Charting the course: Insights into EMR usability from Australian clinicians – A national survey
Notice bibliographique
Résumé
Electronic Medical Record Systems (EMRs) are integral to the work of nursing, medical and allied health professionals in Australia and other countries. Successful adoption of EMR systems is reliant upon their usability and effective use. Usability issues impact safety and quality, workflow, communication, and collaboration. The objective of the study was to measure clinician (nurse, medical and allied health professionals) experience of EMR usability in Australia.We conducted an observational study using a validated, cross-sectional survey, the National Usability-focused Health Information System Scale (NuHISS). Thirteen usability statements collect clinician impressions of EMRs related to ease of use, benefits and collaboration and technical quality. This paper presents responses of Australian clinicians using EMRs in primary care, hospitals and public and private sectors.In 2023, 534 health professionals from Australia submitted valid survey responses. The largest respondent group comprised nurses and midwives, working in publicly funded hospitals and having over three years of experience with the EMR mainly used. A majority (69%) agreed that the EMR system is stable and does not crash and 62% felt that the system responds quickly to inputs. Regarding ease of use of the EMR, 50% disagreed that the arrangement of fields and functions is logical, while 58% found the terminology clear and understandable. Sixty-two percent (62%) disagreed that routine tasks can be performed without extra steps, and 65% felt that significant training to learn the EMR is required. Although 63% agreed it is easy to obtain necessary patient information, 45% disagreed that entering and documenting data is quick and smooth. There were mixed responses regarding the EMR system's role in preventing medication errors, with 50% agreeing that it helps prevent errors and 27% disagreeing. There was agreement (74%) that the EMR system supports collaboration and information sharing within the same health service. Respectively, 51% and 47% disagreed regarding support of their EMR for collaboration between different health services and between clinicians and patients.We highlight the importance of understanding clinicians’ experiences with EMR usability. Our findings suggest areas where EMR usability can be strengthened to enhance user experience and support clinicians in delivering high quality, safe care. The study’s findings provide valuable insights for EMR system developers, vendors, and healthcare organisations, emphasising the need to improve usability to realise the full benefits of EMRs and support a digitally enabled healthcare system. Addressing these issues through targeted interventions is essential to enhance clinician satisfaction with the EMRs used, reduce burnout and improve patient care.
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 | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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 | 0,001 |
| 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.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».