Mapping information uncertainty in hospital wayfinding through patient journey maps

Introduction. This study proposes a replicable framework to detect, code, and visualise information uncertainty during hospital wayfinding across digital and physical touchpoints, treating wayfinding as a distributed information behaviour. Method. A seven-stage patient journey model (pre-arrival to exit) structures data collection. The unit of analysis is a stage-bounded interaction with a touchpoint. Analysis. Events are coded with a codebook. Coded units are aggregated into a Stage–Touchpoint–Uncertainty matrix and transformed into heatmaps and patient journeys that display uncertainty peaks. Results. The framework operationalises uncertainty with observable, time-stamped indicators and supports triangulation. Conclusion. Journey-based, behaviour-proximal coding makes information uncertainty measurable and comparable across sites. The approach enables evidence-based prioritisation of wayfinding interventions while accommodating variability in hospital contexts and patient needs.