Comparing International Experiences With Electronic Health Records Among Emergency Medicine Physicians in the United States and Norway: Semistructured Interview Study
Notice bibliographique
Résumé
BACKGROUND: The variability in physicians' attitudes regarding electronic health records (EHRs) is widely recognized. Both human and technological factors contribute to user satisfaction. This exploratory study considers these variables by comparing emergency medicine physician experiences with EHRs in the United States and Norway. OBJECTIVE: This study is unique as it aims to compare individual experiences with EHRs. It creates an opportunity to expand perspective, challenge the unknown, and explore how this technology affects clinicians globally. Research often highlights the challenge that health information technology has created for users: Are the negative consequences of this technology shared among countries? Does it affect medical practice? What determines user satisfaction? Can this be measured internationally? Do specific factors account for similarities or differences? This study begins by investigating these questions by comparing cohort experiences. Fundamental differences between nations will also be addressed. METHODS: We used semistructured, participant-driven, in-depth interviews (N=12) for data collection in conjunction with ethnographic observations. The conversations were recorded and transcribed. Texts were then analyzed using NVivo software (QSR International) to develop codes for direct comparison among countries. Comprehensive understanding of the data required triangulation, specifically using thematic and interpretive phenomenological analysis. Narrative analysis ensured appropriate context of the NVivo (QSR International) query results. RESULTS: Each interview resulted in mixed discussions regarding the benefits and disadvantages of EHRs. All the physicians recognized health care's dependence on this technology. In Norway, physicians perceived more benefits compared with those based in the United States. Americans reported fewer benefits and disproportionally high disadvantages. Both cohorts believed that EHRs have increased user workload. However, this was mentioned 2.6 times more frequently by Americans (United States [n=40] vs Norway [n=15]). Financial influences regarding health information technology use were of great concern for American physicians but rarely mentioned among Norwegian physicians (United States [n=37] vs Norway [n=6]). Technology dysfunctions were the most common complaint from Norwegian physicians. Participants from each country noted increased frustration among older colleagues. CONCLUSIONS: Despite differences spanning geographical, organizational, and cultural boundaries, much is to be learned by comparing individual experiences. Both cohorts experienced EHR-related frustrations, although etiology differed. The overall number of complaints was significantly higher among American physicians. This study augments the idea that policy, regulation, and administration have compelling influence on user experience. Global EHR optimization requires additional investigation, and these results help to establish a foundation for future research.
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 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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».