International comparison of hospitalizations and emergency department visits related to mental health conditions across high-income countries before and during the COVID-19 pandemic.
Notice bibliographique
Résumé
Objective To explore variation in rates of acute care utilization for mental health conditions, including hospitalizations and emergency department (ED) visits, across high-income countries before and during the COVID-19 pandemic. Data Sources And Study Setting Administrative patient-level data between 2017 and 2020 of eight high-income countries: Canada, England, Finland, France, New Zealand, Spain, Switzerland, and the United States (US).Study Design Multi-country retrospective observational study using a federated data approach that evaluated age-sex standardized rates of hospitalizations and ED visits for mental health conditions. Principal Findings There was significant variation in rates of acute mental health care utilization across countries. Among the subset of four countries with both hospitalization and ED data, the US had the highest pre-COVID-19 combined average annual acute care rate of 1613 episodes/100,000 people (95% CI: 1428, 1797). Finland had the lowest rate of 776 (686, 866). When examining hospitalization rates only, France had the highest rate of inpatient hospitalizations of 988/100,000 (95% CI 858, 1118) while Spain had the lowest at 87/100,000 (95% CI 76, 99). For ED rates for mental health conditions, the US had the highest rate of 958/100,000 (95% CI 861, 1055) while France had the lowest rate with 241/100,000 (95% CI 216, 265). Notable shifts coinciding with the onset of the COVID-19 pandemic were observed including a substitution of care setting in the US from ED to inpatient care, and overall declines in acute care utilization in Canada and France. Conclusion The study underscores the importance of understanding and addressing variation in acute care utilization for mental health conditions, including the differential effect of COVID-19, across different health care systems. Further research is needed to elucidate the extent to which factors such as workforce capacity, access barriers, financial incentives, COVID-19 preparedness, and community-based care may contribute to these variations. What Is Known On This Topic Approximately one billion people globally live with a mental health condition, with significant consequences for individuals and societies. Rates of mental health diagnoses vary across high-income countries, with substantial differences in access to effective care. The COVID-19 pandemic has exacerbated mental health challenges globally, with varying impacts across countries. What This Study Adds This study provides a comprehensive international comparison of hospitalization and emergency department visit rates for mental health conditions across eight high-income countries. It highlights significant variations in acute care utilization patterns, particularly in countries that are more likely to care for people with mental health conditions in emergency departments rather than inpatient facilities The study identifies temporal and cross-country differences in acute care management of mental health conditions coinciding with the onset of the COVID-19 pandemic.
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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 | 0,000 | 0,000 |
| 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 | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».