A comparison between alternative primary care physician payment models: A systematic review and policy analysis
Notice bibliographique
Résumé
Objective: Alternative models of primary care physician payment are being considered by policy-makers as a potential way to contain healthcare expenditures. The purpose of this thesis was to synthesize the evidence for alternative primary care physician payment models on quality and economic outcomes worldwide and to make recommendations with respect to payment models that may improve chronic disease management in Canada. Methods: We first conducted a systematic review, searching selected databases from inception to October 2018, for studies that compared primary care physician payment models. There were no restrictions on language, country, or publication date, however studies were restricted to specific study designs (randomized controlled trial, controlled cohort and interrupted time series). A gray literature search was also conducted. The outcomes considered were quality and access to care, patient and physician satisfaction, clinical outcomes, healthcare utilization and costs. Thirteen studies were selected for synthesis, comparing fee-for-service, capitation, incentive payments, and mixed models. We then identified primary care payment methods currently used in Canada through an environmental scan. We applied evidence from the systematic review to evaluate the impact of the three most promising models on quality, utilization, cost, and implementation feasibility, and made a recommendation. Conclusion: Primary care payment models have moved toward incentive payments and mixed models in recent years, and mixed models have promising effects on cost and utilization overall and for managing chronic disease in primary care in Canada. Incentive payments show low sustainability in quality improvements, and a gap in incentivized and non-incentivized aspects of care. Mixed models have been introduced in primary care in Canada. Based on current evidence, the recommended payment model for Canadian primary care physicians that is most likely to optimize chronic disease management is blended capitation. Future studies should focus on long-term quality improvements and improving the quality of non-incentivized activities in incentive models. Further study would help to elucidate the potential benefit of mixed models, in particular their effect on patient-oriented aspects of care: access, continuity, and quality. More studies are needed to understand how blended capitation payment models affect costs and utilization.
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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 | 0,054 | 0,161 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,010 | 0,019 |
| Bibliométrie | 0,013 | 0,014 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,006 | 0,004 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 ».