A Description of Canadian and United States Physician Reimbursement for Thrombolytic Therapy Administration in Acute Ischemic Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Acute ischemic stroke patients are infrequently treated with rtPA, despite its proven effectiveness. Poor physician reimbursement for acute stroke care is one possible explanation for the low frequency of use. We describe the physician reimbursement for thrombolytic therapy for the stroke team physicians serving the Greater Cincinnati/Northern Kentucky region (GCNK), and the Alberta region. METHODS: GCNK: billing logs were accessed for the study period of 7/01-12/02, and cross-matched to stroke call logs. University of Calgary (UC): treatment records of a single physician were reviewed from 4/02-3/04. A telephone survey of Canadian provinces was conducted regarding billing practices. RESULTS: GCNK: During the study period, 151 patients received rtPA. For treated pts. the average time spent was 2.6 hours, and average reimbursement received was 472 dollars (of those with insurance). The highest reimbursement was received by billing critical care codes. Reimbursement for critical care was similar to or lower than common office procedures for neurologists. UC: during the study period, 131 patients received rtPA. Average reimbursement for rtPA treated patients was 340 dollars US, not including on-call payments. Survey across Canada revealed many provinces with weekend/after hour premium stipends and on-call stipends. CONCLUSIONS: Physician reimbursement for the evaluation and treatment of acute stroke, when compared with other diagnoses commonly treated by neurologists, is relatively low in both the U.S. and Canada. Health policy decision-makers in the US and Canada should be made aware of the importance of providing a more balanced plan to provide medical care to stroke patients.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.009 | 0.017 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".