Insurer Coverage of Invasive Coronary Angiography and Percutaneous Coronary Intervention for Stable Coronary Artery Disease in the United States Compared With Guidelines and Landmark Trials
Bibliographic record
Abstract
BACKGROUND: Invasive coronary angiography (ICA) and percutaneous coronary intervention (PCI) are common procedures for the diagnosis and treatment of coronary artery disease (CAD). These procedures are typically performed within the parameters of insurance coverage, but little is known about how insurance policies align with guidelines and landmark randomized clinical trials. METHODS: We developed 6 use cases (3 each for ICA and PCI) of clinical scenarios for stable CAD commonly encountered in clinical practice and compared policies of the largest US public and private payers (based on total revenue and number of beneficiaries) to the 2012 and 2023 professional society guidelines as well as the ORBITA (Objective Randomized Blinded Investigation With Optimal Medical Therapy of Angioplasty in Stable Angina) and ISCHEMIA (Initial Invasive or Conservative Strategy for Stable Coronary Disease) trials. We classified policies as more restrictive, equal, or less restrictive than the guidelines and published randomized clinical trials by evaluating them on parameters of optimal medical therapy (OMT) and noninvasive imaging for ICA policies; and OMT, anatomic severity of CAD, and ability to proceed with PCI for PCI policies. We summarized findings with descriptive statistics. RESULTS: Among 33 payers, 18 (55%) ICA and 14 (42%) PCI policies were publicly available. When comparing requirements for OMT among symptomatic patients before ICA, 22% of policies were less restrictive, 75% were equivalent, and 3% were more restrictive than the 2012 and 2023 professional society guidelines. For the number of OMT medications among symptomatic patients before ICA, 44% were less restrictive and 56% were equivalent compared with the ORBITA trial. When comparing requirements for OMT for symptomatic patients before PCI, 21% of policies were less restrictive, 75% were equivalent, and 4% were more restrictive than the 2012 and 2023 guidelines. CONCLUSIONS: ICA and PCI coverage policies were only publicly available for approximately half of the largest US insurers, indicating need for greater transparency. When available, policies were variable in their alignment with clinical practice guidelines.
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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 | 0.024 | 0.094 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".