Adapting an Advance Care Planning Intervention Delivered via Telehealth for Older Patients With Acute Myeloid Leukemia and Myelodysplastic Syndromes
Notice bibliographique
Résumé
Background Older patients with acute myeloid leukemia (AML) and myelodysplastic syndromes (MDS) experience high-intensity care (eg, chemotherapy, hospitalization, and life-sustaining treatments) during the end of life. Early advance care planning (ACP) may promote end-of-life care that is more consistent with patients’ values and goals. As the COVID-19 pandemic has resulted in a rapid shift to telehealth, the use of such methods may improve access to ACP among this vulnerable population. Objective In this qualitative study, we aimed to adapt an evidence-based ACP intervention, the Serious Illness Care Program (SICP), to be delivered via telehealth for older adults with AML and MDS. Methods We conducted semistructured interviews with 14 oncology clinicians and 10 palliative care clinicians (physicians, advanced practitioners, and nurses), as well as 15 patients and 4 caregivers. Oncology and palliative care clinicians were recruited if they had cared for at least one patient with AML or MDS in the past year. Eligible patients were aged ≥60 years and had a diagnosis of AML or MDS, and their caregivers, if available, were recruited. Interviews were transcribed and qualitatively coded by 2 independent coders using MAXQDA (VERBI GmbH). We used directed content analyses focused on the content and delivery (telehealth vs in-person ACP) of the SICP. Results The mean ages of clinicians, patients, and caregivers were 48, 71, and 66 years, respectively. Health literacy, which was measured using the 6-item Cancer Health Literacy Test, was high in both patients (score: mean 6; range 0-6) and caregivers (score: mean 6). The majority of participants liked the intent and content of the SICP, with suggestions mainly on wording changes. One patient stated, “I wish I’d had a little of this back in the beginning, it would’ve eased my way through….” Oncologists expressed positive feedback for the SICP language “planting the seeds” of the ACP conversation, emphasizing that “it doesn’t mean that it’s going to happen.” Oncology and palliative care clinicians were comfortable with conducting ACP discussions via telehealth. Providers felt that the use of telehealth in ACP conversations would allow them to “deliver care with less burden.” Most patients and caregivers however were comfortable with conducting ACP conversations via telehealth “after the first couple of appointments [being] in-person” to first establish care. Lastly, providers felt that including a geriatric assessment summary prior to ACP conversations “helps to ground and anchor the discussion,” as it provides a “sense of baseline functionality…[and] quality of life.” Conclusions Overall, the SICP was well received by clinicians, patients, and caregivers. This stakeholder feedback will help us to better understand current barriers to ACP conversations and gauge whether telehealth may be utilized to help improve access to ACP. This feedback will be used to further refine the SICP intervention for a future single-arm pilot study. Trial Registration ClinicalTrials.gov NCT04745676; https://clinicaltrials.gov/ct2/show/NCT04745676 Acknowledgements Funding: R00CA237744, 5UG1CA189961, and R33AG059206. Conflicts of Interest None declared.
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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 | 0,000 | 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 ».