Design, Implementation, and Evaluation of a Community-Based Phygital Telemonitoring Program for Older Adults: Multisite Retrospective Pilot Study in Singapore
Notice bibliographique
Résumé
Background: Noncommunicable diseases, particularly hypertension, diabetes, hyperlipidemia, and obesity, are on the rise among older adults in Singapore, emphasizing the need for effective screening, monitoring, and educational interventions. The traditional health care model, relying on in-person visits to review patients, poses risks of underreported cases and missed opportunities for early interventions to manage complications. Community-based telemonitoring programs present promising opportunities to extend telehealth services to underserved populations, thereby mitigating the digital divide and addressing health inequalities. Objective: This study aimed to retrospectively evaluate the implementation of a community-based telemonitoring program, the Community Telehealth Service (CTS), developed to reduce digital barriers and raise awareness for regular health screening among older adults in the Singapore community. It also aimed to generate insights for scaling up similar telehealth initiatives in the community. Methods: This retrospective study used the (1) Implementation Research Logic Model, (2) Reach, Effectiveness, Adoption, Implementation, and Maintenance framework, and the Implementation Outcomes Framework to guide the design and evaluation of CTS' implementation strategies. Outcomes covered implementation outcomes (reach, adoption, feasibility, and cost), service outcomes (safety and preliminary effectiveness), and user outcomes (satisfaction). Data were collected from operational statistics and structured user feedback surveys across 3 phases of implementation at different community sites. Results: Over the course of the 3 phases, CTS has reached more than 800 older individuals and 147 health ambassadors, with the participation of community organizations, health care institutions, academic collaborators, corporate sponsors, and government agencies. Operational statistics indicated that CTS was delivered consistently across 3 sites, with improving show-up rates and stable service hours. User feedback was generally positive, citing convenience, perceived value, and appreciation for health ambassador support. However, challenges were noted in referral tracking due to differing workflows across partners and in collecting user feedback, particularly in later phases where the survey was perceived as lengthy and complex for older users. Several areas for improvement were identified, such as incorporating more health assessments, providing more health-related information, and improving the referral process. Conclusions: This early-stage retrospective study suggests that community-based telehealth programs may be a feasible and acceptable approach to delivering preventive services in community settings. While initial findings are promising, further rigorous research is needed to evaluate long-term outcomes, integration with health systems, and potential for scale-up.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
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Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,013 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 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 ».