NORTHWESTERN (US) — Mining existing patient data from electronic medical records for genetic testing will speed up the process and make it less expensive as well.
For a new study, researchers culled information from routine doctors’ visits at five national sites that all used different brands of medical record software. By doing so, they were able to accurately identify five kinds of diseases or health conditions—type 2 diabetes, dementia, peripheral arterial disease, cataracts, and cardiac conduction.
“The hard part of doing genetic studies has been identifying enough people to get meaningful results,” says Abel Kho, assistant professor of medicine at Northwestern University. “Now we’ve shown you can do it using data that’s already been collected in electronic medical records and can rapidly generate large groups of patients.”
The paper appears in the journal Science Translational Medicine.
To identify the diseases, Kho and colleagues searched records using a series of criteria such as medications, diagnoses, and laboratory tests. They then tested their results against the physicians’ reviews. The physicians confirmed the results, Kho said. The electronic health records allowed researchers to identify patients’ diseases with 73 to 98 percent accuracy.
Previous genetic findings from prospective studies using the electronic medical records were also successfully reproduced. The five institutions that participated in the study collected genetic samples for research and patients agreed to the use of their records for studies.
Sequencing individuals’ genomes is becoming faster and cheaper. It soon may be possible to include patients’ genomes in their medical records, Kho notes. This would create a bountiful resource for genetic research.
“With permission from patients, you could search electronic health records at not just five sites but 25 or 100 different sites and identify 10,000 or 100,000 patients with diabetes, for example,” Kho says.
The larger the group of patients for genetic studies, the better the ability to detect rarer affects of the genes and the more detailed genetic sequences that cause a person to develop a disease.
Additionally, the study highlights across-the-board weaknesses in institutions’ electronic medical records. For example. institutions don’t do a good job of capturing race and ethnicity, smoking status, and family history, all which are important areas of study, Kho says.
“It shows we need to focus our efforts to use electronic medical records more meaningfully.”
The research was supported by the National Human Genome Research Institute with additional funding from the National Institute of General Medical Sciences.
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