The 2010 AcademyHealth Annual Research Meeting will be held a few miles from my office. So, I’ll be there, as will my colleague and co-blogger Steve Pizer. Will you?
The only place and time I know I’ll be in advance is in front of my poster at 8AM on Monday, June 28. The poster session (B) runs until 9:30AM, but I tend to wander from my poster. So if you want to be sure to find me, get there early. The title of my poster is “The Effects of Medicare Payment Reductions on Private Plan Entry.” Here’s an abstract:
Insurance firms participating in Medicare can offer up to three principal plan types: coordinated care plans (CCPs), prescription drug plans (PDPs), and private fee for service (PFFS) plans. Firms can make entry and marketing decisions separately across plan types and geographic regions. Our firm-level model separately identifies CCP, PDP, and PFFS entry, allowing for correlated residuals. We find evidence of cross-product competition and common cost or demand factors that make entry with certain product combinations more likely. We predict that market presence of CCPs and PFFS plans will decrease and that of PDPs will increase in response to payment reductions.
If you’ve been following my blogging on instrumental variables techniques (or even if you haven’t) and want to learn more about them, I recommend the workshop Steve is co-leading titled “Addressing Selection Bias in Observational Studies.” It’s being held on Tuesday, June 29 from 9:45-11:15AM in room 302. Here’s the description:
Health services research frequently involves the evaluation of interventions in observational studies in which covariates are not balanced between treatment and control groups due to self-selection, which complicates the identification of unbiased associations or treatment effects. In this session, the audience will be presented with an overview of: conceptual issues of how causation is attributed in observational studies and how selection bias can arise, propensity score methods (with examples) to address imbalance in observed covariates, and selection/instrumental variables (IV) methods to address imbalance in unobserved covariates. The intended audience for this workshop is researchers familiar with quantitative methods who are interested in applying more advanced methods for addressing selection bias in observational studies. Level of Difficulty: Introductory.
Enjoy the conference!