Siv Bårdsen
PhD fellow at Nord University
With substantial experience in the municipal sector, including development work and implementation of digital systems, I recently completed my master’s degree in social analysis, focusing on the regulation of Artificial Intelligence in Norway. The work on my thesis ignited a desire to pursue an academic career. I am now part of the OptiCare-AI project at Nord university, where my research examines the use of Artificial Intelligence in shift scheduling within home-based health care across three municipalities. What happens when complex considerations involving users' needs, employees' competencies, team dynamics, and unforeseen events must be translated into algorithms? Which dimensions of scheduling remain invisible to the system, and how does this affect managers' trust in and adoption of the technology? My research aims to identify measures needed to support successful implementation, professionalization, and responsible use of such solutions.
Tell us about your project!
This project is part of OptiCare-AI: Optimization of home-based health care – AI-driven solutions for full-time culture and competence utilization at Nord University. The aim is to develop knowledge-based solutions that better enable home- based healthcare to handle staff shortages through more effective competence utilization and targeted technology development.
A Norwegian Official Report (NOU 2023:4) emphasizes that work scheduling in Norwegian municipalities has not evolved in line with newer medical and organizational needs, and highlights to the need for targeted measures and competence enhancement.
The project employs a mixed-methods approach (convergent pre-post design) to examine shift scheduling in home-based health care before and after the introduction of AI-based solutions in three municipalities. The study combines quantitative measurements (time use, overtime, occupational health and safety violations, temporary staffing, sick leave, and exposure to AI-generated shifts) with qualitative data (focus groups and observations) to explore which organizational, cultural, and data-related conditions affect the applicability and integration of AI in shift scheduling.
“The aim is to develop knowledge-based solutions that better enable home-based healthcare to handle staff shortages through more effective competence utilization and targeted technology development.”
— Siv Bårdsen on her PhD project “Implementation of AI-based shift scheduling in home-based health care: a mixed methods study”