Exploiting Data in Clinical Infomatics

Clinicians lead developments in health care sciences through a proven process of discovery, publication, peer review and dissemination. The fundamental concepts enabling this process are collaboration and sharing.

New Information Technologies offer the potential for both expansion of the collaboration, and acceleration of the review process. Our project will harness that potential, prove the benefits and encourage adoption of similar techniques. We’ll prove the value of aggregated data, cross centre analysis and global dissemination.

We’ll use software to collect parameter data at the bed side, secure the patients privacy, transmit the information for aggregation and analysis, report patient specific intelligence back to the bedside, and discipline specific information back to the community.

And as part of the process we’ll improve the quality of our analysis. Our Bayesian Neural Network will learn more through each cycle, becoming more accurate in its pattern recognition. It’ll also tell us a lot more of events during care and direct other improvements.

This is all the direct output of our research, which is targeted at reducing risks to patients through anticipating adverse events.

An indirect result of the research will be our infrastructure:

* Secure, grid based network incorporating six neurosurgery centres.
* Bed side data capture software.
* Bed side reporting of analysis results.
* Central aggregation and accumulation of international care parameter data.
* Central “mining”, “analysis” and “learning”.

It’s not hard to see this very infrastructure offers potential value to other researchers, both academic and commercial.

Right now we’re working on plans to commercialise this value and interested in swapping ideas with any organisations – (government, academic and commercial) who’d like to help create a new business model for clinical intelligence.