Digital Solutions for Cancer Survivorship Care
Notice bibliographique
Résumé
Background: Both the National Cancer Institute (NCI) and Institute of Medicine have stressed the importance of survivorship care plans (SCP) for cancer patients/survivors and discussed the significance and importance of required input from survivors and advocates. However, there are many barriers to cancer care coordination and the creation of SCPs, including oncology staff time required to write them. Although survivors valued SCPs and liked them, few survivors or caregivers report receiving survivorship information and in some studies, reported no receipt of an SCP. Digital platforms can support cancer survivorship care by integrating with the existing Electronic Health Record and presenting information in a dynamic and user-friendly format that improves coordination and communication. Objective: In this paper, we describe our involvement of stakeholders, including medical staff, patients/survivors and informal caregivers in developing a user-centered design for TOGETHERCARE, a smartphone app envisioned to provide critical functionality including planning and sharing of the SCP among survivors, physicians, and informal caregivers. Methods: Two interviewers conducted a total of nine semi-structured interviews, including a convenience sample of three health care providers who work with cancer patients, three cancer patients/survivors, and three informal caregivers currently caring for cancer patients/survivors. The interviews with Spanish-speaking patients/survivors and caregivers were conducted with a translator. Notes from the interviews were transcribed into a prepared template. The results were compiled and coded by two members of the core team. Results: We identified areas of consistency in responses between the three different groups in terms of how the application should work, as well as areas of difference. Additional suggestions for features for the application are also presented. Health care providers focused on the efficiency of using the application, features that would improve follow-up visits with patients and reduce the nursing triage, ER visits and readmissions. Survivors and caregivers were more focused on features that would provide assistance with patient appointment schedules, at-home medical tasks and activities of daily living. Although all three groups agreed that there is currently no systematic way for specialists to keep in touch with patients once they have moved to community care, and that SCPs would be useful, the practice of providing SCPs is rarely implemented. Survivors, caregivers, and providers all agreed that they have smartphones and that an app that includes the ability to communicate between the different groups, along with other features such as guidance on assisting with daily medical tasks and activities of daily living would be useful. Conclusions: The pervasiveness of mobile devices and mobile app use provides an opportunity to make survivorship information and plans more readily available to caregivers and survivors, and to incorporate patient outcome reporting. Health care providers, cancer survivors, and informal caregivers all responded positively to a variety of features that could improve the efficiency of cancer care coordination and dynamic SCP provision.
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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 | 0,003 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,005 |
| Science ouverte | 0,001 | 0,006 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,026 | 0,006 |
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 ».