Is There a Tension between Clinical Practice and Reimbursement Policy? The Case of Osteoarthritis Prescribing Practices in Ontario
Notice bibliographique
Résumé
BACKGROUND: Reimbursement policies, such as those used to manage the public drug program for senior citizens in Ontario, focus on providing access to cost-effective drug therapies. These policies may create a dilemma for physicians who want to prescribe a particular drug to a patient, but must factor reimbursement restrictions affecting patient-level access into the prescribing decision. METHODS: Information was collected from 102 physicians about prescriptions given to osteoarthritis patients (n=2,147) aged 65 years or older. Patients' access to prescribed drugs was determined from their insurance coverage and the reimbursement criteria set out in the formulary of the public Ontario Drug Benefit Program (ODBP). Starting from the assumption that physicians would follow published consensus guidelines respecting gastroprotection when prescribing NSAIDs in these at-risk elderly patients, three groups of physicians were identified from the record of their actual prescriptions. Group A physicians (n=14) prescribed non-selective NSAIDs alone to >60% of their patients. Group B physicians (n=26) prescribed an NSAID + gastroprotective agent or a Cox-2 selective NSAID to >70% of their patients. Group C physicians (n=62) were those that fit into neither category. An open-ended question was included in the study questionnaire to elicit physicians' own interpretation of what impact drug coverage had on their prescribing behaviour. RESULTS: No significant differences were found across groups with respect to years or type of practice, or to patient characteristics (LR=3.00, p>.2). Group C physicians were most likely to change their treatment choice in favour of restricted (limited use) drugs when patients met the criteria for reimbursement or had private insurance and therefore did not have to bear the additional cost out-of-pocket (LR=58.5; p<.0001). INTERPRETATION: Most elderly at-risk patients are prescribed NSAIDs according to the prevailing guidelines. We found, however, that 40% of physicians have prescribing behaviour that favours non-evidence-based (Group A) or evidence-based (Group B) prescribing in this clinical setting irrespective of drug coverage. The remaining 60% of physicians appeared to be more responsive in their prescribing behaviour to financial constraints on patients' access to drugs. They also self-identified as most likely to change treatment if drug coverage had been different. These results have important implications for equity and quality of patient care. They also confirm that physicians' knowledge, values and self-efficacy are key determinants of prescribing behaviour and require further study to better understand how medical education and third-party policies and programs that govern pharmaceutical care are integrated into physicans' decision-making.
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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 | 0,038 | 0,021 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».