Implementation of Shared Decision-Making Within Internet Hospitals in China Based on Patients’ Needs: Feasibility Study and Content Analysis
Notice bibliographique
Résumé
Background Internet hospitals are developing rapidly in China, and their convenient and efficient medical services are being increasingly recognized by patients. Many hospitals have set up their own internet hospitals to provide web-based medical services. Tianjin Medical University General Hospital has established a multidisciplinary and comprehensive internet hospital to provide diversified medical services according to the needs of patients. A way to further improve web-based medical services is by examining how shared decision-making (SDM) can be carried out in internet hospital diagnosis and treatment services, thereby improving patients’ medical experience. Objective The aim of this study was to analyze the feasibility of implementing doctor-patient SDM in internet hospital diagnosis and treatment services based on patients’ needs in China. Methods In this study, the medical data of 10 representative departments in the internet hospital of Tianjin Medical University General Hospital from January 1 to January 31, 2022, were extracted as a whole; 25,266 cases were selected. After excluding 2056 cases with incomplete information, 23,210 cases were finally included in this study. A chi-square test was performed to analyze the characteristics and medical service needs of internet hospital patients in order to identify the strengths of SDM in internet hospitals. Results The internet hospital patients from 10 clinical departments were significantly different in terms of gender (χ29=3425.6; P<.001), age (χ236=27,375.8; P<.001), mode of payment (χ29=3501.1; P<.001), geographic distribution (χ29=347.2; P<.001), and duration of illness (χ236=2863.3; P<.001). Patient medical needs included drug prescriptions, examination prescriptions, medical record explanations, drug use instructions, prehospitalization preparations, further consultations with doctors (unspecified purpose), treatment plan consultations, initial diagnoses based on symptoms, and follow-up consultations after discharge. The medical needs of the patients in different clinical departments were significantly different (χ272=8465.5; P<.001). Conclusions Our study provides a practical and theoretical basis for the feasibility of doctor-patient SDM in internet hospitals and offers some implementation strategies. We focus on the application of SDM in web-based diagnosis and treatment in internet hospitals rather than on a disease or a disease management software. The medical service needs of different patient groups can be effectively obtained from an internet hospital, which provides the practical conditions for the promotion of doctor-patient SDM. Our findings show that the internet hospital platform expands the scope of SDM and is a new way for the large-scale application of doctor-patient SDM.
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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 | 0,010 | 0,023 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,005 | 0,003 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| 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 ».