Exploring Care Providers’ Perceptions and Current Use of Telehealth Technology at Work, in Daily Life, and in Education: Qualitative and Quantitative Study
Notice bibliographique
Résumé
BACKGROUND: A telehealth technology education curriculum designed to integrate information technology and telecommunication well has great potential to prepare care providers for health care delivery across space, time, and social and cultural barriers. It is important to assess the readiness level of care providers to use and maximize the benefits of telehealth technology in the health care delivery process. Therefore, this study explored care providers' existing experience using technology in various use contexts and compared their familiarity with telehealth technology's relevant features. OBJECTIVE: This study's objective was to explore care providers' familiarity with using technology in different settings and their perceptions of telehealth-driven care performance to lay a foundation for the design of an effective telehealth education program. METHODS: The study used quantitative and qualitative analyses. The online survey included four items that measured care providers' perceptions of care performance when using telehealth technology. Advanced practice registered nurse students rated each item on a 7-point Likert scale, ranging from 1 ("strongly disagree") to 7 ("strongly agree"). They also responded to three open-ended questions about what kinds of health information technology they use at work, after work, and in their current educational program. RESULTS: A total of 109 advanced practice registered nurse students responded to the online survey and open-ended questionnaire. Most indicated that using telehealth technology enhances care performance (mean 5.67, median 6.0, SD 1.36), helps make their care tasks more effective (mean 5.73, median 6.0, SD 1.30), improves the quality of performing care tasks (mean 5.71, median 6.0, SD 1.30), and decreases error in communicating and sharing information with others (mean 5.35, median 6.0, SD 1.53). In addition, our qualitative analyses revealed that the students used the electronic health records technology primarily at work, combined with clinical decision support tools for medication and treatment management. Outside work, they primarily used video-text communication tools and were exposed to some telehealth technology in their education setting. Further, they believe that use of nonhealth technology helps them use health information technology to access health information, confirm their diagnoses, and ensure patient safety. CONCLUSIONS: This research highlights the importance of identifying care providers' existing experience of using technology to better design a telehealth technology education program. By focusing explicitly on the characteristics of care providers' existing technology use in work, nonwork, and educational settings, we found a potential consistency between practice and education programs in care providers' requirements for technology use, as well as areas of focus to complement their frequent use of nonhealth technologies that resemble telehealth technology. Health policymakers and practitioners need to provide compatible telehealth education programs tailored to the level of care providers' technological familiarity in both their work and nonwork environments.
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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 | 0,000 | 0,001 |
| 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 | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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.
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