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AI-Driven Business Model in Health Data Platforms : A Case Study of HippocrAItes

Machourek, Kamil (2025)

 
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Machourek, Kamil
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025060219489
Tiivistelmä
This thesis looks how artificial intelligence helps make innovation in healthcare data platforms. Study case of HippocrAItes, which is Finland startup that specializes in health data integration. Healthcare systems today have many problems - data is in different places not connected, costs go up all time, and we need change from just treating sick people to preventing illness before it happens. AI platforms can help solve these problems by connecting different health information and also making business models that work long time.

My research shows how AI platforms can fix important healthcare problems through connecting all data together, while still following complex rules like European Health Data Space (EHDS). I used qualitative methods for my research and collected data using semi-structured questionnaires from companies working in healthcare technology sector. Questions were about how they really implement things in practice, what experience they have in market, problems with technical integration, and what business results they got.

What I found shows that good health data platforms must balance making new technical things with practical considerations about if users will accept them, following all regulations, and having business model that makes money. HippocrAItes does many things right that match with success factors I found in research. They have platform architecture that fixes problem of fragmented data by putting many different sources into one system. They focus both on giving control to normal people and making useful tools for doctors and nurses.

My research also shows that for AI work good in healthcare, we need AI models made special for healthcare, not just general algorithms. We need strong ways for integrate data, value propositions that speak to different stakeholders, and good approaches for help organizations change. Companies must solve challenges like making their system fit with existing clinical workflows, changing organization culture that resists new technology, following complicated regulations, and creating revenue models that work with special economics of healthcare.
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