Evidence-informed health policy 2 – Survey of organizations that support the use of research evidence
Notice bibliographique
Résumé
BACKGROUND: Previous surveys of organizations that support the development of evidence-informed health policies have focused on organizations that produce clinical practice guidelines (CPGs) or undertake health technology assessments (HTAs). Only rarely have surveys focused at least in part on units that directly support the use of research evidence in developing health policy on an international, national, and state or provincial level (i.e., government support units, or GSUs) that are in some way successful or innovative or that support the use of research evidence in low- and middle-income countries (LMICs). METHODS: We drew on many people and organizations around the world, including our project reference group, to generate a list of organizations to survey. We modified a questionnaire that had been developed originally by the Appraisal of Guidelines, Research and Evaluation in Europe (AGREE) collaboration and adapted one version of the questionnaire for organizations producing CPGs and HTAs, and another for GSUs. We sent the questionnaire by email to 176 organizations and followed up periodically with non-responders by email and telephone. RESULTS: We received completed questionnaires from 152 (86%) organizations. More than one-half of the organizations (and particularly HTA agencies) reported that examples from other countries were helpful in establishing their organization. A higher proportion of GSUs than CPG- or HTA-producing organizations involved target users in the selection of topics or the services undertaken. Most organizations have few (five or fewer) full-time equivalent (FTE) staff. More than four-fifths of organizations reported providing panels with or using systematic reviews. GSUs tended to use a wide variety of explicit valuation processes for the research evidence, but none with the frequency that organizations producing CPGs, HTAs, or both prioritized evidence by its quality. Between one-half and two-thirds of organizations do not collect data systematically about uptake, and roughly the same proportions do not systematically evaluate their usefulness or impact in other ways. CONCLUSION: The findings from our survey, the most broadly based of its kind, both extend or clarify the applicability of the messages arising from previous surveys and related documentary analyses, such as how the 'principles of evidence-based medicine dominate current guideline programs' and the importance of collaborating with other organizations. The survey also provides a description of the history, structure, processes, outputs, and perceived strengths and weaknesses of existing organizations from which those establishing or leading similar organizations can draw.
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 | 0,054 | 0,106 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,006 | 0,006 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,004 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 ».