Utilising stranded predictive intelligence support teams, we are able to proactively manage Stranded & Super Stranded patients (long lengths of stay). From the point of admission, we predict the factors which will cause patients to be stranded and provide suggested actions to improve the discharge process. We look at all patients currently in hospital, those being admitted, and those who we have discharged historically, supporting clinical and operational teams to discharge patients with confidence. For example, we can identify patients who have been successfully discharged in the past as having had ‘X,Y and Z markers’, these markers therefore working as a point of reference to demonstrate what a “good” discharge pathway looks like and helping to inform future discharge processes.


Our module highlights the profile of stranded patients and where they are in the hospital, utilising key metrics such as the proportion of total patients considered stranded or super stranded, as well as the actual proportion of bed days. This therefore enables you to track performance in this regard across specialties and wards within the organisation. Analysing both live and historic data, users can find outliers and review the profiles of these pathways in order to help address underlying issues around patients with long lengths of stay.

Our improvement team are integrated alongside the Stranded module at your site and with bed managers to ensure that we can use the solution multiagency and multidisciplinary teams to improve the discharge process.