Minimizing Long Form Data

Methods: Surveys, prototype testing, A/B testing, concept testing, unmoderated interviews

Responsible for end-to-end research to determine the best approach to minimizing the  length of online healthcare forms to benefit the end user.

Background:

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•Prototype A (Control) is a traditional long healthcare form that was considered a best practice when completing a competitive analysis

•Prototype B is a healthcare form with collapsed sections that expand when manually selecting the ‘yes’ and ‘no’ radio buttons

•Prototype C is a healthcare form divided into sections that can be navigated using ‘previous’ and ‘next’ buttons

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Objectives:

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Determine best approach for minimizing long form data.  

•Include accessibility acknowledgments before completing the survey to obtain feedback from participants with visual, mobile, and cognitive impairments

•Provide tasks to navigate each prototype using mock data, and obtain feedback on usability

•Obtain information for success rate, abandon rate, number of clicks, and time on task

•Determine which prototype participants prefer

•Include (conditional) follow-up questions to obtain feedback on the user experience for people with disabilities

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Participants:

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UserZoom sent each version of the study to 34 participants. A total of 102 participants were recruited for this study. Screener questions were used to capture the participant’s age, state of residence, comfortability with using online technology, and health insurance type Recruitment Includes:

•42 participants are currently enrolled in Medicare or Medicaid insurance plans

•Demographic representation for Fidelis, Wellcare, and Ambetter healthcare plans

•19 participants are 65+

•16 participants reside in NY

•19 participants are disabled, unable to work

•People with disabilities

•14 participants have low vision (e.g., blurry vision, glaucoma, light sensitivity, night blindness)

•3 participants are blind (i.e., substantial loss of vision in both eyes)

9 participants are currently using assistive devices such as screen readers, mouth stick, BigKeys, and joysticks