Notice bibliographique
Résumé
A position paper developed by the Canadian Psychiatric Association s Standing Committee on Scientific Affairs and Research and approved by the Canadian Psychiatric Association s Board of Directors on April 8, 2011. Introduction There is a growing concern that Canadians who are dependent on public drug programs do not have equal access to emerging new medications for mental disorders, compared with those who have private drug insurance coverage. There are also inequities in public drug plans among the provinces and territories. As pharmacologic treatment is often the best first-line treatment for, or the major treatment component of, severe mental disorders, the Canadian Psychiatric Association (CPA) remains committed to improving the mental health of all Canadians, by ensuring the availability and accessibility of effective and safer medications to meet the mental health needs of the population. This position paper addresses pertinent issues and complexities relating to the drug approval process, cost-effective analysis, and cost-containment strategies, and it provides recommendations on improving accessibility to new medications for mental disorders based on an individual patient's clinical treatment needs. Background Social and Economic Burden of Mental Disorders Mental illness affects Canadians irrespective of age, sex, education, income, and ethnicity, either directly or indirectly, through a family member, friend, or colleague. About 20 per cent of Canadians personally experience a mental illness in their lifetime. Chronic major psychiatric disorders, such as schizophrenia and bipolar disorder (BD) type I, individually affect one per cent of the population and their families. Further, one in four women and one in 10 men can expect to develop a depressive episode.1 Given these statistics, in 2003, the cost of mental illness in Canada was estimated at $5 1 billion a year in health care and lost productivity.2 Pharmacologic treatment remains the most important component in the management of major psychiatric disorders, such as schizophrenia, BD, and severe major depression. Medication treatment is often supported by appropriate psychosocial interventions to regain baseline functioning, productivity, and overall recovery. Despite significant progress in the pharmacologic treatment of mental disorders in the last two decades, the burden of mental illness is growing in Canada and worldwide. According to the World Health Organization,' psychiatric conditions, such as depression, schizophrenia, BD, and alcohol and drug abuse, are the most important causes of disability, accounting for one-third of years lost owing to disability among adults aged 1 5 years and older. Limitations in Current Pharmacotherapy Several complex factors are involved in translating the evidence-based treatment to individualized optimum treatment of mental illness, and optimum treatment does not always produce an optimal outcome in each patient. The efficacy data generated from randomized controlled trials (RCTs) cannot be generalized to real-world patients because of selection bias (that is, inclusion of selective patients) in clinical trials. The data from a large sample of patients in an RCT may not be clinically useful to select the right treatment of individual patients because of huge interindividual variations in treatment responses and tolerability. There is limited understanding of the wide differences in treatment responsiveness, medication tolerability, clinical outcome, and biologic risk factors for mental illnesses. Currently, there are no clinically or biologically useful methods to predict responders from nonresponders to specific treatments. Several potential predictors (such as clinical, demographic, genetic, endocrine, and proteomic, and neuroimaging markers) of clinical outcomes have not yet been shown to be reliable for routine clinical use.4 Hence the availability of a wide choice of medications is essential to provide the best treatment possible for the individual patient's response and tolerability to medications. …
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 | 0,004 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,005 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,004 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,193 | 0,058 |
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 ».