Home Virtual Visits for Outpatient Follow-Up Stroke Care: Cross-Sectional Study
Notice bibliographique
Résumé
BACKGROUND: Timely, in-person access to health care is a challenge for people living with conditions such as stroke that result in frailty, loss of independence, restrictions in driving and mobility, and physical and cognitive decline. In Southeastern Ontario, access is further complicated by rurality and the long travel distances to visit physician clinics. There is a need to make health care more accessible and convenient. Home virtual visits (electronic visits, eVisits) can conveniently connect physicians to patients. Physicians use a secure personal videoconferencing tool to connect to patients in their homes. Patients use their device of choice (smartphone, tablet, laptop, or desktop) for the visit. OBJECTIVE: This study aimed to assess the feasibility and logistics of implementing eVisits in a stroke prevention clinic for seniors. METHODS: A 6-month eVisit pilot study was initiated in the Kingston Health Sciences Centre stroke prevention clinic in August 2018. eVisits were used only for follow-up patient encounters. An integrated evaluation was used to test the impact of the program on clinic workflow and patient satisfaction. Patient satisfaction was evaluated by telephone interviews, using a brief questionnaire. Access and patient satisfaction metrics were compared with concurrent standard of care (patients' prior personal experience with in-person visits). Values are presented as median (interquartile range). RESULTS: There were 75 subjects in the pilot. The patients were aged 65 (56-73.5) years, and 39% (29/75) resided in rural areas. There was a shorter wait for an appointment by eVisit versus in-person (mean 59.98 [SD 48.36] days vs mean 78.36 [SD 50.54] days; P<.001). The eVisit was also shorter, taking on an average of only 10 min to deliver follow-up care with a high degree of patient satisfaction versus 90 (60-112) min for in-person care. The total time saved by patients per eVisit was 80 (50-102) min, 44 (21-69) min of which was travel time. Travel distance avoided by the patients was 30.1 km (11.2-82.2). The estimated total out-of-pocket cost savings for patients per eVisit was Can $52.83 (31.26-94.53). The estimated savings (opportunity cost for in-person outpatient care) for our eVisit pilot project was Can $23,832-$28,584. The patient satisfaction with eVisits was very good compared with their prior personal experience with in-person outpatient care. CONCLUSIONS: The eVisit program was well received by patients, deemed to be safe by physicians, and avoided unnecessary patient travel and expense. It also has the potential to reduce health care costs. We plan to scale the project within the department and the institution.
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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 | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| 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 ».