Taking care of the most vulnerable : a descriptive study of patients with 12 attendances or more at a Swiss university hospital emergency department in 2009
Notice bibliographique
Résumé
Introduction: Patients who repeatedly attend the Emergency Department (ED) often have a distinct and complex vulnerability profile that includes poor somatic, psychological, and social indicators. This profile has an impact on the patients' well-being as well as on hospital costs. The objective of the study was to specify the characteristics of hyper users (HU) and explore the connection with ED care and hospital costs. Methods: The study sample comprised all adult patients with 12 or more attendances at the ED of the Lausanne University Hospital in 2009. The data were collected by retrospectively searching internal databases to identify the patients concerned and then analysing the profiles of these patients. Information gathered included demographic, somatic, psychological, at-risk behaviour, and social indicators, and health system consumption including costs. Results: In 2009, 23 patients (0.1%) attended 12 times or more (425 attendances, 0.8%). The average age was about 43 years, 60.9% were female, and 47.8% single. Of these 95.7% had basic insurance, 87.0% had a general practitioner, and 30.4% were under legal guardianship. The majority attended in the evening or at night (67.1%), and almost one quarter of these attendances resulted in inpatient treatment (24.0%). Most HU had attended the ED in previous years too (95.7% in 2008). The most prevalent diagnoses concerned 'mental disorders' (87.0%). About 30.4% of patients had attempted suicide (all were female patients). Other frequent diagnoses concerned 'trauma' (65.2%), and the 'digestive' and the 'nervous system' (each 56.5%). At-risk behaviour such as severe alcohol consumption (34.8%), or excessive use of medicines (26.1%) was very frequent, and some patients used illicit drugs (21.7%). There was only a weak association between the number of ED attendances and the resulting costs. However, a reduction of one outpatient visit per patient would have decreased ED outpatient costs by 8.5%. Conclusions: HU often have a particularly vulnerable profile. Mental problems are prevalent among them, as are at-risk behaviour and severe somatic conditions. The complexity of the patients' profiles demands specific care that cannot be guaranteed within an everyday ED routine. The use of an interdisciplinary case management team might be a promising approach in diminishing the number of attendances and the associated costs, although the profiles of HU are such that they probably cannot completely give up ED attendance.
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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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 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.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».