Abstract P345: The Cost-Effectiveness of Home BP Telemonitoring in Patients With a Cerebrovascular Event
Bibliographic record
Abstract
Background: Home BP telemonitoring, with pharmacist case management, leads to clinically important BP reductions. Our objective was to determine the incremental cost-effectiveness of this intervention compared with usual care BP control in patients with cerebrovascular disease in Alberta, Canada. Methods: A cost-utility analysis using a Markov decision model was created, examining a cohort of high-risk patients with a recent cerebrovascular event residing in their own residence. A lifetime time horizon and health care payer perspective was used. Achieved BP and risk of future cardiovascular events (recurrent stroke, myocardial infarction, unstable angina, or death) were modelled, with attendant consequences on quality adjusted life years and costs. BP telemonitoring was assumed to occur monthly until BP was controlled, then quarterly. Canadian life tables were used to determine overall mortality, adjusted by CVD mortality. Relative efficacy on intervention-associated BP lowering were obtained from published data. Reduction in BP of 9.7/5.1 mmHg at 12-months was used in the base case. Resource use and costs were obtained from Canadian published literature. Results: Telemonitoring with case management led to net health care savings of $2326, and an additional 0.83 QALYs (see Table). Results were robust in sensitivity analysis (see Table). Conclusion: Home BP telemonitoring and pharmacist case management was a dominant strategy, as it lowered costs and improved QALYs, and should be implemented.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".