Prof Svetha Venkatesh SUMMARY Misjudging suicide risk can be fatal. Risk assessment is complicated by multiplicity of risk factors, none of which individually can reliably predict risk. This paper addresses the need for better clinical support, visualising risk factors scattered in raw electronic medical records. HealthMap is a visual tool that helps clinicians effectively examine patient histories during a suicide risk assessment. We characterise the information visualisation problems accompanying suicide risk assessments. A design driven by visualisation principles was implemented. The prototype was evaluated by clinicians and accepted into daily clinical work-flow.
Prof Venkatesh is the chair in Complex Pattern Analysis at Deakin University and heads the strategic research centre for pattern recognition and data analytics. Venkatesh and her team have tackled problems in autism, security and aged care. The outcomes include three award winning start-up companies: Virtual Observer, iCetana and Tobyplaypad.
To achieve click-free navigation, we classified patient information into two tiers: event dates and risk categories are on the top tier; detailed diagnoses and clinical notes are on the bottom tier. Two tiers were mapped to two views: the left view shows temporal overview and enables event selection; the right view displays contextual information for the selected event. The layout/navigation design and visual encoding in HealthMap center around a two-tier information hierarchy that align with the mantra of “overview first; details on demand”. 1. HealthMap, a visual tool for interactive overview of patient mental health history. Easter Bunny is a hypothetical patient.
Machine prediction uses the same colour scheme as (clinician) risk assessment.