Abstract
One of the effects of population ageing is the increase in the proportion of long-term chronic diseases, which require new therapeutical models that mostly take place at the patients’ home rather than inside a health care institution. This requires that patients autonomously follow their prescribed treatment, which can be especially difficult for patients suffering some kind of cognitive impairment. Information technologies show potential for supporting medication adherence but the main challenge is the distributed and highly regulated nature of this scenario, where there are several tasks involving the coordinated action of a range of actors. In this paper we propose to use socially intelligent systems to tackle this challenge. These systems exhibit, understand, and reason about social behaviour, in order to support people in their daily lives. Such systems present an opportunity when applied to information technologies for supporting treatment adherence. We explore how concepts of socially intelligent systems, including social practices and social identities, can be applied to AVICENA, an ongoing project to create a platform for assisting patients in several daily tasks related to their healthcare. We first introduce AVICENA, briefly describe our previous attempts to model the system from an organizational perspective and an institutional one and discuss some of the limitations found in those models. Then the core concepts of socially intelligent systems are introduced and we show how they can be applied to create a socially aware framework for supporting medication adherence.
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Acknowledgments
Ignasi Gómez-Sebastia’s work has been partially funded by the Torres Quevedo program of the Spanish Ministry of economy and competitiveness.
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Gómez-Sebastià, I., Dignum, F., Vázquez-Salceda, J., Cortés, U. (2017). Modelling Patient-Centric Healthcare Using Socially Intelligent Systems: The AVICENA Experience. In: Cranefield, S., Mahmoud, S., Padget, J., Rocha, A. (eds) Coordination, Organizations, Institutions, and Norms in Agent Systems XII. COIN COIN 2016 2016. Lecture Notes in Computer Science(), vol 10315. Springer, Cham. https://doi.org/10.1007/978-3-319-66595-5_2
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