Purpose of review:
More data are anticipated from the expected increase in use of electronic health records (EHRs). Upcoming initiatives require reporting of quality measures, meaningful use of clinical decision support, alert systems, and pharmacovigilance – knowledge resulting through use of EHRs. Data mining is a new tool that will help us manage information and derive knowledge from these data, and is a part of evolving new disciplines of informatics and knowledge management.
Studies are reported from smaller clinic data marts to larger repositories and warehouses in various health systems, biomedical registries, and the medical literature on the Internet. Data mining technologies show promise and challenges. Outcome measures as structured data and narrative text can be mined with human assistance and newer automated natural language processing software. Despite advances, the growing diversity of clinic EHRs lack integration and interoperability with Internet-based biomedical databases.
Allergists have the capability to mine clinic EHRs to discover new information, which may be hidden in charts. A central allergy computer can serve not just as a registry but also allows functionalities to enable EHRs’ meaningful use. Harmonization of technological and organizational standards will allow seamless use of new natural language processing (NLP) tools and ontologies through a semantic web.
Dalan, Dan. “Clinical data mining and research in the allergy office.” Current Opinion in Allergy and Clinical Immunology (February 22, 2010). http://journals.lww.com/co-allergy/Abstract/publishahead/Clinical_data_mining_and_research_in_the_allergy.99896.aspx.