Three Ways to Leverage Translational Research for the Understanding of Complex Disease

Translational Research

Not so long ago, medical records were scribed on paper. A doctor’s office visit or hospital procedure yielded a paper record that appended a patient’s physical file. Imagine how difficult it was to retrieve files and maintain them without the benefit of computer searches!

Times have changed, and the vast majority of medical providers now use either electronic medical record (EMR) or electronic health record (EHR) systems. These records generally include diagnosis codes, procedure codes, clinical labs, medications, clinician notes, and imaging. While the original intent of these systems was to provide better patient care, they were also grounded in the need to track medical procedures for the purpose of billing.

Good news: recent literature suggests EHRs are helping to improve care [1]. And for their next act, EHRs will be instrumental in facilitating translational research.

How? According to Marylyn Ritchie, PhD, Department of Genetics, Institute for Biomedical Informatics, University of Pennsylvania, with consent given by patients, EHRs represent a cost effective and straightforward method for medical centers and pharmaceutical companies to gain access to diverse phenotypic data for performing translational research. Additionally, states Ritchie, they are even more effective when combined with biobanks.

Voila! Cost Effective Recruitment, Continuous Data Collection, and Diverse Phenotypes

When you compare EHRs and biobanks to a typical epidemiology study, it’s easy to see why they are well suited for research studies. A typical epidemiology study involves recruiting people, incentivizing them to participate, and asking them back at regular intervals to gather additional information. The process of follow-up and collecting longitudinal data is difficult.

EHRs and biobanks offer a less expensive, more simplified route to gaining phenotypic and environmental data. If patients have consented and enrolled, then their data are already available and get updated with each new visit.

And astute researchers began to ask: why aren’t we using these data to gain a greater understanding of complex disease? After all, EHR data, when combined with biobank data, can offer us the holy grail: genomic data combined with rich phenotypic and environmental data.

There are three practical ways to use these data in translational research. Watch the video below to learn more.

Works Cited

  1. Manca DP. Do electronic medical records improve quality of care? Yes. Canadian family physician Medecin de famille canadien. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4607324/. Published October 2015. Accessed January 29, 2020.
  2. Mills MC, Rahal C. A scientometric review of genome-wide association studies. Communications biology. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6323052/. Published January 7, 2019. Accessed January 29, 2020.
  3. Verma A, Lucas A, Verma SS, et al. PheWAS and Beyond: The Landscape of Associations with Medical Diagnoses and Clinical Measures across 38,662 Individuals from Geisinger. Am J Hum Genet. 2018;102(4):592-608.