Patient-Centric Mobile Medical Services Accessed Through Smartphones in the Top 100 Chinese Public Hospitals: Cross-Sectional Survey Study
Notice bibliographique
Résumé
BACKGROUND: Smartphone-based technology has been used to enhance the delivery of health care services to the public in numerous countries. OBJECTIVE: This study aims to investigate the application of patient-centric mobile medical services accessed through smartphones in the top 100 Chinese public hospitals. METHODS: Data on 124 tertiary public hospitals, ranked among the top 100 by the China Hospital Science and Technology Evaluation Metrics of the Chinese Academy of Medical Sciences (2019) and China's Hospital Rankings of the Hospital Management Institute of Fudan University (2019), were collected from the WeChat platform (Tencent Inc), mobile phone apps, and official websites until February 10, 2021. RESULTS: A total of 124 tertiary public hospitals, all of which were among the top 100 hospitals according to the 2 ranking lists, were selected for this study. Almost all (122/124, 98.39%) of the hospitals offered basic services such as appointment scheduling, registration, and health education. The majority also provided online access to test reports (95/124, 76.61%), consultations (72/124, 58.06%), and prescriptions (61/124, 49.19%). Among the hospitals offering online prescriptions, the majority (54/61, 88.52%) supported home delivery through third-party carriers. Slightly less than half (57/124, 45.97%) used artificial intelligence for medical guidance. Only a small fraction (8/124, 6.45%) managed chronic diseases through online monitoring and supervision by experienced doctors. Approximately half (60/124, 48.39%) of the included hospitals were officially licensed as internet hospitals approved to provide full online services. Hospitals with official internet hospital licenses provided more extensive digital health offerings. A significantly higher proportion of approved hospitals offered online consultations (29.69% vs 88.33%, r=43.741; P<.001), test reports (62.5% vs 91.67%, r=14.703; P<.001), and chronic disease management (1.56% vs 11.67%, r=5.238; P<.05). These officially approved hospitals tended to provide over 6 mobile medical services, mainly in the regions of Shanghai and Guangdong. This geographic distribution aligned with the overall layout of hospitals included in the study. CONCLUSIONS: Patient-centric mobile medical services offered by the top 100 Chinese public hospitals accessed through smartphones primarily focus on online appointment scheduling, registration, health education, and accessing test reports. The most popular features include online consultations, prescriptions, medication delivery, medical guidance, and early-stage chronic disease management. Approved internet hospitals offer a significantly greater variety of patient-centric mobile medical services compared with unapproved ones.
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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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| 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 ».