Process Mining in Healthcare
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Item Uncovering Complex Relations in Patient Pathways based on Statistics: the Impact of Clinical Actions(2022-01-04) Koorn, Jelmer Jan; Lu, Xixi; Mannhardt, Felix; Leopold, Henrik; Alexander Reijers, HajoProcess mining is a family of techniques that can aid healthcare organizations in improving their processes. Most existing process mining techniques do not provide insights into the impact that activities can have on the process. Some novel techniques try to address this issue, but these techniques are either not generic in their approach or cannot provide insights into complex relations in organizational processes. We propose a novel and generic approach with the goal of producing insights into statistical relations within healthcare processes. We apply the approach on a public data set on sepsis in an emergency room. We find that the hospital might optimize its process in two respects: (1) their cost-benefit balance for patient care by considering their activities in terms of continuous monitoring and substance administration, and (2) their policies on discharging patients as to ensure patients are not discharged too early and return to the emergency room.Item PathwAI Systems in Healthcare – a Framework for Coupling AI and Pathway-based Health Information Systems(2022-01-04) Scheplitz, Tim; Burwitz, Martin; Weimann, ThurePathway-based Health Information Systems (HIS) enable planning, execution and improvement of standardized care processes. Adaptive behavior and learning effects are taken to a new level by advances in Artificial Intelligence (AI). Yet, design support to unlock synergies from coupling pathway-based HIS with AI is lacking. This Umbrella Review identifies applied purposes of AI in healthcare, describes the relation to pathway-based HIS, and derives a PathwAI Framework as design support for future research and development activities. Previous findings already provide a large base of approaches to realize personalized care pathways and improve coordination and business operations. Furthermore, potentials for designing learning health systems at micro, meso, and macro levels are formulated, but there is still greater opportunity for future research and design. Pathway-based HIS in this context can not only provide interpretable and interoperable data input, but can be conceptual as well as operational receivers of artificially generated knowledge.Item An insight to nurse workload: predicting activities in the next shift and analyzing bedside alarms influence(2022-01-04) Medeiros De Carvalho, Renata; Nguyen, Huyen; Heetveld, Maikel; Luime, JolandaThe effects of nursing shortage and the increasing nursing workload have been emphasized in recent years. Hospitals and healthcare organizations have actively implemented initiatives to combat the workforce shortage and mitigate the effects of high workload among their nurses. In cooperation with a Dutch hospital, this project seeks to understand the workload of nurses by understanding what will happen in the next shift and by measuring the alarm workload of their nurses, particularly the bedside alarms that send signals to wifi phones of nurses, to obtain a partial workload of nurses that may reflect the intensity level of the total nurse workload. The project also investigates the effects of the alarm workload, patient, working condition and staff individuality on nurse performance. Finally, the project seeks to discover possible contributing factors to the alarm occurrence, therefore finding a mitigation to reduce the bedside alarm workload.Item Introduction to the Minitrack on Process Mining in Healthcare(2022-01-04) Pufahl, Luise; Munoz-Gama, Jorge; Weske, Mathias