Development and implementation of a digital remote symptom monitoring program (RESPONSe) to support patients undergoing IV chemotherapy at a community ambulatory cancer clinic in Richmond, BC, Canada.
Notice bibliographique
Résumé
406 Background: We identified delays in accessing symptom management during treatment as an existing care gap at the Richmond Cancer Clinic. Patient-reported outcome measures (PROMs) have been demonstrated to communication, quality of life, and reduce symptom burden and acute care utilization. The RESPONSe program was initiated to address this gap by implementing a digital remote symptom monitoring (RSM) system paired with a supporting Symptom Management Nurse (SMN). Methods: We designed a digital RSM system to collect PROMs at specific timepoints during the first 6 months of IV chemotherapy initiation, with automated triaging logic to flag symptoms of concern that would result in a phone call from the SMN. Routine surveys include baseline, health-checks on days 3 and 10 post-chemotherapy, and pre-doctor’s-appointment; with optional health checks available anytime. Through competitive procurement, SeamlessMD was selected as the technology partner. From Aug 2023 to Jan 2024, multiple design cycles with dry run testing were held to incorporate branching logic, COSTARS oncology symptom specific questionnaires, automatic triaging flags, immediate self—management tips and links to educational resources. Concurrent development of SMN clinical workflows included in-person patient enrolment, digital dashboard monitoring and integration with the clinical chart. Results: From Jan 22-Apr 30, 2024, 32 patients have been enrolled with 42% over the age of 70. 90% of patients completed the baseline survey, 79% of patients completed at least 1 post-treatment health check and 45% completed at least 1 pre-doctors’-appointment survey. An average of 22 library resources were accessed per patient. Through the system, 19 severe and 34 moderate symptoms were identified. The dashboard prompted 63 telephone calls from the SMN, with a further 28 follow-up calls required. Early 3-month patient experience surveys (n=8) indicate high satisfaction, with 100% of patients saying they would recommend the program to others undergoing treatment. 87.5% of patients felt the system was very helpful in communicating their issues to the clinical team, with 100% reporting very high/extreme satisfaction with the support provided by the SMN. Additionally, 67% of patients felt very satisfied with the RESPONSe program overall. Conclusions: The RESPONSe program demonstrates the potential of digital RSM systems in improving patient-centered care and assisting with symptom reporting and management. Initial results suggest high engagement and patient satisfaction, showing this is a feasible approach in community oncology settings. We will be reviewing acute care utilization to assess the impact of the RESPONSe program on emergency room visits and hospitalization.
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 | 0,001 | 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 ».