Usability Evaluation of a Co-created Big Data Analytics Platform for Health Policy-Making

Egileak: Brian Cleland Jonathan Wallace Raymond Bond Salla Muuraiskangas Juha Pajula Gorka Epelde Unanue Mónica Arrúe Roberto Álvarez Sánchez Mihaela Black Maurice D Mulvenna Deborah Rankin Paul Carlin

Data: 26.07.2019


Abstract

The increasingly important role of big data in organisational decision-making brings with it significant challenges in terms of designing usable software interfaces. Specifically, such interfaces must allow users to explore, analyse, and visualise complex data from heterogeneous sources and derive insights to support management decisions. This paper describes a usability evaluation of the MIDAS Project, a big data platform for health policy-making, developed by an EU-funded Horizon 2020 project involving a number of international partners and pilot sites. We describe how a combination of heuristic and formative user-centred evaluation methods were employed, and give a summary of the key findings. We discuss key insights from the evaluation, including the importance of having diverse users, the role played by users  prior expectations, and the logistical challenge of coordinating user testing across multiple sites. Finally, we explore the relative value of each of the evaluation methods, and outline how our approach to usability testing will evolve for future iterations of the MIDAS platform.

BIB_text

@Article {
title = {Usability Evaluation of a Co-created Big Data Analytics Platform for Health Policy-Making},
pages = {194-207},
keywds = {
Big data, Health, Usability Evaluation, Policy-making, User-centred
}
abstract = {

The increasingly important role of big data in organisational decision-making brings with it significant challenges in terms of designing usable software interfaces. Specifically, such interfaces must allow users to explore, analyse, and visualise complex data from heterogeneous sources and derive insights to support management decisions. This paper describes a usability evaluation of the MIDAS Project, a big data platform for health policy-making, developed by an EU-funded Horizon 2020 project involving a number of international partners and pilot sites. We describe how a combination of heuristic and formative user-centred evaluation methods were employed, and give a summary of the key findings. We discuss key insights from the evaluation, including the importance of having diverse users, the role played by users  prior expectations, and the logistical challenge of coordinating user testing across multiple sites. Finally, we explore the relative value of each of the evaluation methods, and outline how our approach to usability testing will evolve for future iterations of the MIDAS platform.


}
isbn = {978-3-030-22660-2},
date = {2019-07-26},
}
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