Mapping the Barriers to AI Implementation in Swedish Healthcare Key Barriers: Competencies, Data Accessibility, and Demonstrating Value of AI Products
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Typ
Examensarbete på kandidatnivå
Bachelor Thesis
Bachelor Thesis
Program
Publicerad
2023
Författare
Albuschus Svanvik, Hannah
Landin, Filip
Madsstuen, Emil Andreas
Sjögren, Frida
Stiebe, Elin
To, Kevin
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
Artificial Intelligence (AI) has shown the potential to improve the quality of
care for patients. However, barriers are preventing its adoption, and despite its potential,
the integration of AI into Swedish healthcare remains limited. This thesis
aims to identify the most impactful barriers to implementing AI in Swedish healthcare
by identifying stakeholders, their interests, and their perceived barriers to the
implementation. The data was collected through 19 semi-structured interviews.
These interviewees were categorized into six stakeholders: clinicians, healthcare executives,
MedTech companies, patients, policymakers, and researchers. Thematic
analysis and tools from stakeholder analysis were utilized to synthesize overarching
barriers in the system. The results revealed diverse perspectives on barriers for
the stakeholders. The most prominent barriers identified were competencies, data
accessibility, and demonstrating the value of AI products. Lack of competencies
contributes to several other obstacles, and data accessibility was mentioned by all
stakeholders. Demonstrating AI products’ value is fundamental to integrating AI
into clinical practice. The thesis calls for further research to provide solutions to
the identified barriers. If solved, the large-scale implementation of AI in Swedish
healthcare will be one step closer.
Beskrivning
Ämne/nyckelord
artificial intelligence , barriers , healthcare , stakeholders , Sweden