Telehealth Perceptions Among US Immigrant Patients: Cross-sectional Study Within an Academic Internal Medicine Practice
Notice bibliographique
Résumé
Background The use of telemedicine has increased dramatically through the COVID-19 pandemic. While data are available about patient satisfaction with health care through telemedicine, little is known about the immigrant patient experience. Objective We investigated whether immigrant patients would prefer in-person visits and have higher ratings for interpersonal communication during in-person rather than telemedicine visits. We hoped to identify the reasons behind immigrant visit preferences and consider these reasons to guide suggestions for more equitable use of and access to visit options. Methods Overall, 270 patients including 122 immigrants and 148 nonimmigrants were seen by 4 internal medicine providers in either an in-person (n=132) or telemedicine (n=138) university practice setting. Immigrants were defined as having been born outside of the United States. Patients were queried between February and April 2021 using an adaptation of a previously validated patient satisfaction survey containing standard questions developed by the Consumer Assessment of Healthcare Providers and Systems Program. Patients seen via in-person visits completed a paper copy of the survey. The same survey was administered by a follow-up phone call for telemedicine visits. Patients surveyed spoke English, Spanish, or Arabic and were surveyed in their preferred language. For televisits, the same survey was read to the patient by a certified translator. The survey comprised 9 questions on a 5-point Likert scale assessing satisfaction under the categories of access to care, interpersonal interaction, quality of care, and next visit preference. An additional write-in question assessed reasons for subsequent visit type preferences. Survey question responses were compared with paired t tests. Results Across both immigrant and nonimmigrant patient populations, satisfaction with perceived quality of care was universally high regardless of visit type (televisits: P=.80 and P=.60; in-person: P=.76 and P=.37). During televisits, immigrants were more likely than nonimmigrants to feel that providers spent sufficient time with them (P<.001). Different perceptions were noted among nonimmigrant patients. Nonimmigrants tended to perceive more provider time during in-person visits (P=.006). When asked to comment on reasons behind subsequent visit preference, nonimmigrant patients prioritized convenience, whereas immigrants noted the telemedicine advantage of not having to navigate other office logistics. Conclusions While satisfaction was quite high for both telemedicine and in-person visits across immigrant and nonimmigrant populations, significant differences in patient priorities were identified. Immigrants found televisits desirable because they felt they spent more time with their providers and were able to avoid additional office logistics that are often challenging barriers for non-English speakers. This suggests opportunities to use information technology to provide cultural and language-appropriate information throughout the in-person and telemedicine visit experience of immigrants, such as assistance with call-in scheduling, appointment reminders, and portal access. A focus on diminishing these barriers will help reduce health care inequities among immigrant patients. Conflicts of Interest None declared.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 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 ».