Service pathway personalization in digital health services.
Thesis event information
Date and time of the thesis defence
Place of the thesis defence
L6, https://oulu.zoom.us/j/69265102966?pwd=dmw1U2FUZUV2ZGtQaWZLVlEvQlluUT09
Topic of the dissertation
Service pathway personalization in digital health services.
Doctoral candidate
Master of science Olli Korhonen
Faculty and unit
University of Oulu Graduate School, Faculty of Information Technology and Electrical Engineering, Empirical Software Engineering in Software, Systems and Services (M3S)
Subject of study
Information processing science
Opponent
Professor Jonna Häkkilä, University of Lapland
Custos
Professor Minna Isomursu, University of Oulu
Service pathway personalization in digital health services
As the main result, this thesis proposes personalization filters that represent the role of IT in the personalization of digital health service pathways. The personalization filters are as follows:
(1) the contextual filter, where the role of IT is to consider the healthcare-specific parameters for personalization
(2) the data-driven filter, where the role of IT is to consider the aggregated data parameters for personalization
(3) the user-specific filter, where the role of IT is to consider the characteristics and preferences of the healthcare user as parameters for personalization.
In these personalization filters, IT plays a role that varies from fully automated personalization to a more collaborative form of data-driven decision making to make digital health service pathways more personalized for the individual healthcare user. In IS, various personalization approaches are used to design and implement personalization in technologies and to classify personalization through technologies. Still, personalization studies rarely consider personalization and the role of IT more holistically at the level of digital services.
The present work applies a service pathway concept as it provides the means by which to consider all the available health services to be included for the individual healthcare user in the context of digital health services. The present work investigates the phenomenon through a multiple-case study approach. The data collected are thematically analyzed to provide understanding on the role IT can play in the personalization of digital health service pathways. The work undertaken in this thesis contributes to research and practice by proposing personalization filters that can collectively represent the roles IT can play in the personalization of digital health service pathways.
(1) the contextual filter, where the role of IT is to consider the healthcare-specific parameters for personalization
(2) the data-driven filter, where the role of IT is to consider the aggregated data parameters for personalization
(3) the user-specific filter, where the role of IT is to consider the characteristics and preferences of the healthcare user as parameters for personalization.
In these personalization filters, IT plays a role that varies from fully automated personalization to a more collaborative form of data-driven decision making to make digital health service pathways more personalized for the individual healthcare user. In IS, various personalization approaches are used to design and implement personalization in technologies and to classify personalization through technologies. Still, personalization studies rarely consider personalization and the role of IT more holistically at the level of digital services.
The present work applies a service pathway concept as it provides the means by which to consider all the available health services to be included for the individual healthcare user in the context of digital health services. The present work investigates the phenomenon through a multiple-case study approach. The data collected are thematically analyzed to provide understanding on the role IT can play in the personalization of digital health service pathways. The work undertaken in this thesis contributes to research and practice by proposing personalization filters that can collectively represent the roles IT can play in the personalization of digital health service pathways.
Last updated: 1.3.2023