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

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

Author information

1
Laboratory of Computer Science, Massachusetts General Hospital, Boston, Massachusetts 02114, USA. jronquillo@partners.org

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.

PMID:
22511017
PMCID:
PMC3384119
DOI:
10.1136/amiajnl-2011-000621
[Indexed for MEDLINE]
Free PMC Article
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