Impact of Vaginal Antifungal Products on Utilization of Health Care Services: Evidence from Physician Visits
Bibliographic record
Abstract
BACKGROUND: Recently many medications formerly available only by prescription have been approved for over-the-counter (OTC) status. In 1990, clotrimazole became the first available OTC drug to treat candidal vaginitis. Subsequently several other prescription antifungal medications have also been available in OTC products. One proposed benefit of these switches from prescription to OTC status is a reduction in the utilization of health care services. METHODS: Using National Ambulatory Medical Care Survey data, the average numbers of annual visits for vaginal complaints were estimated for 1985, 1990, and 1994. These years were chosen because they represented periods before, close to, and after the approval of the OTC antifungal preparations. The estimated visits for each year were compared using a chi-square analysis with a sample weight correction. RESULTS: There was a 15% decline in the number of vaginitis visits from 1990 to 1994 that potentially could be attributed to the availability of the OTC antifungal preparations. The decrease in physician visits results in approximately $45 million in direct cost savings and another $18.75 million in indirect savings by reducing time lost from work. CONCLUSIONS: It appears that the availability of OTC anticandidal fungal preparations reduces the number of physician visits for vaginitis, resulting in cost savings.
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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 | 0.004 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".