Health economic consequences of optimal vs. observed guideline adherence of coronary angiography in patients with suspected obstructive stable coronary artery in Germany: a microsimulation model
Bibliographic record
Abstract
AIMS: While the number of patients with stable coronary artery disease (SCAD) is similar across European countries, Germany has the highest per capita volume of coronary angiographies (CA). This study evaluated the health economic consequences of guideline-non-adherent use of CA in patients with SCAD. METHODS AND RESULTS: As part of the ENLIGHT-KHK trial, a prospective observational study, this microsimulation model compared the number of major adverse cardiac events (MACE) and the costs of real-world use of CA with those of (assumed) complete guideline-adherent use (according to the German National Disease Management Guideline 2019). The model considered non-invasive testing, CA, revascularization, MACE (30 days after CA), and medical costs. Model inputs were obtained from the ENLIGHT-KHK trial (i.e. patients' records, a patient questionnaire, and claims data). Incremental cost-effectiveness ratios were calculated by comparing the differences in costs and MACE avoided from the perspective of the Statutory Health Insurance (SHI). Independent on pre-test probability (PTP) of SCAD, complete guideline adherence for usage of CA would result in a slightly lower rate of MACE (-0.0017) and less cost (€-807) per person compared with real-world guideline adherence. While cost savings were shown for moderate and low PTP (€901 and €502, respectively), for a high PTP, a guideline-adherent process results in slightly higher costs (€78) compared with real-world guideline adherence. Sensitivity analyses confirmed the results. CONCLUSION: Our analysis indicates that improving guideline adherence in clinical practice by reducing the amount of CAs in patients with SCAD would lead to cost savings for the German SHI.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".