Powered by massive data sets, precision medicine is unlocking new insight into the treatment of diseases and conditions. At the same time, pathology groups and medical laboratories are leading the way to creating the storage solutions, analytic tools, and networks that will power tomorrow’s advances in precision medicine

There is exponential growth in the amount of data generated at medical laboratories, pathology groups, and hospital diagnostic facilities. As gene sequencing technologies and tools continue to decrease in price but increase in both speed and accessibility, the volume of data will grow further still.

This has major implications for the field of precision medicine. In order for physicians, hospitals, and clinical laboratories to move forward with precision medicine, to advance, it will be essential that they have sophisticated capabilities in data handling, storage, and analysis.

Yet, hospitals wanting to do more with precision medicine might not be the providers that unravel the technicalities of harnessing this new pool of big data. Pathology groups and medical laboratories are already familiar with the challenges of managing complex data, such as that created by genome sequencing and molecular diagnostic assays. As they continue to bolster their information technology (IT) staffing and infrastructure, these labs are positioned to be the keepers for much of the data driving new medical developments.

Hospital IT Departments Lag in Preparations to Handle Genomic Data

In a Health Catalyst survey, 59% of healthcare executives polled do not believe that precision medicine will play a significant role in their organizations by 2020. Nearly two-thirds of respondents have no plan to integrate genomic data into their electronic health record (EHR) systems.

Despite the trend against genomic data integration, the same survey noted that half of the respondents believe that DNA sequencing could improve patient treatment strategies within their organizations.

However, as medical laboratories have known for some time, obtaining data from molecular and genetic testing is only the beginning. Without the ability to analyze results, communicate information, and store lab test data for access by other parties, the potential benefits of precision medicine will remain unrealized.

Medical Laboratories Leading the Charge for Better Data Handling and Analysis

The good news is that within many health systems, medical laboratories are already adapting IT systems to manage the large data sets required for molecular diagnostics and genetic testing. One of the lessons these labs are learning is that the more molecular and genetic testing the do, the more informatics staff they need.

Simply said, these innovative labs are devoting more physical space to informatics and a larger proportion of the laboratory staff are informatics specialists. In The Dark Report, Gregory J. Tsongalis, PhD, Professor of Pathology and Director of Molecular Pathology at the Theodore Geisel School of Medicine at Dartmouth College, stated, “We just opened a new clinical lab facility of 11,000 square feet at the Geisel School. Over 25% of that space will be devoted to data management. Because of the increasing volume of data generated at this site, there are more computational technologists than lab technicians.” (See The Dark Report, “New Molecular Analyzers to Bring Big Data to All Labs, July 13, 2015.)

 

Gregory J. Tsongalis, PhD (center right), is Professor of Pathology and Director of Molecular Pathology at the Theodore Geisel School of Medicine at Dartmouth College. (Photo copyright: The Geisel School of Medicine at Dartmouth.)

Gregory J. Tsongalis, PhD (center right), is Professor of Pathology and Director of Molecular Pathology at the Theodore Geisel School of Medicine at Dartmouth College. (Photo copyright: The Geisel School of Medicine at Dartmouth.)

Tsongalis believes that labs themselves are positioned to become the storage providers and gatekeepers for much of the data driving precision medicine. Noting an increasing shift toward staffing informaticists in clinical labs to handle data, he says, “This is probably one aspect of the big data trend where pathologists and lab scientists are ahead of health system administrators.”

Medical Labs Must Address Issues Associate with Handling Genomic Data

Regardless of who holds the increasing amount of genomic data coming out of assays and tests, healthcare providers, laboratories, and vendors must create a set of standards to address both integration with EHR systems, and maintaining privacy and security on a scale never-before addressed.

In an article published in Health Data Management, Deven McGraw, Deputy Director for Health Information Privacy at the Department of Health and Human Services Office for Civil Rights, stressed the importance of data security as the regulatory agency begins work on aspects of the Precision Medicine Initiative. “A robust data security framework will be built in from the start. This is a new model for scientific research, but it is not widespread,” McGraw stated.

The Action Collaborative on Developing Guiding Principles for Integrating Genomic Information into the Electronic Health Record Ecosystem also is piloting a collaborative between Intermountain Healthcare, ARUP Laboratories, and Cerner, to examine privacy standards as well as standards for integration and representation of genomic data sets.

As pools of healthcare data and medical laboratory test results continue to grow and clinical laboratories continue to explore new methods of genetic testing and analysis, partnerships such as the Action Collaborative will remain critical opportunities for medical laboratories and pathology groups to use their current advantage to further their future roles in precision medicine.

—Jon Stone

Related Information:

Survey: Most Healthcare Organizations Unprepared for Precision Medicine 

Big IT Challenges Ahead for Precision Medicine 

About the Precision Medicine Initiative Cohort Program 

Fact Sheet: President Obama’s Precision Medicine Initiative 

DIGITizE: Displaying and Integrating Genetic Information Through the EHR 

Newer, Smaller Analyzers Will Bring Big Data to Labs 

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