Electronic medical records (EMRs) are widely expected to serve as a cornerstone technology that drives the delivery of modern patient care.
But can the EMR alone support all the informatics capabilities required by an ever-evolving healthcare industry? The rapid growth of precision medicine, particularly the use of genetic and genomic information during clinical decision making, is a compelling example that functionality beyond the EMR is required. Not only does genomic data represent a category of information used differently than traditional clinical knowledge, but the volume of data generated through molecular testing alone also requires informatics and management of a higher magnitude than previously required.
The EMR is designed to reflect a snapshot (or collection of snapshots) in time: clinical summaries, annotated lab and test results, operation notes, etc. These are mostly stored as isolated documents, loosely coupled with the rest of the patient chart. They need to remain available for reference over time, in some instances, so providers can chart and contextualize ongoing trends and chronic conditions. However, these views are anchored in time and represent limited actionable value during clinical decision-making months, years, and decades later.
Genomic information, on the other hand, represents a patient’s life signature. DNA rarely changes over the course of an individual’s lifetime. This means the results from germline testing – a patient’s molecular profile – conducted early in life are relevant, meaningful, and actionable during clinical decision making far into the future. They can also deliver insights exposing heritable proclivities that may be life-changing or life-saving for family members as well.
This recognition in and of itself alerts healthcare leaders that they need to adopt an advanced, more sophisticated strategy for data governance, management, and sharing than the approach traditionally applied to other clinical information systems, such as EMRs.
To be successful, healthcare organizations need an accelerator external to the EMR that is built on a data model unique to the management of molecular knowledge so test results and genomic insights can be used and shared across clinical specialties and care settings, as well as overtime. In addition, the rise of precision medicine requires an agile informatics platform that enables the cross-pollination of genomic data with clinical insights and ever-advancing discoveries in genomic science.
Consider these examples of how EMRs fall short of expectations for optimal use of genomic intelligence:
1. Studies have found that, despite ubiquitous availability of molecular tests, providers consistently fail to identify patients most at risk for heritable diseases. The Journal of the American Medical Informatics Association (JAMIA) recently released research showing that half the women meeting national guidelines for genetic screening are not getting the tests they need to determine their breast and ovarian cancer risk.
The reason? “The full story of a patient’s risk for heritable cancer within their record often does not exist in a single location,” says the JAMIA article. “It is fragmented across entries created by many authors, over many years, in many locations and formats, and commonly from many different institutions in which women have received care over their lifetimes.” In other words, no matter which EMRs they use, health systems routinely miss opportunities to improve care for patients they see. To achieve greater success, providers need tools that exceed EMR functionality and span multiple clinical systems.
2. Shortly after birth, Alexander develops a seizure disorder. The neonatologist orders a germline test to help her arrive at a precise diagnosis and begin targeted treatment. This approach is successful and Alexander thrives. In addition to genomic variants identifying the cause of his seizure disorder, the test results also contain information about other heritable risk factors, including cardiovascular disease.
Decades later, in the 70s, Alexander sees his primary care provider (PCP) with a rapid heartbeat and shortness of breath. After doing routine lab work, the PCP diagnoses congestive heart failure (CHF). If, however, the PCP had access to Alexander’s genomic test results – which remain as relevant and accurate as when he was an infant – the PCP would have noted a variation that indicated the CHF was due to dilated cardiomyopathy, requiring a different treatment regime.
It is vital that health leaders immediately begin to plan an informatics strategy that accommodates genetic and genomic data while empowering providers to leverage these insights at the point of care as they make routine, yet critical, clinical decisions. As they evaluate their approach, they would do well to ask the following questions:
– Which providers in my organization are already ordering genomic tests on their patients? How are test results being stored and managed – and can they be easily shared with and accessed by others in the health system?
– As the volume of genetic and genomic testing accelerates – and it will – how will we manage the volume of data generated? How will we apply consistent governance to the ordering process? How can we ensure results will be consumed as discrete data so our organization can optimize its value now and in the future?
– What steps do we need to take so our precision medicine strategy remains current with changing science? Which informatics tools deliver access to up-to-date knowledge bases and clinical guidelines to ensure optimal medical decisions are made?
The advent of precision medicine represents a new standard of care for healthcare providers from coast to coast. Genetic and genomic information supplies a new data set that can be used to arrive at more accurate diagnoses sooner and more effective treatment faster. This, in turn, supports better outcomes, higher patient (and provider) satisfaction, and competitive differentiation for the health system adopting precision medicine first in its market.
But to capture this value, healthcare leaders must look beyond their legacy EMRs, recognizing that they were not developed nor do they have the capacity to properly handle the upcoming data revolution. Instead, industry innovators are looking for platforms agnostic to individual EMRs and integrated with molecular labs to address the next-generation demands of precision medicine.
About Assaf Halevy
Assaf Halevy is the founder and CEO of 2bPrecise, LLC, leading an international team dedicated to bridging the final mile between the science of genomics and making that data useful at the point of care. He joined Allscripts as senior vice president of products and business development in 2013 when the company acquired Israel-based dbMotion. An initial inventor and co-founder of dbMotion, Halevy helped develop the leading clinical integration and population health management platforms in the industry today.
With 13 patents pending in the areas of actionable clinical integration, interoperability, and precision medicine, Halevy leverages his industry expertise by evaluating strategic alliances and partnerships for U.S. and international markets. Halevy was invited to participate in several U.S. government activities and contribute to an HHS privacy committee task force. In 2016, he was part of a small selective group of executives invited to the White House by Vice President Joe Biden to discuss the future of interoperability.
