Defining user needs for an electronic tool to improve chemotherapy-related toxicity management.
Notice bibliographique
Résumé
157 Background: Cancer drugs are associated with toxicities which can negatively impact patients’ (pts) quality of life, outcomes and increase acute care use (ACU). There is increasing interest in leveraging technology to solve clinical problems in healthcare. We hypothesized that an electronic tool (toxicity module) targeting management of chemotherapy toxicities could decrease ACU by facilitating more effective symptom management. Methods: Participatory design methodology consisting of end user needs assessment through ethnographic field study (shadowing and in-depth interviews) and focus groups was used to inform design of an interactive prototype toxicity module. Oncology pts and their caregivers, and health care providers (HCPs) including oncologists, oncology nurses and primary care providers were included in all stages of development. Contemporaneous notes were taken during ethnography while focus groups were also audio recorded. Thematic analysis through ideation sessions and time-of-day exercises allowed identification of overarching issues. Results: Eight pts and 8 HCPs participated in the ethnographic field study. Two focus groups, one with 7 pts, one with 4 HCPs were held. Most themes were common to both pts and HCPs; gaps and barriers in the current system, need for decision aids, improved HCP communication and options in care delivery, and access to credible information delivered in a timely, secure manner and integrated into existing systems. Additionally, pts further identified missed opportunities, care not meeting their needs, feeling overwhelmed and anxious and wanting to be more empowered; HCPs identified accountability as an issue. These themes informed development of a prototype for a web-based toxicity management tool, which has served the purpose of defining user needs for symptom tracking, self-management advice, and timely communication with an oncology provider. Iterative evaluation over 2 rounds of usability testing is currently underway. Conclusions: An electronic tool that integrates just-in-time self-management advice and oncology provider support into routine care may address some of the gaps identified in the current system for managing chemotherapy toxicity.
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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) | 0,001 | 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) | 0,001 | 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 ».