Clinical Decision Support Systems

The KPF can be used to synthesize clinical decision support systems (CDSS) for a diverse range of healthcare disciplines such as the examination of real-time data from monitoring devices, analyses of patient and family history for the purpose of diagnosis, reviews of common characteristics and trends in medical record databases. Using a stratified approach, the CDSS can play a significant role in individual patient diagnosis and prognosis. Cognitive and knowledge based methods are applied constantly to analyse EMRs, medical / drug data and best practice guidelines, ensuring the latest techniques and best practice are available medical staff when making treatment decisions.

A CDSS can handle multi-dimensional and multi-criteria biomarker data (which can be conflicting) enabling a stratified response on an individual patient basis.  Based on the current data, the system can forecast “what-if” outcomes and provide analysis of the affect of a prescribed treatment over time. Different version of the technology can also be used for patient monitoring.


  • Efficient healthcare provision
  • Accelerates development of new diagnostics, medicines and clinical pathways
  • Better patient outcomes through more effective drug selection
  • Reduced adverse reactions and side effects
  • More cost effective solutions by not buying treatments that do not work and time wasted trying unsuitable medicines

The healthcare market is driven by government policies, performance evaluation, value and improved patient outcomes. Consequently, healthcare organisations can use IDSS to analyse data to improve overall operational performance. The results can determine the disease patterns, high risk patients and suggest the most suitable cost effective treatments.