Expectations to data: Perspectives of service providers and users of future health and wellness services

Juha Häikiö* (Corresponding Author), Sari Yli-Kauhaluoma, Minna Pikkarainen, Marika Iivari, Timo Koivumäki

*Corresponding author for this work

    Research output: Contribution to journalArticleScientificpeer-review

    6 Citations (Scopus)
    41 Downloads (Pure)

    Abstract

    The healthcare and wellness sector currently attempts to provide more proactive service models with data-driven solutions. This study examines the expectations and values related to personal data i.e. data valences from the perspective of service providers and individual users. The study is based on the analysis of extensive empirical material collected through interviews and a collaborative workshop. The data was collected in one cultural context, Finland. The results suggest that the potential service providers and users have similar expectations regarding self-evidence of data while the main differences concern the expectations of transparency. The results of the study propose some basic requirements for the development of personalised data-driven services in future. The study suggests that basic requirements for the development of future data driven services concern expectations to usable data visualisations, data as a motivator, data accuracy and data transparency. Even though there are varying expectations to personal health data and even some concerns, it can be seen that here different ecosystem actors primarily perceived the wider use of personal health and wellness data as a positive trend. It can be concluded that collaborative personal data-driven service ecosystems are an integral part of development towards proactive service models in healthcare.

    Original languageEnglish
    Pages (from-to)621-636
    Number of pages16
    JournalHealth and Technology
    Volume10
    DOIs
    Publication statusPublished - 1 May 2020
    MoE publication typeA1 Journal article-refereed

    Keywords

    • Data expectations
    • Data valence
    • Health data
    • Personal data
    • Wellness data

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