Improving usability benchmarking for the eHealth domain: The development of the eHealth UsaBility Benchmarking instrument (HUBBI)

PLoS One. 2022 Feb 17;17(2):e0262036. doi: 10.1371/journal.pone.0262036. eCollection 2022.

Abstract

Background: Currently, most usability benchmarking tools used within the eHealth domain are based on re-classifications of old usability frameworks or generic usability surveys. This makes them outdated and not well suited for the eHealth domain. Recently, a new ontology of usability factors was developed for the eHealth domain. It consists of eight categories: Basic System Performance (BSP), Task-Technology Fit (TTF), Accessibility (ACC), Interface Design (ID), Navigation & Structure (NS), Information & Terminology (IT), Guidance & Support (GS) and Satisfaction (SAT).

Objective: The goal of this study is to develop a new usability benchmarking tool for eHealth, the eHealth UsaBility Benchmarking Instrument (HUBBI), that is based on a new ontology of usability factors for eHealth.

Methods: First, a large item pool was generated containing 66 items. Then, an online usability test was conducted, using the case study of a Dutch website for general health advice. Participants had to perform three tasks on the website, after which they completed the HUBBI. Using Partial Least Squares Structural Equation Modelling (PLS-SEM), we identified the items that assess each factor best and that, together, make up the HUBBI.

Results: A total of 148 persons participated. Our selection of items resulted in a shortened version of the HUBBI, containing 18 items. The category Accessibility is not included in the final version, due to the wide range of eHealth services and their heterogeneous populations. This creates a constantly different role of Accessibility, which is a problem for a uniform benchmarking tool.

Conclusions: The HUBBI is a new and comprehensive usability benchmarking tool for the eHealth domain. It assesses usability on seven domains (BSP, TTF, ID, NS, IT, GS, SAT) in which a score per domain is generated. This can help eHealth developers to quickly determine which areas of the eHealth system's usability need to be optimized.

MeSH terms

  • Benchmarking / methods*
  • Consumer Health Informatics / statistics & numerical data*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Search Engine*
  • Surveys and Questionnaires
  • Telemedicine / instrumentation*
  • Telemedicine / methods
  • Telemedicine / statistics & numerical data*
  • User-Computer Interface*

Grants and funding

The author(s) received no specific funding for this work.