Blessing Ikechukwu is a researcher in the field of mathematics and statistics with a strong interest in data-driven decision-making in healthcare systems. She holds a B.Sc. in Statistics and masters' degrees in mathematical sciences and mathematical engineering respectively, where her research focused on statistical modeling and machine learning methods for health data analysis. Before joining the SUPPORT-HH project, Blessing worked as a medical statistician with a Pediatric Research Consortium, where she collaborated with multidisciplinary teams to analyze maternal and neonatal health data and support evidence-based medical research. Her work combines statistical analysis, optimization methods, and programming tools such as R and Python to address complex problems in healthcare. Within the SUPPORT-HH project, Blessing’s research focuses on the development of optimization models and decision-support tools for staff shift design in home hospitalization services. Her interests lie in operations research, healthcare management, and the application of mathematical modeling to improve healthcare efficiency, workforce planning, and patient outcomes. 

Keywords: Hospital at Home | Staff scheduling | Optimization