Mining and Visualizing Family History Associations in the Electronic Health Record: A Case Study for Pediatric Asthma

Elizabeth S. Chen, Genevieve B. Melton, Richard C. Wasserman, Paul T. Rosenau, Diantha B. Howard, Indra Neil Sarkar

Research output: Contribution to journalArticlepeer-review

Abstract

Asthma is the most common chronic childhood disease and has seen increasing prevalence worldwide. While there is existing evidence of familial and other risk factors for pediatric asthma, there is a need for further studies to explore and understand interactions among these risk factors. The goal of this study was to develop an approach for mining, visualizing, and evaluating association rules representing pairwise interactions among potential familial risk factors based on information documented as part of a patient's family history in the electronic health record. As a case study, 10,260 structured family history entries for a cohort of 1,531 pediatric asthma patients were extracted and analyzed to generate family history associations at different levels of granularity. The preliminary results highlight the potential of this approach for validating known knowledge and suggesting opportunities for further investigation that may contribute to improving prediction of asthma risk in children.

Original languageEnglish (US)
Pages (from-to)396-405
Number of pages10
JournalAMIA ... Annual Symposium proceedings. AMIA Symposium
Volume2015
StatePublished - Jan 1 2015

Fingerprint

Dive into the research topics of 'Mining and Visualizing Family History Associations in the Electronic Health Record: A Case Study for Pediatric Asthma'. Together they form a unique fingerprint.

Cite this