Team-based innovations in primary care delivery in Quebec and timely physician follow-up after hospital discharge: a population-based cohort study
Notice bibliographique
Résumé
BACKGROUND: Outpatient follow-up has been a key intervention point in addressing gaps in care after hospital discharge. We sought to estimate the association between enrolment in new team-based primary care practices and 30-day postdischarge physician follow-up among older patients and patients with chronic illnesses who were admitted to hospital in Quebec, Canada. METHODS: Patients were selected into this cohort if a primary care physician enrolled them as a "vulnerable patient" between November 2002 and January 2005. Data for this analysis included province-wide health insurance claims for inpatient and outpatient services delivered between November 2002 and January 2009 in Quebec. The primary analysis examined time to the first outpatient postdischarge follow-up service provided by either a primary care physician or a medical specialist. We used marginal structural models to estimate adjusted rates of follow-up with a primary care physician or with a medical specialist by primary care delivery models. RESULTS: We extracted billing data for 312 377 patients that represented 620 656 index admissions for any cause from 2002 to 2009. Rates of 30-day follow-up were 374 visits to primary care physicians and 422 visits to medical specialists per 1000 discharges. Rates of primary care physician follow-up were similar across primary care delivery models, except for patients with very high morbidity; these patients had significantly higher rates of follow-up with a primary care physician if they were enrolled in team-based primary care practices (30-d rate difference [RD] 13.3 more follow-up visits per 1000 discharges, 95% confidence interval [CI] 6.8 to 19.8). Rates of follow-up with a medical specialist were lower among patients enrolled in team-based practices, particularly within 15 days of hospital discharge (15-d RD 25.1 fewer follow-up visits per 1000 discharges, 95% CI 21.1 to 29.1). INTERPRETATION: Our study found lower rates of postdischarge follow-up with a medical specialist among older patients and patients with chronic illness who were enrolled in team-based primary care practices compared with those enrolled in traditional primary care practices. Future research is needed to better understand the role of primary health care service organization in improving acute postdischarge care.
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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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 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 ».