Initiatives in healthcare knowledge management have provided some interesting solutions for the implementation of large-scale information repositories vis-à-vis the implementation of Healthcare Enterprise Memories (HEM). In this paper, we present an agent-based Intelligent Healthcare Information Assistant (IHIA) for dynamic information gathering, filtering and adaptation from a HEM comprising an amalgamation of (i) databases storing empirical knowledge, (ii) case-bases storing experiential knowledge, (iii) scenario-bases storing tacit knowledge and (iv) document-bases storing explicit knowledge. The featured work leverages intelligent agents and medical ontologies for autonomous HEM-wide navigation, approximate content matching, inter- and intra-repositories content correlation and information adaptation to meet the user's information request. We anticipate that the use of IHIA will empower healthcare stakeholders to actively communicate with an 'information/knowledge-rich' HEM and will be able to retrieve with ease 'useful' task-specific information via the presentation of cognitively intuitive queries.
* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.