The Political Economy of the World Health Organization Model Lists of Essential Medicines
Notice bibliographique
Résumé
Policy Points The World Health Organization (WHO) Model Lists of Essential Medicines (EML) aims to select clinically beneficial and cost-effective medicines that ought to be prioritized by health systems based on the priority needs of their populations. However, the rapid evolution within the pharmaceutical sector toward complex, high-priced medicines has challenged WHO decision making in recent years, as evidenced by earlier literature demonstrating inconsistencies in the application of decision criteria and recommendations. Proposed solutions to these challenges focus on technical aspects of the program, such as refining the quality of evidence in applications, improving the connection with guidelines, and using evidence assessment frameworks. Yet, earlier literature has not examined the political challenges that the WHO-as a global health organization-has encountered during the past 20 years. This article examines these challenges by reviewing documents and interviewing stakeholders involved with the WHO EML decision making. A diverse range of stakeholders shape the process to select medicines, each with different interests (e.g., protecting commercial interests versus advocating for access) and ideas (the role of the WHO EML in indirectly resulting in lower prices versus safeguarding low- and middle-income countries from catastrophic expenditure). A lack of data and financial and human resources inhibits evaluation of the impact of the EML and exacerbates the influence of external actors, including which products are reviewed and how they are recommended. As a result, a degree of inconsistency has emerged, both in recommendations and in the concept of essential medicines. CONTEXT: The World Health Organization (WHO) Model Lists of Essential Medicines (EML) aims to help countries select medicines based on the priority needs of their populations. However, rapid evolution within the pharmaceutical sector toward complex, high-priced medicines has challenged WHO decision making, leading to inconsistent decisions. The purpose of this paper is to investigate how political factors impact the WHO EML. METHODS: Document review and semistructured interviews of diverse stakeholder groups with direct experience with the WHO EML, either as stakeholders involved with WHO EML processes (e.g., selection of medicines, observers) or external applications (n = 29). Donabedian's structure-process-outcome framework was combined with the Three I's framework (ideas, interests, and institutions) to understand how political factors shape the WHO EML. FINDINGS: The concept of essential medicines evolved from an original focus on generic medicines in resource-constrained countries to include complex, high-priced therapeutics also relevant to high-income nations. The WHO has never explicitly addressed whom its decisions are for. Some believe the Model Lists have a "symbolic" price-lowering mechanism, whereas others do not (e.g., the pharmaceutical industry concerns to profitability). This tension has led to different ideas and interests driving the EML. A lack of data and human resources inhibits evaluation and exacerbates the influence of external actors. A degree of inconsistency has emerged in the concept and recommendations of essential medicines. CONCLUSIONS: The current debate about the role of the WHO EML centers on the question whether the Model Lists ought to include complex, high-priced medicines. However, this research demonstrates that challenges may have roots deeper than amending decision criteria. At the core of this issue is the role of the list. Defining a strategic vision for the WHO EML, refining decision criteria, and increasing institutional support would align interests, good processes, and, ultimately, contribute to positive societal health outcomes.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| 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 ».