dc.contributor.advisor | Nytrø, Øystein | |
dc.contributor.advisor | Grimsmo, Anders | |
dc.contributor.advisor | Nordgård, Torbjørn | |
dc.contributor.author | Røst, Thomas Brox | |
dc.date.accessioned | 2023-12-04T15:48:56Z | |
dc.date.available | 2023-12-04T15:48:56Z | |
dc.date.issued | 2023 | |
dc.identifier.isbn | 978-82-326-7599-9 | |
dc.identifier.issn | 2703-8084 | |
dc.identifier.uri | https://hdl.handle.net/11250/3105882 | |
dc.description.abstract | Healthcare professionals make decisions every day. These decisions can have a profound impact on those they concern, such as a decision on how to treat a patient. Patients and their families can experience prolonged illness or death if the decision results in an adverse event; the treating healthcare organization and society as a whole will suffer the additional clinical, economic and social impact. Getting decisions right is important for safe provisioning of healthcare.
This thesis discusses ways of helping healthcare professionals make better decisions through targeted use of healthcare data and knowledge. We specifically consider these three research questions:
RQ1 How can health-related data and knowledge aid decision-making?
RQ2 How can healthcare professionals contribute to implementation of datadriven decision-making?
RQ3 How can patient trajectory data contribute to decision-making in healthcare?
The five included publications cover various aspects of data- and knowledgedriven decision-making in the healthcare domain. The application scope ranges from decision support in the electronic health record to automated clinical knowledge classification. Results from the publications are discussed in light of the research questions. Finally, we consider how recent machine learning advances may affect decision support in healthcare, both in terms of possibilities and obstacles. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | NTNU | en_US |
dc.relation.ispartofseries | Doctoral theses at NTNU;2023:448 | |
dc.relation.haspart | Paper 1: Røst, Thomas Brox; Sørby, Inger Dybdahl; Seland, Gry. Development of a Medication Reconciliation Tool for Norwegian Primary Care EPR Systems: Experiences from a User-initiated Project. Practical Aspects of Health Informatics; 2014-05-19 - 2014-05-20. Copyright © 2014 for the individual papers by the papers' authors. | en_US |
dc.relation.haspart | Paper 2: Røst, Thomas Brox; Tvedt, Christine Raaen; Husby, Haldor; Berg, Ingrid Andås; Nytrø, Øystein. Identifying catheter-related events through sentence classification. International Journal of Data Mining and Bioinformatics 2020 ;Volum 23.(3) s. 213-233. © 2023 Inderscience Enterprises Ltd. Available at: http://dx.doi.org/10.1504/IJDMB.2020.107877 | en_US |
dc.relation.haspart | Paper 3: Røst, Thomas Brox; Slaughter, Laura; Nytrø, Øystein; Muller, Ashley Elizabeth; Vist, Gunn Elisabeth. Using neural networks to support high-quality evidence mapping. BMC Bioinformatics 2021 ;Volum 22. Suppl. 11 s. - Open Access This article is licensed under a Creative Commons Attribution 4.0 International License CC BY. Available at: http://dx.doi.org/10.1186/s12859-021-04396-x | en_US |
dc.relation.haspart | Paper 4: Røst, Thomas Brox; Clausen, Carolyn; Nytrø, Øystein; Koposov, Roman A; Leventhal, Bennett; Westbye, Odd Sverre; Bakken, Victoria; Knudsen, Linda Helen; Koochakpour, Kaban; Skokauskas, Norbert. Local, Early, and Precise: Designing a Clinical Decision Support System for Child and Adolescent Mental Health Services. Frontiers in Psychiatry 2020 ;Volum 11. s. - This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). Available at: http://dx.doi.org/10.3389/fpsyt.2020.564205 | en_US |
dc.relation.haspart | Paper 5: Clausen, Carolyn Elizabeth; Leventhal, Bennett; Nytrø, Øystein; Koposov, Roman A; Røst, Thomas Brox; Westbye, Odd Sverre; Koochakpour, Kaban; Frodl, Thomas; Stien, Ulrika Line; Skokauskas, Norbert. Usability of the IDDEAS prototype in child and adolescent mental health services: A qualitative study for clinical decision support system development. Frontiers in Psychiatry 2023 ;Volum 14. s. - This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). Available at: http://dx.doi.org/10.3389/fpsyt.2023.1033724 | en_US |
dc.title | Enabling data-driven decision support in healthcare | en_US |
dc.type | Doctoral thesis | en_US |
dc.subject.nsi | VDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550 | en_US |