Can Plan Recommendations Improve the Coverage Decisions of Vulnerable Populations in Health Insurance Marketplaces?

Abstract

OBJECTIVE: The Affordable Care Act's marketplaces present an important opportunity for expanding coverage but consumers face enormous challenges in navigating through enrollment and re-enrollment. We tested the effectiveness of a behaviorally informed policy tool--plan recommendations--in improving marketplace decisions. STUDY SETTING: Data were gathered from a community sample of 656 lower-income, minority, rural residents of Virginia. STUDY DESIGN: We conducted an incentive-compatible, computer-based experiment using a hypothetical marketplace like the one consumers face in the federally-facilitated marketplaces, and examined their decision quality. Participants were randomly assigned to a control condition or three types of plan recommendations: social normative, physician, and government. For participants randomized to a plan recommendation condition, the plan that maximized expected earnings, and minimized total expected annual health care costs, was recommended. DATA COLLECTION: Primary data were gathered using an online choice experiment and questionnaire. PRINCIPAL FINDINGS: Plan recommendations resulted in a 21 percentage point increase in the probability of choosing the earnings maximizing plan, after controlling for participant characteristics. Two conditions, government or providers recommending the lowest cost plan, resulted in plan choices that lowered annual costs compared to marketplaces where no recommendations were made. CONCLUSIONS: As millions of adults grapple with choosing plans in marketplaces and whether to switch plans during open enrollment, it is time to consider marketplace redesigns and leverage insights from the behavioral sciences to facilitate consumers' decisions.