Mining electronic health records: an additional perspective

We read with great interest the article by Jensen et al. (Mining electronic health records: towards better research applications and clinical care. Nature Reviews Genetics 13, 395–405)1. This was a well-written Review that summarized a large, complex and topical subject. To augment the article, and in particular to augment Table 1, we would like to point out that one of the earliest and most successful research databases that integrated diverse data sources with electronic health records (EHRs) is the Utah Population Database (UPDB) at the University of Utah, USA. Its earliest success was the identification of families with a high incidence of breast cancer; this research led to the discovery of the breast cancer genes BRCA1 and BRCA2 (Refs 2,3,4,5). A crucial component of the UPDB — one that allowed it to probe genetic inheritance long before gene sequencing was widely available — was the linking of diverse data sources with family pedigrees that were originally supplied by the Utah Genealogical Society and that were later updated by probabilistic matching with vital records from the Utah Department of Health (records such as birth, death and marriage certificates).