Knowledge-analytics synergy in Clinical Decision Support

Stud Health Technol Inform. 2012:180:703-7.

Abstract

Clinical Decision Support (CDS) systems hold tremendous potential for improving patient care. Most existing systems are knowledge-based tools that rely on relatively simple rules. More recent approaches rely on analytics techniques to automatically mine EHR data to reveal meaningful insights. Here, we propose the Knowledge-Analytics Synergy paradigm for CDS, in which we synergistically combine existing relevant knowledge with analytics applied to EHR data. We propose a framework for implementing such a paradigm and demonstrate its principles over real-world clinical and genomic data of hypertensive patients.

MeSH terms

  • Artificial Intelligence*
  • Data Mining / methods*
  • Decision Support Systems, Clinical*
  • Diagnosis, Computer-Assisted / methods*
  • Electronic Health Records*
  • Health Records, Personal
  • Humans
  • Hypertension / diagnosis*
  • Knowledge Bases*