Optimizing Healthcare at the Population Level: Results of the Improving Cardiovascular Outcomes in Nova Scotia Partnership
Notice bibliographique
Résumé
Disease management is increasingly considered a valid strategy in the chronic care of our aging patient populations with multiple diseases. The Improving Cardiovascular Outcomes in Nova Scotia (ICONS) project examined whether a community-oriented health management partnership would lead to enhanced care and improved outcomes across an entire healthcare system. ICONS was a prospective cohort study, with baseline and repeated measurements of care and outcomes fed back to all project partners, along with other interventions aimed at optimizing care; preceding interval cohorts served as controls to post-intervention cohorts. The setting was the province of Nova Scotia, whose population is approximately 950,000. All 34,060 consecutive adult patients hospitalized in Nova Scotia with acute myocardial infarction (AMI), unstable angina (UA) or congestive heart failure (CHF) October 1997-March 2002 were included. Interventions were a combination of serial audits and feedbacks of practices and outcomes, web-based publication of findings, newsletter-based education and reminders, physician small-group workshops, pharmacy monitoring and compliance programs, care maps, algorithms, discharge forms and patient information cards. Rates of use of evidence-based marker therapies were the primary outcome measure. Secondary measures included one-year, all-cause mortality and re-hospitalization. Evidence-based prescription practices, for all target diseases, continuously and markedly improved over time. At the population level, there were no changes in one-year mortality for any disease state, although use of proven therapies predicted survival at the individual level throughout the five-year period for all disease states. Rates of re-hospitalization decreased significantly for all disease states over the course of ICONS; but most traditional positive and negative predictors of this outcome, like advanced age and use of proven therapies, respectively, were not predictive. ICONS demonstrated that provider prescribing patterns and patient re-hospitalization rates were continuously improved in three disease states and across an entire health system, through a community partnership model of disease management that was sustained over a long time. Further studies are needed to better understand the drivers and modifiers of patient outcomes at the population level.
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 | 0,003 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| 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 ».