Family Caregivers’ Perspectives on the Potential of Drone-Based Medication Delivery in Palliative Home Care: Qualitative Focus Group Study
Notice bibliographique
Résumé
Background: Palliative care supports individuals with incurable, life-threatening illnesses, focusing on symptom management and quality of life. Access to timely care, including essential medications, is often limited, particularly in rural areas, leading to gaps in home-based care. Digital health technologies, including drone-based delivery systems, have the potential to address such logistical challenges. For these technologies to be effective, they must be adapted to the specific needs of patients and caregivers, which often differ from general health care contexts, especially in remote areas. Objective: This study aimed to identify user needs and requirements for a drone-based medication delivery system designed to supplement traditional courier services in palliative care. The study also sought to explore practical considerations for integrating drones into home-based care workflows, with the goal of informing both technical design and clinical applicability. Methods: We conducted 1 focus group (FG) and 4 semistructured individual interviews with family caregivers involved in home-based palliative care. Participants were recruited via local palliative care services in rural regions. The discussions focused on experiences with palliative care, medication logistics, needs, expectations, and concerns regarding drone-assisted delivery. Interviews and the FG were audio-recorded, transcribed, and analyzed using structured qualitative content analysis. Results: A total of 10 caregivers participated (mean age 68.6, SD 12.3 years) in this study. Six participants took part in the FG and 4 participants were part of individually conducted interviews. Caregivers frequently reported long travel distances to obtain medications, sometimes leaving patients unattended and noting medication shortages, especially in the afternoons and on weekends. Participants highlighted the potential of drones to supplement existing courier services during periods of high demand. At the same time, caregivers expressed concerns about limited technical skills, particularly regarding mobile apps for ordering deliveries, and emphasized the need for simple, user-friendly systems. . Conclusions: These findings reveal logistical gaps in palliative care medication supply and design requirements for drone-based delivery systems. There is a clear demand for faster, more reliable access to essential medication, especially during evenings and weekends. Whether drone-assisted delivery can reduce hospitalizations and support patients' wishes to remain at home warrants further research. Specialized outpatient palliative care teams are central to eHealth adoption, providing technical guidance, emotional support, and confidence in using new technologies. Their involvement in communication and training is critical. Strengthening digital health literacy requires individual training and structural adjustments to meet the needs of older caregivers and those with limited digital affinity. Concerns about losing personal interaction remain significant; digital tools should complement, not replace, face-to-face care. Timely medication access could reduce caregiver stress and improve quality of life by supporting symptom control at home. To foster acceptance, caregivers need hands-on experience. Future studies should test drone delivery in real-world settings, addressing technological, psychological, and social factors.
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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.
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