Telemedicine in primary care of older adults: a qualitative study
Notice bibliographique
Résumé
BACKGROUND: The COVID-19 pandemic changed the healthcare system, leading to the rapid evolution and implementation of telemedicine (TM). TM has the potential to improve the quality of primary health care and increase accessibility for the population. However, its use may represent challenges for older people, as they may have distinct needs from the general population due to age-related changes in perceptual, motor, and cognitive capacities. We, thus, aimed to identify potential facilitators and barriers to TM use in primary care for older adults and develop recommendations accordingly. METHODS: We conducted a qualitative study to explore the challenges associated with TM use among older adults and healthcare professionals (HCPs) in primary care practice. Interviews were conducted with 29 older adults, and three focus groups involving HCPs from four McGill family medicine sites were organized. Employing a hybrid codebook thematic analysis, guided by the Consolidated Framework for Implementation Research (CFIR), we identified facilitators and barriers affecting the optimal use of TM by older adults and HCPs. We synthesized the results from semi-structured interviews and focus groups. These findings were then presented during a deliberative dialogue with eight participants, including family physicians, nurses, a social worker, and a government-level TM expert, to validate our results. The purpose was to gather feedback, identify and refine actionable recommendations. Subsequently, we utilized a thematic analysis using the same codebook to synthesize findings from the deliberative dialogue. RESULTS: Participants agreed that TM contributed to maintaining the continuity of care and was particularly convenient when there was an existing or established patient-physician relationship or for addressing minor health issues. TM was found to be beneficial for people with limited mobility, reducing their exposure to potentially high-risk environments. However, participants expressed concerns about the lack of visual contact, causing essential details to be overlooked. Additionally, issues related to miscommunication due to language or hearing barriers were identified. HCPs perceived that most older adults did not consider phone consultations a medical act. Participants were open to a hybrid approach, combining in-person consultations and TM, based on their specific health conditions. Building upon these results, we formulated seven key recommendations. CONCLUSIONS: Both older adults and HCPs consider TM a good alternative for accessing healthcare services. To improve the effective use of TM, it's crucial to advocate for a hybrid approach that integrates both in-person and virtual methods. This approach should actively encourage and support individuals in becoming familiar with technological tools.
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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 | 0,017 | 0,018 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,009 | 0,006 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,001 | 0,005 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 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 ».