Evaluation of a Telemonitoring System Using Electronic National Early Warning Scores for Patients Receiving Medical Home Care: Pilot Implementation Study
Notice bibliographique
Résumé
Background: Telehealth programs and wearable sensors that enable patients to monitor their vital signs have expanded due to the COVID-19 pandemic. The electronic National Early Warning Score (e-NEWS) system helps identify and respond to acute illness. Objective: This study aimed to implement and evaluate a comprehensive telehealth system to monitor vital signs using e-NEWS for patients receiving integrated home-based medical care (iHBMC). The goal was to improve the early detection of patient deterioration and enhance care delivery in home settings. The system was deployed to optimize remote monitoring in iHBMC and reduce emergency visits and hospitalizations. Methods: The study was conducted at a medical center and its affiliated home health agency in central Taiwan from November 1, 2022, to October 31, 2023. Patients eligible for iHBMC were enrolled, and sensor data from devices such as blood pressure monitors, thermometers, and pulse oximeters were transmitted to a cloud-based server for e-NEWS calculations at least twice per day over a 2-week period. Patients with e-NEWSs up to 4 received nursing or physician recommendations and interventions based on abnormal physiological data, with reassessment occurring after 2 hours. Unlabelled: A total of 28 participants were enrolled, with a median age of 84.5 (IQR 79.3-90.8) years, and 32% (n=9) were male. All participants had caregivers, with only 5 out of 28 (18%) able to make decisions independently. The system was implemented across one medical center and its affiliated home health agency. Of the 28 participants, 27 completed the study, while 1 exited early due to low blood pressure and shortness of breath. The median e-NEWS value was 4 (IQR 3-6), with 397 abnormal readings recorded. Of the remaining 27 participants, 8 participants had earlier home visits due to abnormal readings, 6 required hypertension medication adjustments, and 9 received advice on oxygen supplementation. Overall, 24 out of 28 (86%) participants reported being satisfied with the system. Conclusions: This study demonstrated the feasibility of implementing a telehealth system integrated with e-NEWS in iHBMC settings, potentially aiding in the early detection of clinical deterioration. Although caregivers receive training and resources for their tasks, the system may increase their workload, which could lead to higher stress levels. The small sample size, short monitoring duration, and regional focus in central Taiwan may further limit the applicability of the findings to areas with differing countries, regions, and health care infrastructures. Further research is required to confirm its impact.
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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 | 0,007 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».