Antonia Burt, Nuffield Department of Clinical Neurosciences, University of Oxford
In the UK 110,000 patients are admitted to 240 Intensive Care Units (ICUs) annually. Of these patients 77% are discharged to the wards. Up to 12% of these patients die before leaving hospital (Intensive Care National Audit Research Centre, ICNARC). The Post Intensive Care Risk Adjusted Monitoring (PICRAM) study was designed to develop an estimate of an individual patient’s future risk of being readmitted to the ICU or of dying in hospital. This risk estimate is based on data collected during their ICU stay and subsequent vital signs when on the ward. The final phase of this project is to develop a working recognition and response system for these acutely unwell patients. To do this we need to produce a user interface able to cope with multi-site task variability in following up these complex patients.
The Human Factors (HF) team observed nurses at three hospitals as they completed their routine daily tasks to follow up patients discharged from the ICU. Semi-structured interviews were subsequently conducted. Hierarchical Task Analyses (HTAs) were produced based on the data collected for each of the three hospitals. Applied Cognitive work analyses (ACWAs) were created from the interviews. Results from the HTAs were combined with the ACWAs and used to inform the initial design of the user interface. Iterative user testing will aid the final design of the user interface.