based tube feeding (TF) weaning involves reducing the volume of tube feeds to induce hunger, with interdisciplinary monitoring to allow for proactive medical, nutritional, and behavioral intervention as needed. This can be done outpatient; however, the current standard of care requires a high degree of medical monitoring and care coordination, which can be challenging to implement. The CHAMP App is a mobile app designed for remote patient monitoring of children born with congenital heart conditions who are at high risk for medical morbidity and mortality. The CHAMP App remote patient monitoring program would be ideally suited to improve medical monitoring and care coordination. Objective: This study aims to determine the feasibility of adapting the CHAMP App for children ready to wean from TF. Methods: We used the Non-adoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) framework as a formative tool and conducted a case study beta test. Results: The level of complexity for the digital innovation's adaptation supported a high likelihood of success for the TF population. Most issues were simple, such as expanding the types of data that could be entered into the app, and some were more complicated, for instance, training all relevant staff to use and maintain the technology. The case study beta test was conducted with "Greyson", a 10-month old child weaning from TF (name changed for confidentiality). Once a week, the team reviewed the parent-entered data and communicated with Greyson's parents, recommending a 25% reduction in tube feeding each week. With the CHAMP App facilitating 2-way communication between the family and the team, Greyson successfully transitioned from receiving 30% of his feeds orally and 70% via tube feeding to 100% oral feedings over the course of 1 month in a home setting. Conclusions: The CHAMP App is likely to be incredibly valuable in TF weaning. The NASSS framework helped identify key considerations for adapting the CHAMP App for TF weaning at a Midwestern children's hospital. Interviews with the health care team highlighted issues like data entry expansion and staff training. The framework confirmed TF weaning as a suitable application with no major barriers. The CHAMP App successfully supported a test patient, Greyson, in weaning from his feeding tube. It may improve access, communication efficiency, and satisfaction among families and health care teams while reducing costs and enhancing safety monitoring. The app could also make TF weaning more accessible to families with lower health literacy.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».