ArticleJournal of the American Medical Informatics Association : JAMIA
Genetic testing behavior and reporting patterns in electronic medical records for physicians trained in a primary care specialty or subspecialty.
Article in Journal of the American Medical Informatics Association : JAMIA. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- Delivering genomic medicine in the United Kingdom National Health Service: a systematic review and narrative synthesis.Genetics in medicine : official journal of the American College of Medical Genetics · 2019Pooled it
- Precision Medicine Landscape of Genomic Testing for Patients With Cancer in the National Institutes of Health All of Us Database Using Informatics Approaches.JCO clinical cancer informatics · 2022Observational
- Assessing the readiness of precision medicine interoperabilty: An exploratory study of the National Institutes of Health genetic testing registry.Journal of innovation in health informatics · 2017Article
- Clinical Informatics Researcher's Desiderata for the Data Content of the Next Generation Electronic Health Record.Applied clinical informatics · 2017Article
- Implementing and Improving Automated Electronic Tumor Molecular Profiling.Journal of oncology practice · 2016Article
- Sex-specific patterns and differences in dementia and Alzheimer's disease using informatics approaches.Journal of women & aging · 2016Article
- Supporting interoperability of genetic data with LOINC.Journal of the American Medical Informatics Association : JAMIA · 2015Article
- Closing the gap between knowledge and clinical application: challenges for genomic translation.PLoS genetics · 2015Review
- How the electronic health record will change the future of health care.The Yale journal of biology and medicine · 2012Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
objectiveTo characterize important patterns of genetic testing behavior and reporting in modern electronic medical records (EMRs) at the institutional level. MATERIALS AND
methodsRetrospective 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.
resultsPatients 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).
conclusionsIn 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.