Return on Investment in Endovascular Care: The Case of Endovascular Reperfusion Alberta
Bibliographic record
Abstract
OBJECTIVE: We examined the return on investment (ROI) from the Endovascular Reperfusion Alberta (ERA) project, a provincially funded population-wide strategy to improve access to endovascular therapy (EVT), to inform policy regarding sustainability. METHODS: We calculated net benefit (NB) as benefit minus cost and ROI as benefit divided by cost. Patients treated with EVT and their controls were identified from the ESCAPE trial. Using the provincial administrative databases, their health services utilization (HSU), including inpatient, outpatient, physician, long-term care services, and prescription drugs, were compared. This benefit was then extrapolated to the number of patients receiving EVT increased in 2018 and 2019 by the ERA implementation. We used three time horizons, including short (90 days), medium (1 year), and long-term (5 years). RESULTS: EVT was associated with a reduced gross HSU cost for all the three time horizons. Given the total costs of ERA were $2.04 million in 2018 ($11,860/patient) and $3.73 million in 2019 ($17,070/patient), NB per patient in 2018 (2019) was estimated at -$7,313 (-$12,524), $54,592 ($49,381), and $47,070 ($41,859) for short, medium, and long-term time horizons, respectively. Total NB for the province in 2018 (2019) were -$1.26 (-$2.74), $9.40 ($10.78), and $8.11 ($9.14) million; ROI ratios were 0.4 (0.3), 5.6 (3.9) and 5.0 (3.5). Probabilities of ERA being cost saving were 39% (31%), 97% (96%), and 94% (91%), for short, medium, and long-term time horizons, respectively. CONCLUSION: The ERA program was cost saving in the medium and long-term time horizons. Results emphasized the importance of considering a broad range of HSU and long-term impact to capture the full ROI.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| 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".