The Political Economy of the World Health Organization Model Lists of Essential Medicines
Bibliographic record
Abstract
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".