Engaging Patients, Empowering Doctors in Digitalization of Healthcare: Rich Data in Policy Decision-Making

Marika Iivari, Julius Gomes, Minna Pikkarainen, Juha Häikiö, Peter Ylén

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

1 Citation (Scopus)


This study explores how heterogeneous types of data, e.g., personal data, big data, public data, statistical data, third sector data as well as social media, jointly referred to as 'rich data', are currently being utilised in healthcare policy making, and what kind of implications data has on future decision-making. Conducted as a qualitative case study with municipal decision-makers in Finland, this study examines the use of data in the context of preventive mental healthcare services, and highlights mental issues as a complex, systemic kind with far reaching long term impact, where the needs ands requirements for right kinds of data extend beyond healthcare domain. Making rich data available for policy decisions is only one preliminary step in the road to data-driven policy decisions. Data analysis and visualisation are essential elements in making data usable for decision-makers in order to improve the health and wellbeing of the society.
Original languageEnglish
Title of host publicationProceedings of the ISPIM 2017
EditorsStanislav Klimenko, Zhisheng Huang, Hua Wang, Yanchun Zhang, Uwe Aickelin, Rui Zhou, Siuly Siuly
PublisherInternational Society for Professional Innovation Management ISPIM
Number of pages5
ISBN (Print)978-952-335-021-2
Publication statusPublished - 1 Jan 2017
MoE publication typeA4 Article in a conference publication
EventISPIM Innovation Conference 2017: Composing the Innovation Symphony - Vienna, Austria
Duration: 18 Jun 201721 Jun 2017

Publication series

SeriesLecture Notes in Computer Science
Volume10594 LNCS


ConferenceISPIM Innovation Conference 2017
Abbreviated titleISPIM


  • healthcare
  • data
  • big data
  • decision-making
  • policy making
  • public sector
  • data-driven
  • data-driven decision-making
  • mental health
  • patient health records (PHR)
  • medical data presentation
  • adherence to treatment
  • distant medical monitoring
  • intellectual algorithms

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