Cross‐Country Measures for Monitoring Epilepsy Care
Bibliographic record
Abstract
PURPOSE: The International League Against Epilepsy (ILAE) Commission on Healthcare Policy in consultation with the World Health Organization (WHO) examined the applicability and usefulness of various measures for monitoring epilepsy healthcare services and systems across countries. The goal is to provide planners and policymakers with tools to analyze the impact of healthcare services and systems and evaluate efforts to improve performance. METHODS: Commission members conducted a systematic literature review and consulted with experts to assess the nature, strengths, and limitations of the treatment gap and resource availability measures that are currently used to assess the adequacy of epilepsy care. We also conducted a pilot study to determine the feasibility and applicability of using new measures to assess epilepsy care developed by the WHO including Disability-Adjusted Life Years (DALYs), responsiveness, and financial fairness. RESULTS: The existing measures that are frequently used to assess the adequacy of epilepsy care focus on structural or process factors whose relationship to outcomes are indirect and may vary across regions. The WHO measures are conceptually superior because of their breadth and connection to articulated and agreed upon outcomes for health systems. However, the WHO measures require data that are not readily available in developing countries and most developed countries as well. CONCLUSION: The epilepsy field should consider adopting the WHO measures in country assessments of epilepsy burden and healthcare performance whenever data permit. Efforts should be made to develop the data elements to estimate the measures.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.075 | 0.146 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.015 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".