David L Carl

ORCID: 0000-0003-0615-0133
Publications
Citations
Views
---
Saved
---
About
Contact & Profiles
Research Areas
  • Health Systems, Economic Evaluations, Quality of Life
  • Pharmaceutical Economics and Policy
  • Bayesian Modeling and Causal Inference
  • Statistical Methods and Bayesian Inference
  • Statistical Methods and Inference
  • Economic and Financial Impacts of Cancer
  • Pharmaceutical studies and practices
  • Biosimilars and Bioanalytical Methods

University of Zurich
2021-2022

Importance Biologics account for a substantial proportion of health care expenditures. Their costs have been projected to reach US $452 billion in global spending by 2022. Given recent expiration patent protection biologics, shift toward greater follow-on competition among biosimilars would be expected that allow uptake and lower drug costs. Objective To assess prices the compared with 2 European countries (Germany Switzerland) national mechanisms price negotiation. Design, Setting,...

10.1001/jamanetworkopen.2022.44670 article EN cc-by-nc-nd JAMA Network Open 2022-12-02

Many European countries introduced (confidential) rebates in the past years. Authorities and manufacturers argue that this strategy allows reduction of spending on high-cost drugs, quick access innovative drugs. We evaluated these arguments using Switzerland as an example, one last with transparent rebates. identified all drugs granted new without between January 2012 October 2020. assessed amount over time, clinical benefit rebates, duration approval price determination. Our study cohort...

10.1016/j.lanepe.2021.100050 article EN cc-by-nc-nd The Lancet Regional Health - Europe 2021-03-02

TSCI implements treatment effect estimation from observational data under invalid instruments in the R statistical computing environment. Existing instrumental variable approaches rely on arguably strong and untestable identification assumptions, which limits their practical application. does not require classical conditions is effective even if all are invalid. a two-stage algorithm. In first stage, machine learning used to cope with nonlinearities interactions model. second space capture...

10.48550/arxiv.2304.00513 preprint EN other-oa arXiv (Cornell University) 2023-01-01
Coming Soon ...