THE EFFECTS OF PRESCRIPTION DRUG COST SHARING: EVIDENCE FROM THE MEDICARE MODERNIZATION ACT
Bibliographic record
Abstract
This study assesses the impact of reductions in cost sharing for prescription drugs on preventable hospitalizations and outpatient care utilization among the elderly in the United States. In addition to affecting demand for drugs, drug cost sharing can also affect the demand for complement services, such as primary or preventive care. In order to evaluate this possibility, I analyze the effects of varying patient cost sharing for prescription drugs on hospitalizations from ambulatory care sensitive conditions (ACSC), which can represent a failure of preventive and outpatient care. To address endogeneity from selection and sorting of individuals into insurance plans, I aggregate data from the 2000-2009 Medical Expenditure Panel Survey (MEPS) to the region-year level, and use an instrumental variables strategy. The analysis exploits exogenous variation in prescription drug cost sharing that occurred as a result of the Medicare Modernization Act of 2003, and therefore plausibly identifies causal effects of cost sharing. Results show that for the elderly in the United States, who have generous insurance coverage for other outpatient services, reductions in prescription drug cost sharing do not have an effect on hospitalizations related to ambulatory care sensitive conditions, or on specific types of preventive care utilization.
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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 | 0.008 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".