Unlocking Nursing Work Organization Insights through Integrated HIS and RTLS Data: Novel Methods and Applications

Abstract

Hospital nursing shortages can lead to significant drawbacks for both patients and nurses, including longer waiting times, missed assessments, delayed responses, and medication errors. Nurses also experience higher stress, increased burnout, and lower job satisfaction. Addressing these challenges requires a deeper understanding of how nursing work is organized in practice. Currently, most insights rely on nurses recording tasks in a Hospital Information System (HIS). While HIS data is context-rich, it is prone to bias and often fails to capture the timing and completeness of nursing activities due to delayed or missing documentation. In contrast, Real-Time Location System (RTLS) data provides an automatically recorded, accurate account of staff and equipment movement, but lacks clinical context and cannot specify the nature of the tasks performed. To date, most research has considered HIS and RTLS data in isolation, limiting the ability to reconstruct a more accurate view of nursing work organization. This doctoral research aims to address this gap by integrating HIS and RTLS data to generate a richer and more accurate nursing task log than either source can provide alone. By combining the strengths of both data types, the resulting unified log serves as a foundation for advanced process mining and analysis, supporting the discovery of actionable insights to improve nursing work organization.