This study explores the conditions and practices for data-driven innovation in the Swedish healthcare sector. While innovation nowadays often is based on big amounts of data, the laws for handling data in healthcare are restrictive. However, we see that remarkable innovation is happening in Swedish healthcare anyway. Therefore, we decided to explore the legal situation and talk to different actors to examine how they deal with the circumstances and how they innovate. We related those findings to the literature on data-driven innovation, platforms, artificial intelligence and about the healthcare sector context. It turned out that legislation is only one of the barriers to innovation. In addition, organizational and structural factors play a big role, too. Furthermore, we point out the strategic responses and their usage of artificial intelligence. Our contributions are that we mapped the Swedish healthcare landscape with a focus on data-driven innovation and that we applied Huang’s et al. (2017) model of rapid platform scaling to this context. Moreover, we point out how the healthcare sector differs from commercial business and how that is reflected in the innovation practices. Finally, we show which barriers need to be removed in order to improve the conditions for data-driven innovation.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:umu-197439 |
| Date | January 2022 |
| Creators | Shenouda, Ramy, Herz, Stefan |
| Publisher | Umeå universitet, Institutionen för informatik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | Informatik Student Paper Master (INFSPM) ; 2022.07 |
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