PHP139 Which Criteria are Considered in Health Care Decisions? Insights from an International Survey of Policy and Clinical Decision Makers
Notice bibliographique
Résumé
Defining and applying decision criteria are key to accountability and reasonableness in decisionmaking and to ensure the most beneficial allocation of health care resources. Objectives were to gather data on criteria considered by policy and clinical decisionmakers in health care decisions globally. An online questionnaire was developed with 43 criteria organized into 10 clusters. Using snowball sampling, decision makers were invited by an international task force to report which criteria they consider and how these criteria weighed when making decisions on health care interventions in their context. For each criterion, respondents reported “currently considered”, “should be considered” and weight assigned. Differences in proportions of participants reporting consideration of each criterion were explored with inferential statistics across levels of decision (micro, meso, macro), decision-maker perspective, and world region. A total of 140 decision makers (1/3 clinical, 2/3 policy) from 23 countries in five continents completed the survey. Most relevant criteria (top ranked for “Currently considered”, “Should be considered” and weights) were Clinical efficacy/effectiveness, Safety, Quality of evidence, Disease severity and Impact on health care costs. Organizational and skill requirements ranked high for consideration but low for weights. For a majority of criteria, the number of decision makers reporting that they ‘should be considered' was higher than that reporting they are currently considered (P<0.05). For more than 75% of criteria, there were no statistical differences in proportions across levels of decision, perspective and world region. Differences in proportions across several comparisons were statistically significant for criteria: Population priorities, Stakeholder pressure/interests, Capacity to stimulate research, Impact on partnership and collaboration, and Environmental impact (P<0.05). Results suggest a significant international agreement among decision makers on the relevance of a core set of normative and feasibility criteria and on the need to consider a wider range of criteria in decision-making processes. Areas of divergence appear to be principally related to contextual aspects.
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 | 0,029 | 0,032 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| 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 | 0,000 |
| 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 ».