Notice bibliographique
Résumé
Editor—Davey Smith et al have identified some problems with evidence based decision making in health care.1 Nevertheless, when these are set against the deficiencies of much current (non-evidence based) decision making, evidence based decision making still compares favourably. Administrators, facing complex allocation choices within tight budgets, are inclined to focus on economic notions of efficiency and fair play. The rationale is: “If it's not too expensive and seems to help a disadvantaged group we might be prepared to pay for it.” When people are presented with a problem (often the solution is presented first, implying that there must be a problem) they gather whatever information will confirm the merit of the intended intervention as quickly as possible. Inequalities in health are not remedied, nor the health of the population as a whole benefited, by this short term damage control. Computed tomography is important in examining efficacy (the safety and benefits of treatments used under ideal conditions). But to be of value to policymakers, research should seek to identify evidence supporting effectiveness (whether an intervention is likely to do more good than harm in routine use). The evidence needed for sound policymaking should thus be much more comprehensive than attempts to extrapolate dubious principles from the findings of computed tomography. Evidence based decision making is, fundamentally, the process of ensuring that the right questions are asked. Is an intervention safe and effective (will it do more good than harm)? Who needs it? Can it be provided under conditions of equal accessibility? Who is the population at risk, and what are the relevant clinical and social determinants? What change may be expected in the burden of disease? What are the social consequences (what are the implications in power and dominance issues, and what public and private interests are being served)? If decisions are based on such comprehensive evidence then the budgetary issues that follow will be much more accurately circumscribed. Tools exist that can synthesise such data to scientific standards and provide logical and defensible conclusions about impacts on a system, a population, and society.2 Decisions can be then be made that are based on meaningful comparison with interventions competing for the same budget. Ultimately, the aim of decision making in health care should be to achieve not equal health standards (however low the ceiling) but good health for all population groups–or, to put it another way, the best care for the greatest number of people. SUE SHARPLES
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 | 0,006 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,011 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,004 |
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 ».