Abstract
BackgroundDelay in identifying deterioration in hospitalised patients is associated with delayed admission to an intensive care unit (ICU) and poor outcomes. For the HAVEN project (HICF ref.: HICF-R9–524), we have developed a mathematical model that identifies deterioration in hospitalised patients in real time and facilitates the intervention of an ICU outreach team. This paper describes the system that has been designed to implement the model. We have used innovative technologies such as Portable Format for Analytics (PFA) and Open Services Gateway initiative (OSGi) to define the predictive statistical model and implement the system respectively for greater configurability, reliability, and availability.ResultsThe HAVEN system has been deployed as part of a research project in the Oxford University Hospitals NHS Foundation Trust. The system has so far processed > 164,000 vital signs observations and > 68,000 laboratory results for > 12,500 patients and the algorithm generated score is being evaluated to review patients who are under consideration for transfer to ICU. No clinical decisions are being made based on output from the system. The HAVEN score has been computed using a PFA model for all these patients. The intent is that this score will be displayed on a graphical user interface for clinician review and response.ConclusionsThe system uses a configurable PFA model to compute the HAVEN score which makes the system easily upgradable in terms of enhancing systems’ predictive capability. Further system enhancements are planned to handle new data sources and additional management screens.
Highlights
Delay in identifying deterioration in hospitalised patients is associated with delayed admission to an intensive care unit (ICU) and poor outcomes
Hospital inpatients whose condition deteriorates are often transferred from a general ward to an Intensive Care Unit (ICU) in order for them to receive a higher level of care
Unplanned ICU admission is associated with a poor patient
Summary
Delay in identifying deterioration in hospitalised patients is associated with delayed admission to an intensive care unit (ICU) and poor outcomes. Hospital inpatients whose condition deteriorates are often transferred from a general ward to an Intensive Care Unit (ICU) in order for them to receive a higher level of care. Such unplanned ICU admissions from within hospital typically make up over half of the total ICU admissions [1]. HAVEN is a decision support system that can be used hospital-wide It uses a configurable predictive model and a user-defined graphical user interface to display details of patients at risk of unplanned admission to the ICU. This paper describes the architecture and technologies that we used to build the system
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
