Visit Types in Primary Care With Telehealth Use During the COVID-19 Pandemic: Systematic Review
Notice bibliographique
Résumé
BACKGROUND: Telehealth was rapidly incorporated into primary care during the COVID-19 pandemic. However, there is limited evidence on which primary care visits used telehealth. OBJECTIVE: The objective of this study was to conduct a systematic review to assess what visit types in primary care with use of telehealth during the COVID-19 pandemic were reported; for each visit type identified in primary care, under what circumstances telehealth was suitable; and reported benefits and drawbacks of using telehealth in primary care during the COVID-19 pandemic. METHODS: This study was a systematic review using narrative synthesis. Studies were obtained from four databases (Ovid [MEDLINE], CINAHL Complete, PDQ-Evidence, and ProQuest) and gray literature (NSW Health, Royal Australian College of General Practitioners guidelines, and World Health Organization guidelines). In total, 3 independent reviewers screened studies featuring telehealth use during the COVID-19 pandemic in primary care. Levels of evidence were assessed according to the Grading of Recommendations Assessment, Development, and Evaluation. Critical appraisal was conducted using the Mixed Methods Appraisal Tool. Benefits and drawbacks of telehealth were assessed according to the National Quality Forum Telehealth Framework. RESULTS: A total of 19 studies, predominately cross-sectional surveys or interviews (13/19, 68%), were included. Seven primary care visit types were identified: chronic condition management (17/19, 89%), existing patients (17/19, 89%), medication management (17/19, 89%), new patients (16/19, 84%), mental health/behavioral management (15/19, 79%), post-test result follow-up (14/19, 74%), and postdischarge follow-up (7/19, 37%). Benefits and drawbacks of telehealth were reported across all visit types, with chronic condition management being one of the visits reporting the greatest use because of a pre-existing patient-provider relationship, established diagnosis, and lack of complex physical examinations. Both patients and clinicians reported benefits of telehealth, including improved convenience, focused discussions, and continuity of care despite social distancing. Reported drawbacks included technical barriers, impersonal interactions, and semi-established reimbursement models. CONCLUSIONS: Telehealth was used for different visit types during the COVID-19 pandemic in primary care, with most visits for chronic condition management, existing patients, and medication management. Further research is required to validate our findings and explore the long-term impact of hybrid models of care for different visit types in primary care. TRIAL REGISTRATION: PROSPERO CRD42022312202; https://tinyurl.com/5n82znf4.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,004 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| 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 tête enseignante, 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 ».