Genetic testing behavior and reporting patterns in electronic medical records for physicians trained in a primary care specialty or subspecialty

J Am Med Inform Assoc. Jul-Aug 2012;19(4):570-4. doi: 10.1136/amiajnl-2011-000621. Epub 2012 Apr 17.

Abstract

Objective: To characterize important patterns of genetic testing behavior and reporting in modern electronic medical records (EMRs) at the institutional level.

Materials and methods: Retrospective observational study using EMR data of all 10,715 patients who received genetic testing by physicians trained in a primary care specialty or subspecialty at an academic medical center between January 1, 2008 and December 31, 2010.

Results: Patients had a mean±SD age of 38.3±15.8 years (median 36.1, IQR 30.0-43.8). The proportion of female subjects in the study population was larger than in the general patient population (77.2% vs 55.0%, p<0.001) and they were younger than the male subjects in the study (36.5±13.2 vs 44.6±21.2 years, p<0.001). Approximately 1.1% of all patients received genetic testing. There were 942 physicians who ordered a total of 15,320 genetic tests. By volume, commonly tested genes involved mutations for cystic fibrosis (36.7%), prothrombin (13.7%), Tay-Sachs disease (6.7%), hereditary hemochromatosis (4.4%), and chronic myelogenous leukemia (4.1%). EMRs stored reports as free text with categorical descriptions of mutations and an average length of 269.4±153.2 words (median 242, IQR 146-401).

Conclusions: In this study, genetic tests were often ordered by a diverse group of physicians for women of childbearing age being evaluated for diseases that may affect potential offspring. EMRs currently serve primarily as a storage warehouse for textual reports that could potentially be transformed into meaningful structured data for next-generation clinical decision support. Further studies are needed to address the design, development, and implementation of EMRs capable of managing the critical genetic health information challenges of the future.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • Data Collection
  • Electronic Health Records* / statistics & numerical data
  • Female
  • Genetic Testing* / statistics & numerical data
  • Humans
  • Male
  • Massachusetts
  • Practice Patterns, Physicians'*
  • Primary Health Care
  • Retrospective Studies