Helping Nurses to Improve Their Work Organisation Using Process Data

Abstract

Today, hospitals face increasing care demands and budgetary constraints, which challenge the delivery of high-quality care. In addition, most organisations suffer from a chronic nurse understaffing. To address these challenges, hospitals are looking into ways to improve the work organisation of nurses. However, current research on nursing work organisation predominantly relies on self-reported data and observational studies, both of which present significant limitations, such as data quality concerns (e.g., the Hawthorne effect in observational settings) and the added burden on participating nurses. This research aims to provide hospitals and nursing staff with data-driven insights into current work organisation practices, enabling more informed decision making. To this end, task execution data will be automatically collected through a combination of hospital information system (HIS) data and real-time location system (RTLS) data, gathered from both nurses and mobile equipment in hospital wards. This research focuses on two primary challenges: (i) the integration of HIS-and RTLS-data and (ii) the identification and visualisation of work organisation patterns. Through addressing these challenges, this research will offer hospitals deep insights into nursing work organization without imposing additional burdens on healthcare staff, facilitating evidence-based decision making about how to best organise nursing work.