Economic Benefit of Increasing Utilization of Intravenous Tissue Plasminogen Activator for Acute Ischemic Stroke in the United States
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Health economic analyses of intravenous tissue plasminogen activator (tPA) in acute ischemic stroke reveal a substantial cost savings. Unfortunately, tPA is vastly underused. The purpose of this study was to determine the economic impact of increasing tPA utilization in the United States. METHODS: Annual incidence estimates of ischemic stroke in the United States and individual states were obtained. The proportion of all ischemic stroke patients who receive tPA was derived from published data. Economic analyses that report the expected annual cost savings of tPA were consulted. The analysis was conducted from the perspective of the healthcare system over a time period of 1 year. With incremental increases in the proportion of all ischemic stroke patients treated with tPA, potential cost savings were recalculated. The outcomes are expressed in dollars saved annually. RESULTS: There are 616,000 new ischemic stroke patients annually. A 600 dollars net cost savings is associated with each tPA-treated patient. Currently, an estimated 2% of all ischemic stroke patients receive tPA. If the proportion was increased to 4, 6, 8, 10, 15, or 20%, the realized cost savings would be approximately 15, 22, 30, 37, 55, and 74 million dollars, respectively. CONCLUSIONS: If even small manageable increases in the proportion of all ischemic stroke patients who received tPA were achieved, it would result in an enormous realized savings for America's healthcare system.
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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 | 0.000 | 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".