The study, published in the Journal of the American Medical Association, said as data becomes cheaper and more available to healthcare providers the ability to store large-scale raw data -- "big data" -- for future reference with patients is critical, and current EHRs are not up to the task.
For example, genome sequencing -- the complete DNA sequence of an organism's genome at a single time -- can be quite large or approximately 6 billion base pairs in each human diploid genome and to be stored electronically requires a large amount of computing power and storage capacity.
"EHRs are designed to facilitate day-to-day patient care," study author Justin Starren of Northwestern University's Feinberg School of Medicine said in a statement. "EHRs are not designed to store large blocks of data that do not require rapid access, nor are they currently capable of integrating genomics clinical decision support."
Diagnostic tests create large amounts of data, but only a small portion of relevant information is transferred to a patient's EHR, the researchers said.
This arrangement generally worked because physicians rarely needed to refer to prior diagnostic tests.
However, data collection is changing and an individual's genetic sequence changes little over a lifetime, but science's understanding of that sequence changes rapidly, Starren said.
"Areas of DNA that were once considered genetic 'junk' are now known to play important roles in gene regulation and disease," Starren said. "We need dynamic systems that can reanalyze and reinterpret stored raw data as knowledge evolves, and can incorporate genomic clinical decision support."
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