The administrative burden of medication affordability resources: an environmental scan with implications for health informatics to advance health equity
Bibliographic record
Abstract
OBJECTIVE: To characterize and demonstrate how to reduce the administrative burden experienced by patients when navigating medication affordability resources in the United States. MATERIALS AND METHODS: Informed by administrative burden theory, we conducted an environmental scan of medication affordability resources for atrial fibrillation, and four common comorbidities (diabetes, heart failure, hypertension, and lipid disorder). We systematically searched for resources (eg, patient assistance programs, savings cards and nonprofit support) and extracted information about types, eligibility criteria, needed documentation, and application processes. RESULTS: We identified 66 resources across 12 categories across the five conditions. The resources' varied eligibility criteria, application processes, and requirements for providing sensitive financial documents could introduce multiple administrative costs for patients. DISCUSSION: The volume and complexity of medication affordability resources and related application processes may create substantial administrative burden for patients that could prevent their use-especially when prescribed multiple medications. CONCLUSION: Medication affordability resource informatics tools that reduce administrative burden could advance equitable medication access.
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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 | 0.016 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".