Emergency department utilization and hospital admissions for ambulatory care sensitive conditions among people seeking a primary care provider during the COVID-19 pandemic
Notice bibliographique
Résumé
BACKGROUND: Primary care attachment improves health care access and health outcomes, but many Canadians are unattached, seeking a provider via provincial wait-lists. This Nova Scotia-wide cohort study compares emergency department utilization and hospital admission associated with insufficient primary care management among patients on and off a provincial primary care wait-list, before and during the first waves of the COVID-19 pandemic. METHODS: We linked wait-list and Nova Scotian administrative health data to describe people on and off wait-list, by quarter, between Jan. 1, 2017, and Dec. 24, 2020. We quantified emergency department utilization and ambulatory care sensitive condition (ACSC) hospital admission rates by wait-list status from physician claims and hospital admission data. We compared relative differences during the COVID-19 first and second waves with the previous year. RESULTS: During the study period, 100 867 people in Nova Scotia (10.1% of the provincial population) were on the wait-list. Those on the wait-list had higher emergency department utilization and ACSC hospital admission. Emergency department utilization was higher overall for individuals aged 65 years and older, and females; lowest during the first 2 COVID-19 waves; and differed more by wait-list status for those younger than 65 years. Emergency department contacts and ACSC hospital admissions decreased during the COVID-19 pandemic relative to the previous year, and for emergency department utilization, this difference was more pronounced for those on the wait-list. INTERPRETATION: People in Nova Scotia seeking primary care attachment via the provincial wait-list use hospital-based services more frequently than those not on the wait-list. Although both groups have had lower utilization during COVID-19, existing challenges to primary care access for those actively seeking a provider were further exacerbated during the initial waves of the pandemic. The degree to which forgone services produces downstream health burden remains in question.
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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 | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,004 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| 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 ».