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The 2025 DirectTrust Annual Conference
2025-08-04 - 2025-08-07    
12:00 am
Three of the most interesting healthcare topics are going to be featured at the DirectTrust Annual conference this year: Interoperability, Identity, and Cybersecurity. These are [...]
ALS Nexus Event Recap and Overview
2025-08-11 - 2025-08-14    
12:00 am
International Conference on Wearable Medical Devices and Sensors
2025-08-12    
12:00 am
Conference Details: International Conference on Wearable Medical Devices and Sensors , on 12th Aug 2025 at New York, New York, USA . The key intention [...]
Epic UGM 2025
2025-08-18 - 2025-08-21    
12:00 am
The largest gathering of Epic Users at the Epic user conference in Verona. Generally highlighted by Epic’s keynote where she often makes big announcements about [...]
Events on 2025-08-04
Events on 2025-08-11
Events on 2025-08-18
Epic UGM 2025
18 Aug 25
Verona

Events

Articles

EHRs should develop as large Information use develops

ehrs

As big data use continues to increase in healthcare, electronic health records will need to evolve simultaneously, researchers from Northwestern University, Geisinger Health System and Mount Sinai School of Medicine write in a viewpoint recently published in the Journal of the American Medical Association. Current EHRs, the authors say, are not built to handle the capacity of data created by current electronic medical tools, a problem that will only continue to grow as data access becomes easier.

“EHRs are designed to facilitate day-to-day patient care,” co-study author Justin Starren, chief of the division of health and biomedical informatics in the department of preventive medicine at Northwestern’s Feinberg School of Medicine, says in an announcement. “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.”

As a temporary solution until more advanced EHRs are developed, Starren and his colleagues suggest using auxiliary systems for the storage of data culled from what they call increasing ‘omics’ research efforts–studies focusing on genomics, epigenomics, proteomics and metabolomics. Groups like the Electronic Medical Records and Genomics (eMERGE) consortium, they say, already are “bridging the chasm” by creating interoperable systems with the ability to integrate large-scale genomic data with clinical workflow.

es to increase in healthcare, electronic health records will need to evolve simultaneously, researchers from Northwestern University, Geisinger Health System and Mount Sinai School of Medicine write in a viewpoint recently published in the Journal of the American Medical Association. Current EHRs, the authors say, are not built to handle the capacity of data created by current electronic medical tools, a problem that will only continue to grow as data access becomes easier.

“EHRs are designed to facilitate day-to-day patient care,” co-study author Justin Starren, chief of the division of health and biomedical informatics in the department of preventive medicine at Northwestern’s Feinberg School of Medicine, says in an announcement. “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.”

As a temporary solution until more advanced EHRs are developed, Starren and his colleagues suggest using auxiliary systems for the storage of data culled from what they call increasing ‘omics’ research efforts–studies focusing on genomics, epigenomics, proteomics and metabolomics. Groups like the Electronic Medical Records and Genomics (eMERGE) consortium, they say, already are “bridging the chasm” by creating interoperable systems with the ability to integrate large-scale genomic data with clinical workflow.

“Omic data are different,” the authors write. “An individual’s germline genetic sequence changes little over a lifetime, but understanding of that sequence is changing rapidly. The 1000 Genomes project has identified tens of millions of different genomic variants; the clinical significance of these variants is mostly unknown, but current understanding is rapidly changing. … This necessitates systems that dynamically reanalyze and reinterpret stored static genomic results in the context of evolving knowledge.”

(source)