Plan selection in Medicare Part D: Evidence from administrative data
Daniel McFadden and
Joachim Winter ()
Munich Reprints in Economics from University of Munich, Department of Economics
We study the Medicare Part D prescription drug insurance program as a bellwether for designs of private, non-mandatory health insurance markets, focusing on the ability of consumers to evaluate and optimize their choices of plans. Our analysis of administrative data on medical claims in Medicare Part D suggests that fewer than 25\% of individuals enroll in plans that are ex ante as good as the least cost plan specified by the Plan Finder tool made available to seniors by the Medicare administration, and that consumers on average have expected excess spending of about 300 per year, or about 15\% of expected total out-of-pocket cost for drugs and Part D insurance. These numbers are hard to reconcile with decision costs alone; it appears that unless a sizeable fraction of consumers place large values on plan features other than cost, they are not optimizing effectively.
References: Add references at CitEc
Citations View citations in EconPapers (27) Track citations by RSS feed
Published in Journal of Health Economics 6 32(2013): pp. 1325-1344
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Journal Article: Plan selection in Medicare Part D: Evidence from administrative data (2013)
Working Paper: Plan Selection in Medicare Part D: Evidence from Administrative Data (2012)
Working Paper: Plan Selection in Medicare Part D: Evidence from administrative Data (2012)
Working Paper: Plan selection in Medicare Part D: Evidence from administrative data (2012)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:lmu:muenar:19428
Access Statistics for this paper
More papers in Munich Reprints in Economics from University of Munich, Department of Economics Ludwigstr. 28, 80539 Munich, Germany. Contact information at EDIRC.
Series data maintained by Tamilla Benkelberg ().