PhD Dissertation Defense - Yan Heras
Apr 19, 2012 1:00 AM
Integrating Constitutional Cytogenetic Test Result Reports into Electronic Health Records
Location: HSEB 2958
Date: May 2, 2012
Time: 3:00 pm
Supervisory Committee: Stan Huff, M.D.; Arthur Brothman, Ph.D.; Peter Haug, M.D.; Joyce Mitchell, Ph.D; Scott Narus, Ph.D.; Marc Williams, M.D.
Genetic testing is becoming increasingly important to medical practice since the completion of the Human Genome project. To realize the full promise of personalized medicine, we need to first integrate genetic and genomic information into Electronic Health Records (EHRs) as coded and structured data using standards. However, EHRs are not ready for personalized medicine; lack of standardized information models and terminologies for genetic and genomic data representation is recognized as one of the major barriers.
In this study, we have focused on constitutional cytogenetic tests. We first evaluated the Logical Observation Identifiers Names and Codes (LOINC), the de facto vocabulary standard for representing laboratory test names and results, and identified that a gap exists in LOINC to support the integration of cytogenetic test results into EHRs. We analyzed sample clinical reports from several large cytogenetics laboratories, and developed LOINC panels and codes for representing constitutional cytogenetic test findings through the LOINC panel approach. The LOINC committee approved the cytogenetic LOINC panels and officially released them as part of the LOINC database in December 2010. We then followed the well vetted standard development process of Health Level Seven (HL7), developed and balloted a HL7 version 2 implementation guide that details how these LOINC panels are coupled with the messaging standard to transfer cytogenetic test results over the wire. We also described the advantages of coupling the LOINC panel content to HL7 version 2 messages, and why we think this approach could be a practical and efficient way for implementers to develop interfaces that utilize standard information models bound to standard terminologies.
We have filled the gap that there were no standard information models and no standard terminologies for representing constitutional cytogenetic test results, and have developed the foundation to allow incremental enhancement in the future.
Yan Heras is a Ph.D. Candidate in the Department of Biomedical Informatics at the University of Utah. Currently, she is a senior medical informaticist with Lantana Consulting Group. She has been the lead information analyst for several quality measure respecification projects with Center for Medicare and Medicaid Services (CMS) and National Quality Forum (NQF), and a co-editor to the Quality Reporting Document Architecture (QRDA) Implementation Guide for CDA Release 2 (US Realm). Prior to join Lantana, she was with Intermountain Healthcare for seven years with primary focus on data modeling and terminology.