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Hilton Atlanta, 301
Health Economics Research Organization
Economics of the Pharmaceutical Industry: Current Issues
Saturday, Jan. 5, 2019 10:15 AM - 12:15 PM
- Chair: Robert Kaestner, University of Chicago
A Dose of Managed Care: Controlling Drug Spending in Medicaid
AbstractWe study the effect of privatizing Medicaid benefits on drug prices and utilization. Drug spending would fall by 22.4 percent if the drug benefit was fully administered by private insurers. One-third of the decrease is driven by private insurers' ability to negotiate lower point-of-sale prices with pharmacies. The remaining two-thirds are driven by the greater use of lower cost drugs, such as generics, and are only realized in states that give private insurers the flexibility to design prescription drug benefits. Privatization does not decrease prescriptions per enrollee and spending cuts are smaller for drugs that lower medical spending.
Delegating Decision-Making to the Machine: Experimental Evidence from Health Insurance
AbstractWith the proliferation of on-line shopping tools and the advancement of predictive algorithms, personalized decision-making support software for consumers - especially in markets for household finances - is becoming commonplace. Does delegating consumer decisions to algorithms affect consumer choices and market efficiency? We present the results of a randomized controlled trial in which we offered (elderly) consumers a decision-making support software for choosing among pharmaceutical insurance plans. We find that algorithmic “expert” recommendation significantly alters consumer choices (plan switching rate increases by 8pp relative to 28% baseline rate). At the same time, personalized, but passive, informational treatment has little effect on switching. We find that selection into who uses the support tool is quantitatively large. Consumers that are more likely to switch their insurance plans are much more likely to take up our intervention. We find similar patterns for other measures of choice behavior. We use a discrete choice model of consumer decision-making to analyze the mechanisms that underlie the aggregate treatment effects and to estimate how the algorithmic decision-making support affects consumer welfare.
University of Illinois Urbana-Champaign
University of Southern California
- I1 - Health
- I1 - Health