The EHRs now being installed in hospitals, viewed as the key hospital information systems, are totally unable to mange the "big data" that is being generated as a byproduct of precision medicine. This was the conclusion in a viewpoint article in JAMA by Justin Starren and co-authors. (see: Electronic Health Records Upgrades Needed for Big Medical Data). Starren is chief of the Division of Health and Biomedical Informatics in the Department of Preventive Medicine at Northwestern University Feinberg School of Medicine. Here is an excerpt from an article describing their views:
Even as physicians across the nation transition to electronic health records, commonly known as EHRs, these data systems are not sophisticated enough to handle or store the amount of electronic information created by currently available medical technology, argue the authors of a new viewpoint published online in JAMA ( Crossing the Omic Chasm. A Time for Omic Ancillary Systems). According to the authors, this chasm will only continue to grow as “big data,” including next-generation genomic sequencing, becomes cheaper and more available to healthcare providers. As fields such as genomics, epigenomics, and proteomics advance, the ability to store large-scale raw data for future reference with patients is critical, and current EHRs are not up to the task. “EHRs are designed to facilitate day-to-day patient care,” says ...Starren....“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.”When diagnostics tests create large amounts of data,...only a small portion of relevant information is transferred to a patient’s EHR....With the rise of genomics, epigenomics, proteomics, and metabolomics..., however, the data are different....We need dynamic systems that can reanalyze and reinterpret stored raw data as knowledge evolves, and can incorporate genomic clinical decision support.”....The authors propose dedicated ancillary storage systems as an interim solution to store and analyze raw omics data.“ This approach adds value by providing a location to store variants of unknown significance until enough knowledge emerges to move these variants into clinical practice,” says Starren....The authors note that large organizations like Northwestern will likely operate their own ancillary omics systems, while smaller practices may use reference laboratories. Genomics clinical decision support systems may be part of the omics ancillary system, they write, but the decision system can also be external to the organization.“The time for omics ancillary systems is now,” concludes Starren.
Starren and colleagues are right on target here. Large academic centers are spending hundreds of millions of dollars, or even billions in the case of Kaiser, on EHRs that merely replicate the paper medical records of the past. Little attention is being paid by hospital executives and chief medical officers to the need to access and analyze the "big data" that is generated in the -omics sciences. Cancer genotyping is already leading to radically new approaches to cancer treatment (see: Cancer Centers Racing to Map Patients’ Genes). They are also correct with their following statement: ...[L]arge [academic hospitals] will likely operate their own ancillary omics systems, while smaller practices may use reference laboratories. Most of the knowledge related to the storage and interrogation of -omics information has been developed on the research side of these academic centers and these scientists will lead the way to the development of specialized -omics systems. Starren suggests in his paper that some of the solutions will be developed by the eMERGE Network. Here's a description of this network from the web home page:
The Electronic Medical Records and Genomics (eMERGE) Network is a national consortium organized by NHGRI (National Human Genome Research Institute) to develop, disseminate, and apply approaches to research. It combines DNA biorepositories with electronic medical record (EMR) systems for large-scale, high-throughput genetic research with the ultimate goal of returning genomic testing results to patients in a clinical care setting. The Network is currently exploring more than a dozen phenotypes (with 13 additional electronic algorithms having already been published). Various models of returning clinical results have been implemented or planned for pilot at sites across the Network. Themes of bioinformatics, genomic medicine, privacy and community engagement are of particular relevance to eMERGE.
Unfortunately, the large academic centers are being so badly drained of resources to pay for their EHRs, there may not be enough left over to develop the necessary ancillary -omics systems.