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Process Mining Dashboard in Operating Rooms: Analysis of Staff Expectations with Analytic Hierarchy Process
Antonio Martinez-Millana1, Aroa Lizondo2, Roberto Gatta3
1Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, Camino de Vera S/N, 46022 Valencia, Spain. anmarmil@itaca.upv.es.
International Journal of Environmental Research and Public Health
|January 16, 2019
Summary
Real-time location systems in operating rooms can improve surgical processes using process mining. Different staff roles prioritize dashboard features differently, highlighting the need for a flexible system.
Area of Science:
- Health Informatics
- Process Mining
- Real-Time Location Systems
Background:
- Real-time location systems (RTLS) are increasingly used in hospitals for tracking.
- RTLS in operating rooms (ORs) enable advanced analytics like process mining to enhance surgical workflows.
- Clinical adoption of these technologies faces barriers.
Purpose of the Study:
- To evaluate preferred features for a process mining dashboard in hospital ORs using RTLS data.
- To understand how different OR staff roles prioritize dashboard functionalities.
- To identify requirements for effective clinical implementation of process mining.
Main Methods:
- An analytic hierarchy process was used to quantify feature prioritization.
- Operating room staff (n=10) were categorized into technical, clinical, and managerial groups.
- Feature preferences for a process mining dashboard were assessed for each staff group.
Main Results:
- Distinct feature priorities were identified among technical, clinical, and managerial staff.
- Patient flow discovery and enhancement based on location data were key functionalities.
- Varied importance assigned to features like data filtering, enhancement, node selection, and statistics.
Conclusions:
- A flexible process mining dashboard is crucial for maximizing its utility in OR management.
- Tailoring dashboard features to specific user roles can overcome adoption barriers.
- RTLS-powered process mining offers significant potential for improving clinical interventions in ORs.
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