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Enregistrement W4362652860 · doi:10.2196/40983

A Digital-First Health Care Approach to Managing Pandemics: Scoping Review of Pandemic Self-triage Tools

2023· article· en· W4362652860 sur OpenAlex
Christina Ziebart, Marisa Kfrerer, Meagan Stanley, Laurel Austin

Pourquoi ce travail est dans la base

Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.

affAu moins un auteur déclare une institution canadienne dans l'instantané OpenAlex épinglé.
fundUn bailleur canadien est enregistré sur le travail.

Notice bibliographique

RevueJournal of Medical Internet Research · 2023
Typearticle
Langueen
DomaineHealth Professions
ThématiqueDisaster Response and Management
Établissements canadiensWestern University
Organismes subventionnairesIvey Business School, Western UniversityCanadian Institutes of Health Research
Mots-clésCINAHLTriagePsycINFOPandemicHealth careMEDLINEUsabilityScopusDigital healthMedicineTelemedicineNursingMedical emergencyCoronavirus disease 2019 (COVID-19)Computer sciencePsychological interventionPolitical science

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: During the COVID-19 pandemic, many patient-facing digital self-triage tools were designed and deployed to alleviate the demand for pandemic virus triage in hospitals and physicians' offices by providing a way for people to self-assess their health status and get advice on whether to seek care. These tools, provided via websites, apps, or patient portals, allow people to answer questions, for example, about symptoms and contact history, and receive guidance on appropriate care, which might be self-care. OBJECTIVE: This scoping review aimed to explore the state of literature on digital self-triage tools that direct or advise care for adults during a pandemic and to explore what has been learned about the intended purpose, use, and quality of guidance; tool usability; impact on providers; and ability to forecast health outcomes or care demand. METHODS: A literature search was conducted in July 2021 using MEDLINE, Embase, Scopus, PsycINFO, CINAHL, and Cochrane databases. A total of 1311 titles and abstracts were screened by 2 researchers using Covidence, and of these, 83 (6.76%) articles were reviewed via full-text screening. In total, 22 articles met the inclusion criteria; they allowed adults to self-assess for pandemic virus, and the adults were directed to care. Using Microsoft Excel, we extracted and charted the following data: authors, publication year and country, country the tool was used in, whether the tool was integrated into a health care system, number of users, research question and purpose, direction of care provided, and key findings. RESULTS: All but 2 studies reported on tools developed since early 2020 during the COVID-19 pandemic. Studies reported on tools that were developed in 17 countries. The direction of care advice included directing to an emergency room, seeking urgent care, contacting or seeing a physician, being tested, or staying at home and self-isolating. Only 2 studies evaluated tool usability. No study demonstrated that the tools reduce demand on the health care system, although at least one study suggested that data can predict demand for care and that data allow monitoring public health. CONCLUSIONS: Although self-triage tools developed and used around the world have similarities in directing to care (emergency room, physician, and self-care), they differ in important ways. Some collect data to predict health care demand. Some are intended for use when concerned about health status; others are intended to be used repeatedly by users to monitor public health. The quality of triage may vary. The high use of such tools during the COVID-19 pandemic suggests that research is needed to assess and ensure the quality of advice given by self-triage tools and to assess intended or unintended consequences on public health and health care systems.

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.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,021
score de la tête « metaresearch » (Gemma)0,006
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,433
Score d'incertitude au seuil0,803

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0210,006
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,001
Intégrité de la recherche0,0000,002
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,291
Tête enseignante GPT0,568
Écart entre enseignants0,278 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle