Poor Consumer Comprehension and Plan Selection Inconsistencies Under the 2016 HealthCare.gov Choice Architecture.

Published

Journal Article

Background: Many health policy experts have endorsed insurance competition as a way to reduce the cost and improve the quality of medical care. In line with this approach, health insurance exchanges, such as HealthCare.gov, allow consumers to compare insurance plans online. Since the 2013 rollout of HealthCare.gov, administrators have added features intended to help consumers better understand and compare insurance plans. Although well-intentioned, changes to exchange websites affect the context in which consumers view plans, or choice architecture, which may impede their ability to choose plans that best fit their needs at the lowest cost. Methods: By simulating the 2016 HealthCare.gov enrollment experience in an online sample of 374 American adults, we examined comprehension and choice of HealthCare.gov plans under its choice architecture. Results: We found room for improvement in plan comprehension, with higher rates of misunderstanding among participants with poor math skills (P < 0.05). We observed substantial variations in plan choice when identical plan sets were displayed in different orders (P < 0.001). However, regardless of order in which they viewed the plans, participants cited the same factors as most important to their choices (P > 0.9). Limitations: Participants were drawn from a general population sample. The study does not assess for all possible plan choice influencers, such as provider networks, brand recognition, or help from others. Conclusions: Our findings suggest two areas of improvement for exchanges: first, the remaining gap in consumer plan comprehension and second, the apparent influence of sorting order - and likely other choice architecture elements - on plan choice. Our findings inform strategies for exchange administrators to help consumers better understand and select plans that better fit their needs.

Full Text

Duke Authors

Cited Authors

  • Wang, AZ; Scherr, KA; Wong, CA; Ubel, PA

Published Date

  • January 2017

Published In

Volume / Issue

  • 2 / 1

PubMed ID

  • 29892710

Pubmed Central ID

  • 29892710

Electronic International Standard Serial Number (EISSN)

  • 2381-4683

Digital Object Identifier (DOI)

  • 10.1177/2381468317716441

Language

  • eng

Conference Location

  • United States