Avert-IT is an EU-funded project to develop a mechanism, for use within intensive and high-dependency care units, which will have the ability to monitor and predict the likelihood, and primary causes of arterial adverse hypotension events.
The main scientific objective of the project is to determine the association between multiple patient parameters and subsequent arterial hypotension. The main technological objective will be the development of an IT-based decision support system ("HypoPredict") appropriate for deployment within intensive and high dependency care units. The system will be capable of:
- Automatically and continually monitoring at least four in-vivo patient parameters (ECG, arterial blood pressure, Oxygen
saturation and core temperature), together with open interfaces providing input of key demographic data (age, gender etc.)
and periodic data (clinical pathology results etc.) related to the patient.
- Outputting a continuous Hypotension Prediction Index (HPi).
- Providing primary and secondary weighted causal data (current values of input parameters) in parallel with the HPi to facilitate appropriate intervention selection by clinician (for example, elevated core temperature could be indicative of sepsis, a common precursor to hypotension).
- Providing updated HPi, and primary and secondary causal data values, immediately upon any change detected in the patient parameter input set.
A further objective is the development and maintenance of a distributed clinical data monitoring platform ("HypoNet"), capable of integrating with a wide variety of clinical monitoring systems, then automatically transmitting this data - securely - to a central repository. Current systems that can interface to HypoNet are:
- Draeger Infinity Gateway (HL7)
- Philips DocVu
- Datex Ohmeda
- ADI LabChart
- Odin Browser
The resources in terms of data, technology and expertise for the project will be combined from a variety of areas:
- Historic patient care data from 22 specialist brain injury units across Europe.
- Distributed e-Science technologies for secure data access across multiple specialist units and hospitals.
- Baysian Artificial Neural Network (BANN) techniques for analysing data.
- Specialists in treating Traumatic Brain Injury (TBI) from 6 leading hospitals, in Sweden, Germany, Italy, Spain, Lithuania and Scotland.
The project will also look to develop an exploitation model for the commercialisation of the software in product/service sales across international markets. Potential opportunities include:
- Clinical trials of drugs and interventions
- BANN (Bayesian Artificial Neural Network) techniques for asset performance management and environmental monitoring and control
- Distributed patient treatment data collection for physiological research
For more information on the Avert-IT project please contact Rob Donald (email@example.com), Ian Piper (firstname.lastname@example.org), Anthony Stell (email@example.com) or Lydia Lepecuchel (firstname.lastname@example.org).
Page updated on the 31st August 2010
Maintained by Anthony Stell