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Genomic Data Integrated with EHRs May Soon Guide Medical Decisions

Genomic Data Integrated with EHRs May Soon Guide Medical Decisions

Electronic health records (EHRs) have received a lot of attention in recent years, especially in terms of managing them in the cloud so that the data can be shared between organizations. Another recent push is to make genomic data part of the EHR.

Genomic testing has advanced to the point that the results can help in clinical decision making and precision medicine. Already, genomic data is quite complex, so EHRs will need to evolve to incorporate and interpret this data in meaningful ways for patients and clinicians. Integration will depend on several factors, including health IT professionals with expertise in data transferability and clinicians training.

Healthcare professionals have pointed to many potential benefits of integrating genomic data with EHRs. It could facilitate more efficient diagnoses and make precision medicine more feasible, for example. In addition, genomic data can of course assist in the diagnosis and treatment of genetic disorders. Genetic information can also help patients and their doctors understand the patient’s risk of developing a genetic condition or passing it on to their children.

Genetic data may also save time and reduce costs by helping clinicians make better decisions about which tests their patients need. Researchers have also pointed to the value of linking genomic data to clinical decision support systems. Powered by machine learning, these systems provide recommendations at the point of care to help clinicians make the best decisions for their patients. Genomic information could improve the technology’s recommendations.

Challenges in Integrating Genomic Data with the EHR

Interoperability is one of the biggest hurdles in integrating genomic data. Different EHRs should be able to collect data from each other and share it with both the patient and clinicians while respecting privacy. This interoperability is key to progress in personalized medicine and other fields, but integrating different systems can be tricky.

However, organizations like the American College of Medical Genetics and Genomics (ACMG) are already working on resources that can guide genomic data integration with EHRs and promote secure sharing among different systems while respecting patient privacy. 

In a guidance document released last year, ACMG points to several resources for completing this integration in a way that respects patients’ privacy and access to information. These resources include the Health Level 7 genomics model and Fast Healthcare Interoperability Resources. The guide also makes several recommendations for how to complete this integration, such as allowing patients full access to their genetic data, including direct test results, secondary findings, and clinician interpretations. ACMG also recommends that informed consent should be altered to give patients direct right of access to their genomic data.

ACMG emphasized that more research on privacy is necessary to guarantee appropriate protections with integrated EHRs. The organization also noted that EHR access should never serve as a replacement for direct conversations between patients and their healthcare providers. At the same time, the ACMG’s guide can help institutions as they develop policies and procedures related to genomic data in EHRs. The guide identifies other obstacles involved in integrating genomic data with EHRs, such as the size and complexity of genetic data, but advances in EHR systems have largely resolved this problem. Interoperability is a bigger challenge.

What Clinicians Need to Use Genomic Data Effectively

Whether through EHRs or a genomic database, access to genomic data is already being used by healthcare providers in the diagnostic and decision-making processes. Remarkably, these decisions are being guided by a relatively small amount of genomic data for each patient. A 2021 study in the Journal of the American Medical Informatics Association Open (JAMIA Open) showed that clinicians only view only about 1 percent of available genomic data in EHRs. Part of the problem is that the data needs to be translated into clinically relevant information. 

Experts have explained that the key to getting clinicians to buy into this integration is to provide valuable insights directly at the point of care. Turning genomic data into actionable insights will require a significant investment of both time and resources. However, this is the primary way to make genomic information meaningful for both patients and clinicians.

To begin addressing this issue, the National Human Genome Research Institute recently developed the Clinical Genomic Database, a database of conditions with known genetic causes. Each entry for a condition includes data such as the gene affected, inheritance pattern, the age at which intervention is indicated, and a general description of the intervention. In other words, the database can give clinicians suggestions on the type of interventions they might consider based on their patient’s genomic data. The database could be expanded over time to provide point-of-care alerts through clinical decision support systems.

Clinicians are highly pressed for time, so it’s not surprising that the JAMIA Open study revealed they accessed so little of their patients’ genomic data in EHRs—especially since most clinicians likely do not have a background in genetics. While the insights from genomic data can be extremely beneficial for patients, again, the data needs to be interpreted and distilled into actionable points.

Moving forward, IT developers, health systems, and EHR companies will all need to work together to improve interoperability among different platforms to make genetic data truly accessible. Then, they’ll need to translate the data into clinically relevant information that clinicians can actually use during diagnosis and treatment.