TL;DR
This paper introduces a nonparametric Bayesian instrumental variable method to evaluate how different coronary artery access strategies affect hospitalization costs, accounting for unobserved heterogeneity and demographic differences.
Contribution
It develops a hierarchical Bayesian latent index model with Dirichlet process mixtures for nonparametric error modeling, applied to real clinical registry data.
Findings
Wrist access reduces hospitalization charges compared to groin access.
Male patients experience higher cost reductions from wrist access.
The method effectively accounts for unmeasured heterogeneity in treatment effects.
Abstract
Percutaneous coronary interventions (PCIs) are nonsurgical procedures to open blocked blood vessels to the heart, frequently using a catheter to place a stent. The catheter can be inserted into the blood vessels using an artery in the groin or an artery in the wrist. Because clinical trials have indicated that access via the wrist may result in fewer post procedure complications, shortening the length of stay, and ultimately cost less than groin access, adoption of access via the wrist has been encouraged. However, patients treated in usual care are likely to differ from those participating in clinical trials, and there is reason to believe that the effectiveness of wrist access may differ between males and females. Moreover, the choice of artery access strategy is likely to be influenced by patient or physician unmeasured factors. To study the effectiveness of the two artery access…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
