Factors associated with primary health care contacts by the elderly population in groups of family doctors in Quebec, Canada
Notice bibliographique
Résumé
INTRODUCTION The aging population in Quebec, combined with the chronic disease rise, has increased the health care service use among the elderly population. Therefore, elderly care has largely relied on primary health care (PHC) providers as they are best positioned to care for such population. This influx of PHC physician contacts, both face-to-face and virtual, has become a concern due to the limited PHC physician resources. As such, a clear understanding of the factors contributing to PHC contacts by the elderly population is needed. OBJECTIVES To identify the factors contributing to the number of PHC contacts by the elderly population in Quebec family medicine groups, or Groupes de Medecine de Famille (GMF). METHODS In a cross-sectional design, two main data sources were used: 1) A chart review from the Alzheimer's Plan Evaluation Study provided patient-level factors and the number of PHC contacts. 2) The Quebec Ministry of Health information pertaining to GMF-level factors. A total of 1,919 patients were randomly selected. Eligibility criteria included patients aged 75+ years with a minimum of one PHC contact in a 9-month period. Descriptive analyses of independent variables and the study outcome were performed. Generalized Estimating Equations; GEE models were used to analyze correlated data with binary, discrete, or continuous outcomes. RESULTS Descriptive results:Males represented 40% (768 patients) of the study population. Patient age ranged from 75.0 to 104.0 (mean=81.7, SD=5.0) years. Patients aged 75.0-79.9, 80.0-84.9, and 85+ represented 44.1%, 30.5%, and 25.4% of the population, respectively. Nearly half (49.7%) lived with the family, whereas 20% lived alone. A total of 22,221 medications were retrieved from patient charts to identify chronic diseases. Of those medications, 16,336 were matched to 21 chronic diseases. The number of chronic and non-chronic disease medications ranged from 0 to 33 (mean=8.5, SD=5.3) and 0 to 17 (mean=3.0, SD=2.5) respectively. The number of chronic diseases identified ranged from 0 to 17 (mean=5.7, SD=2.9).Elderly proportion among total registered patients ranged from 7% to 17% (mean=12.1%, SD=3.4%). The number of patients per Full-Time Equivalent (FTE)-physician and FTE-RN ranged from 816 to 2,115 (mean=1,244, SD=439) and from 3,218 to 14,193 (mean 8,048.9, SD=3,909.5), respectively. The number of sites within GMFs ranged from 1 to 8 (mean=3.25, SD=2.5). GMF years of operation ranged from 2.2 to 11 years (mean=7.6, SD=3.0). In terms of the study outcome, total PHC contacts ranged from 1 to 81 (mean=4.4, SD=5.1).GEE results:The "oldest old‟ population group (85+) showed a statistically significant 16.4% increase in PHC contact incidence. Likewise, each additional chronic disease showed an 11% increase in the incidence of PHC contacts. The proportion of elderly population showed a 4.5% decrease in PHC contact incidence for each additional 1% of elderly patients. The number of physicians per FTE physician had a 1.6% decrease in the PHC contact incidence for each additional physician. Moreover, Université Laval-affiliated GMF sites had a 60% higher PHC contact incidence compared to Université de Sherbrooke, our reference (p=0.001). Likewise, public GMFs had an 18.2% lower PHC contact incidence than mixed GMFs. CONCLUSION This study provides an evidence-based description of the delivery of PHC contacts among the elderly. Study findings can guide GMF managers and health policy makers, and assist in the development of well-informed staffing, budgetary plans, and decisions in Quebec.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 source (Gemma direct ou Codex distillé), 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 ».