Human-Data Interaction in Healthcare

Human-Data Interaction in Healthcare

Federico Cabitza (Università degli Studi di Milano-Bicocca, Italy) and Angela Locoro (Università degli Studi di Milano-Bicocca, Italy)
DOI: 10.4018/978-1-7998-1204-3.ch058

Abstract

In this chapter, we focus on an emerging strand of IT-oriented research, namely Human-Data Interaction (HDI) and on how this can be applied to healthcare. HDI regards both how humans create and use data by means of interactive systems, which can both assist and constrain them and the operational level of data work, which is both work on data and by data. Healthcare is a challenging arena where to test the potential of HDI towards a new, user-centered perspective on how to support and assess “data work”. This is especially true in current times where data are becoming increasingly big and many tools are available for the lay people, including doctors and nurses, to interact with health-related data. This chapter is a contribution in the direction of considering health-related data through the lens of HDI, and of framing data visualization tools in this strand of research. The intended aim is to let the subtler peculiarities among different kind of data and of their use emerge and be addressed adequately. Our point is that doing so can promote the design of more usable tools that can support data work from a user-centered and data quality perspective and the evidence-based validation of these tools.
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Background

As rightly noted by Hornung et al. (2015), the expression HDI is neither specific nor new. On the one hand, humans have always interacted with data, that is they have inscribed, read and communicated data in terms of simple marks, more complex symbols and any kind of meaningful signs1. On the other hand, this interaction has predominantly been mono-directional until interactive systems have allowed users to get access to data according to their peculiar and situated needs. In the computing literature, the expression has been used since the 1990s, e.g., by Kennedy et al. (1996), to address the needs of the users in the context of data intensive settings and hence “the problem of delivering personalized, context-aware, and understandable data from big datasets” (Cafaro, 2012). More recently a number of authors have tried to define Human-Data Interaction, by focusing on different aspects: Elmqvist (2011) and Cafaro (2012) focused on the material and embodied aspects of interaction; Crabtree and Mortier (2015) prefer to assimilate HDI to “the management and use of personal data in society at large” where personal here means that data are either “about individuals” or are delivered in terms of “personalized experiences”. In particular, Elmqvist (2011) defines HDI as “the human manipulation, analysis, and sense making of large, unstructured, and complex datasets” and Cafaro sees HDI systems “as technologies that use embodied interaction to facilitate the users' exploration of rich datasets”. We agree with Hornung et al. (2015) and Crabtree and Mortier (2014) in regard to the fact that “HDI does not only refer to embodied interaction, but to all kinds of interaction” and that “HDI should investigate ‘data that affects people’ ”.

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