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TigerConnect + eVideon Unite Healthcare Communications
2025-09-30    
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TigerConnect’s acquisition of eVideon represents a significant step forward in our mission to unify healthcare communications. By combining smart room technology with advanced clinical collaboration [...]
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Elevate Patient Care: Discover the Power of DP & AI Pathology Visions unites 800+ digital pathology experts and peers tackling today's challenges and shaping tomorrow's [...]
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Register for AHIMA25  Conference Today! HI professionals—Minneapolis is calling! Join us October 12-14 for AHIMA25 Conference, the must-attend HI event of the year. In a city known for its booming [...]
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One of the top healthcare innovation events that brings together healthcare startups, investors, and other healthcare innovators. This is comparable to say an investor and [...]
Federal EHR Annual Summit
2025-10-21 - 2025-10-23    
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The Federal Electronic Health Record Modernization (FEHRM) office brings together clinical staff from the Department of Defense, Department of Veterans Affairs, Department of Homeland Security’s [...]
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2025-11-02 - 2025-11-05    
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NextGen UGM 2025 is set to take place in Nashville, TN, from November 2 to 5 at the Gaylord Opryland Resort & Convention Center. This [...]
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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)