The Impact of Primary Care Practice Models on Indicators of Unplanned Health Care Utilization for Ontario Adults Newly Diagnosed With Chronic Obstructive Pulmonary Disease: A Retrospective Cohort Study
Notice bibliographique
Résumé
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a highly prevalent chronic disease. Most of the care for this population occurs within the primary care setting; however, the extent to which different primary care practice models influence the outcomes of patients with COPD remains unclear. OBJECTIVE: The study aimed to compare and analyze the influence of different primary care practice models on indicators of unplanned health care utilization among newly diagnosed COPD patients in Ontario. DESIGN: A retrospective cohort study was conducted using health administrative database within the Institute for Clinical Evaluative Sciences. The cohort included persons who were 35 years and older with physician-diagnosed COPD between January 1, 2014 and December 31, 2019. Patients were assigned into 3 practice models: team-based, traditional, and no enrolment. The primary outcomes examined was unplanned health care utilization, specifically emergency department (ED) visits and hospitalizations. To account for excessive zero values, the zero inflated negative binomial (ZINB) models were used to analyze the association between different practice models and unplanned health care utilization. RESULTS: Among 57,145 individuals who met the inclusion criteria, 55,994 were included in the regression analysis. Of the included participants, 62.8% of patients were in the traditional group, 30.3% were in the team-based group, and 6.9% were in the no enrolment group. Between 2014 and 2019, 70.7% of the cohort had at least 1 all-cause ED visit without hospitalization. The adjusted ZINB models showed no significant difference in risks of experiencing an unplanned health care utilization between the team-based and traditional groups. However, patients in the no enrolment group had a significantly higher risk of ED visit without hospitalization regardless of cause, ED visit with hospitalization regardless of cause, and 30-day readmissions regardless of cause. CONCLUSIONS: Primary care practice models are complex, influenced by remuneration and organizational structures, reinforcing the need for further research to enhance our understanding of primary care reforms. Furthermore, given the growing shortage of primary care providers, patients with COPD and other chronic conditions are particularly vulnerable.
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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 | 0,004 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,004 |
| 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 ».