Putting health policy and systems research on the map
Notice bibliographique
Résumé
For four decades, the World Health Organization (WHO) has helped to pioneer the development of the field of health policy and systems research (HPSR). In 1974, WHO Director-General Halfdan Mahler, recognizing the importance of research on the development of sustainable health-care delivery systems, called for an emphasis on health services and systems research.1 Two years later, the Advisory Committee on Medical Research, established by WHO in 1959, endorsed the definition of health services and systems research as “the systematic investigation and evaluation of specific aspects relative to the development and functioning of health services in their relationship with health related factors”.1 These initial efforts were important in increasing awareness of the value of HPSR and in stimulating scientific discourse about its nature and scope, as reflected by the numerous definitions and frameworks for HPSR that have followed since. Towards the end of the twentieth century, WHO helped to bring together as a unified community the diverse disciplines of research that contributed to health systems strengthening. The establishment of the Alliance for Health Policy and Systems Research (AHPSR) in 1999 as a partnership hosted by WHO marked an important milestone for the field of HPSR.2 It not only legitimized HPSR by demonstrating strong commitment and investment of human and financial resources by WHO and global funding agencies, but also provided a platform for international partnership and collaboration and created an identity for this growing field. The value of HPSR was further reinforced by the release of The world health report 2000, which made clear the prominent role of HPSR in improving health systems performance.3 This recognition of the need for and validation of HPSR as a field helped to stimulate growth within the community of researchers and triggered an increase in overall investments by global funding agencies. WHO then shifted its efforts to bridging the worlds of research and policy-making. In 2004 it convened the Ministerial Summit on Health Research in Mexico City, and in 2008 it co-sponsored the Global Ministerial Forum on Research for Health in Bamako, Mali. Both meetings provided policy-makers with a unique opportunity to engage with diverse stakeholders, including academics, funding agencies and the media;4,5 both were pivotal in building linkages to facilitate the use of evidence generated through HPSR in health policy and management decision-making. From these discussions emerged innovations, among them various knowledge translation platforms and the Evidence-Informed Policy Network (EVIPNet) established by WHO, designed to move research into practice. This firm commitment towards the use of evidence was carried forward by WHO’s current Director-General, Margaret Chan, who in 2008 formed the High Level Task Force on Scaling Up Research and Learning for Health Systems.6 More recent actions have further advanced the field of HPSR by helping to identify research priorities and facilitating interactions between evidence generators and evidence users. Prominent among them are the launch in 2010 of WHO’s Research for Health strategy, the organization of global symposia on health systems research in Montreux, Switzerland, and Beijing, China, and the establishment of a society of health system researchers known as Health Systems Global.7,8 Now, with the launch of the Strategy on Health Policy and Systems Research on 1 November 2012, WHO is helping to institutionalize HPSR and facilitate evidence-informed decision-making. To this end, the strategy will promote greater integration of research and decision-making in an effort to embed the evidence generated through research at every stage of the policy-making process. This will result in greater transparency, accountability and mutual learning. The strategy proposes options to strengthen collaboration between researchers and decision-makers and draws on lessons from countries, in all stages of development, that are creating institutional mechanisms to support evidence-informed decision-making. The success of this strategy depends on all stakeholders, and WHO will do its part to ensure that the strategy’s aims are reflected in the work it undertakes and supports. As a first step towards implementing the new strategy, an inter-cluster platform will be established within WHO to facilitate coordination, alignment of priorities and a unified position on HPSR. This platform will promote a “systems approach” to the delivery of health programmes and encourage the use of HPSR to achieve this objective. Second, in collaboration with partners, WHO will lead efforts to monitor, on a biennial basis, Member States’ capacity for investing in and conducting HPSR, as well as their use of the evidence generated by HPSR. By doing so, it aims to help Member States and funders of research to optimize existing resources and identify priorities for future investments. Finally, in collaboration with relevant organizations, including McMaster University in Canada, which hosts Health Systems Evidence,9 WHO will support the establishment of a global repository of evidence generated through programme evaluations, the grey literature and assessments of best practices. This repository will complement the evidence emerging from the peer-reviewed literature and will provide a strong basis for health decision-making and health systems strengthening.
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 | 0,094 | 0,127 |
| Méta-épidémiologie (sens strict) | 0,005 | 0,003 |
| Méta-épidémiologie (sens large) | 0,009 | 0,003 |
| Bibliométrie | 0,023 | 0,019 |
| Études des sciences et des technologies | 0,012 | 0,100 |
| Communication savante | 0,045 | 0,092 |
| Science ouverte | 0,009 | 0,030 |
| Intégrité de la recherche | 0,037 | 0,049 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,031 | 0,008 |
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 ».