The impact of multiple chronic diseases on ambulatory care use; a population based study in Ontario, Canada
Notice bibliographique
Résumé
BACKGROUND: The prevalence of multiple chronic diseases is increasing and is a common problem for primary health care providers. This study sought to determine the patient and health system burden of multiple chronic diseases among adults in Ontario, Canada, with a focus on the ambulatory health care system (outpatient primary health care and specialist services). METHODS: This population-based study used linked health administrative data from Ontario, Canada. Individuals, aged 20 years or older, who had a valid health card, were included. Validated case definitions were used to identify persons with at least one of the following nine chronic diseases: diabetes, congestive heart failure, acute myocardial infarction, stroke, hypertension, asthma, chronic obstructive lung disease, peripheral vascular disease and end stage renal failure. Prevalence estimates for chronic diseases were calculated for April 1, 2009. Ambulatory physician billing records for the two-year period, April 1, 2008 to March 31, 2010, were used to identify the number of outpatient ambulatory care visits. RESULTS: In 2009, 26.3% of Ontarians had one chronic disease, 10.3% had two diseases, and 5.6% had three or more diseases. Annual mean primary health care use increased significantly with each additional chronic disease. Overall, there were twice as many patient visits to primary health care providers compared to specialists across all chronic disease counts. Among those with multiple diseases, primary health care visits increased with advancing age, while specialist care dropped off. While persons with three or more diseases accounted for a disproportionate share of primary health care visits, the largest number of visits were made by those with no or one chronic disease. CONCLUSIONS: The burden of care for persons with multiple chronic diseases is considerable and falls largely on the primary health care provider. However persons with no or one chronic disease are responsible for the largest number of ambulatory health care visits overall. Continued investment in primary health care is needed both to care for those with multiple diseases and to prevent the accumulation of chronic diseases with aging.
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 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) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| 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 ».