Impact of Automated Digital Navigation Program on Bowel Preparation Quality and Patient Satisfaction for Colonoscopy: A Comparative Study Across Multiple Sites
Notice bibliographique
Résumé
Background Nearly 1 in 5 patients suffers from inadequate or poor bowel preparation in advance of a colonoscopy. Prior studies have shown that this leads to a decrease in adenoma detection rate, increased time spent in completing efficiency in endoscopy suite, as well as an overall increase in cost of care from 13-20%. With the shift to value-based care in the American healthcare system, there is an urgent need for solutions that can automate pre-procedure guidance and post-procedure follow up. Objective As part of the American Gastroenterology Association digital transformation network, we sought to automate and improve pre-procedure navigation for colonoscopy using connected health technologies (specifically digital navigation). At Arizona Center for Digestive Health (AZCDH), we assessed the impact of digital navigation on bowel preparation quality, patient engagement, and patient satisfaction. We also sought to assess the reproducibility of outcomes seen at AZCDH at additional sites that have implemented digital navigation for endoscopic procedures as part of the American Gastroenterology Association network, including Yale New Haven Hospital (YNHH) and three Mount Sinai Hospital locations. Methods At AZCDH, we compared two cohorts of patients (usual care versus digital navigation) scheduled for colonoscopy. The digital navigation cohort received usual care in addition to time based messages and education content pathways on smartphones and delivered through Rx.Health’s digital medicine platform. Bowel preparation quality was then assessed, as well as patient satisfaction with the digital navigation intervention. Patient engagement and satisfaction were then compared with initial data from other sites within the network. Results Of the 217 patients prescribed the digital navigation program at AZCDH, 93 completed the procedure to date and had bowel preparation results documented in the electronic endoscopic record system. After implementing the digital navigation program the rate of aborted procedures decreased from 2.2% at baseline to 1.07%. In a follow up survey, 93% of respondents “strongly agreed” or “agreed” that the digital navigation program was helpful in preparing for their colonoscopy. At other locations to date, 433 patients have been prescribed the pathway at YNHH along with 213 patients at Mount Sinai locations. One hundred percent and 94% of respondents “strongly agreed” or “agreed” that the digital navigation program was helpful in preparing for their procedure at YNHH and Mount Sinai locations, respectively. Conclusions Our single-site study at AZCDH paved the way to implementing digital navigation pathways at YNHH and Mount Sinai endoscopy locations by demonstrating that colonoscopy instructions are well received by patients, can reduce the rate of aborted procedures and can result in higher patient satisfaction as well as a higher quality of bowel preparation. Further, patient engagement rates and satisfaction with the program was consistent at all sites across the US where the digital navigation program has been implemented. In the future, we plan to report on patient outcomes (including reduction in no shows, poor bowel preparation) to allow benchmarking on a national scale.
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 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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».