Prescription Tablets in the Digital Age: A Cross-Sectional Study Exploring Patient and Physician Attitudes Toward the Use of Tablets for Clinic-Based Personalized Health Care Information Exchange
Notice bibliographique
Résumé
BACKGROUND: To reduce the cost of health care while increasing efficiency and quality, health systems are seeking innovative means to engage and empower patients. Improved use of information technology and electronic health record (EHR) infrastructure is essential, and required for "meaningful use" as mandated by the federal government. Providing personalized health information using tablets at the point of care could enhance the clinical experience and enable efficient collection of patient reported outcome measures to guide clinical decision making. OBJECTIVE: The aim of this study is to explore patient and provider attitudes and interest in a proposed clinic-based tablet system for personal health information exchange. To provide a context to understand patients' use of tablets during their clinic visit, we also examine patients' current activities and time spent in the waiting room, and their use of health information resources. METHODS: Surveys were administered to 84 patients in the waiting room of a community health center affiliated with Massachusetts General Hospital (MGH) in Boston, MA. This survey included a vignette and illustration describing a proposed tablet-based system in which the patient, upon sign in at the clinic, receives a tablet loaded with personalized information tailored to their specific medical conditions and preferences. Patients were queried about their interest in such a system in comparison to traditional forms of patient education as well as their current health information seeking behaviors and activities and time spent in the waiting room. Interviews with five MGH-affiliated health care providers were conducted to assess their opinions regarding the proposed tablet system. RESULTS: The majority (>60%) of patients were "very" or "extremely" interested in the proposed tablet system and thought it would improve their knowledge about their medical condition (60%), assist them in making healthy choices (57%), and help them to feel more comfortable talking with their provider (55%). Patients thought the system would be more motivating, informative, and engaging than traditional printed health education materials. The tablet system was not considered more effective than face-to-face interaction with providers, though 44% thought it would improve their relationship with their physician. Overall, 91% of respondents were willing to learn how to use a tablet and 75% reported being "very" or "extremely" confident they could use one. Four of the five providers believed that the proposed tablet system would improve clinical workflow and patient education. Patients and providers were concerned about privacy and security of data collected using the tablets. CONCLUSIONS: Both patients and providers were highly amenable to integrating tablets into the clinical experience, and tablets may be useful in improving patients' health knowledge, the collection of patient reported outcome measures, and improved patient-provider communication. Further research into operationalizing such systems and their validation is necessary before integration into standard clinical practice.
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 | 0,004 |
| 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 | 0,000 |
| 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 ».