Picwell was founded by some of the leading academics in health economics, with the idea that advanced decision support could radically simplify the process of purchasing health insurance, thereby unlocking value for insurers, brokers and consumers alike.
Picwell maintains this commitment to objectivity and innovation through our continuous research into new areas of decision support.
Consumer confusion in health insurance is rampant. In the absence of true decision support, members often shop by price alone leading to a variety of challenges for carriers. Picwell changes that by helping your members select the health insurance products that best fit their needs and values. See how Picwell’s technology platform drives value for carriers.
Jonathan Kolstad, University of California, Berkeley
Traditional models of insurance choice are predicated on fully informed and rational consumers protecting themselves from exposure to financial risk. In practice, choosing an insurance plan is a complicated decision often made without full information. In this paper we combine new administrative data on health plan choices and claims with unique survey data on consumer information to identify risk preferences, information frictions, and hassle costs. Our additional friction measures are important predictors of choices and meaningfully impact risk preference estimates. We study the implications of counterfactual insurance allocations to illustrate the importance of distinguishing between these micro-foundations for welfare analysis.
In this paper we focus on a specific element of the distinction between public and private exchanges: the ability of private exchanges to run large-scale experiments and use the findings to target messaging to consumers. The ability of private firms to learn about consumer behavior—either on average or across the population—or target messaging may impact both rates of insurance take-up and welfare.
What Does a Deductible Do? The Impact of Cost-Sharing on Health Care Prices, Quantities, and Spending Dynamics
Measuring consumer responsiveness to medical care prices is a central issue in health economics and a key ingredient in the optimal design and regulation of health insurance markets. We study consumer responsiveness to medical care prices, leveraging a natural experiment that occurred at a large self-insured firm which required all of its employees to switch from an insurance plan that provided free healthcare to a non-linear, high deductible plan. The switch caused a spending reduction between 11.79%-13.80% of total firm-wide health spending.
Young adults found the process of selecting a health insurance plan on the exchange HealthCare.gov website challenging. Young adults’ perspective on health insurance can inform strategies to design plans and communication about these plans in a way that engages and meets the needs of young adult populations.
We develop a model of selection that incorporates a key element of recent health reforms: an individual mandate. Using data from Massachusetts, we estimate the parameters of the model. In the individual market for health insurance, we find that premiums and average costs decreased significantly in response to the individual mandate. We find an annual welfare gain of 4.1 percent per person or $51.1 million annually in Massachusetts as a result of the reduction in adverse selection. We also find smaller post-reform markups.
We report results from two surveys of representative samples of Americans with private health insurance. The first examines how well Americans understand, and believe they understand, traditional health insurance coverage. The second examines whether those insured under a simplified all-copay insurance plan will be more likely to engage in cost-reducing behaviors relative to those insured under a traditional plan with deductibles and coinsurance, and measures consumer preferences between the two plans. The surveys provide strong evidence that consumers do not understand traditional plans and would better understand a simplified plan, but weaker evidence that a simplified plan would have strong appeal to consumers or change their healthcare choices.
Tom Baker, University of Pennsylvania
The Tens of millions of people are currently choosing health coverage on a state or federal health insurance exchange as part of the Patient Protection and Affordable Care Act. We examine how well people make these choices, how well they think they do, and what can be done to improve these choices. We conducted 6 experiments asking people to choose the most cost effective policy using websites modeled on current exchanges. Our results suggest there is significant room for improvement. Without interventions, respondents perform at near chance levels and show a significant bias, overweighting out-of-pocket expenses and deductibles. Financial incentives do not improve performance, and decision-makers do not realize that they are performing poorly. However, performance can be improved quite markedly by providing calculation aids, and by choosing a ‘‘smart’’ default. Implementing these psychologically based principles could save purchasers of policies and taxpayers approximately 10 billion dollars every year.
The design of the Affordable Care Act’s online health insurance Marketplaces can improve how consumers make complex health plan choices. We examined the choice environment on the state-based Marketplaces and HealthCare.gov in the third open enrollment period. Compared to previous enrollment periods, we found greater adoption of some decision support tools, such as total cost estimators and integrated provider lookups. Total cost estimators differed in how they generated estimates: In some Marketplaces, consumers categorized their own utilization, while in others, consumers answered detailed questions and were assigned a utilization profile. The tools available before creating an account (in the window-shopping period) and afterward (in the realshopping period) differed in several Marketplaces. For example, five Marketplaces provided total cost estimators to window shoppers, but only two provided them to real shoppers. Further research is needed on the impact of different choice environments and on which tools are most effective in helping consumers pick optimal plans.
What are the barriers to voluntary take-up of high-deductible plans? We address this question using a large-scale employer survey conducted after an open-enrollment period in which a new high-deductible plan was first introduced. Only 3% of the employees chose this plan, despite the respondents’ recognition of its financial advantages. Employees who believed that the high-deductible plan provided access to top physicians in the area were three times more likely to choose it than employees who did not share this belief. A framed field experiment using a similar choice menu showed that displaying additional financial information did not increase high deductible plan take-up. However, when plans were presented as identical except for the deductible, respondents were highly likely to choose the high-deductible plan, especially in a two-way choice. These results suggest that informing plan choosers about high-deductible plans’ health access provisions may affect choice more strongly than focusing on their financial advantages.
Robert Town, University of Texas at Austin
Standard Medicare Part D drug insurance provides limited coverage in a “doughnut hole” region, making the purchase problem dynamic. We develop a discontinuity-based test for myopia using enrollees who arrived near the coverage gap early in the year. We find that there are fewer and cheaper purchases immediately after reaching the gap, providing evidence in favor of myopia. We structurally estimate a dynamic drug purchase model and find complete myopia. For a nationally representative sample, “behavioral hazard” increases enrollee spending by 41%. Entirely eliminating the gap would increase insurer spending 31%, compared to 6% for generic-only gap coverage.
Learn more about Picwell’s technology stack and the team behind it on our technology blog: nerds.picwell.com