Life Sciences

Genomics – Getting the Right Data

  Genomics – Getting the Right Data

Everyone is unique – from our DNA to fingerprints. As such, I recently signed up for genomics testing to determine both my lineage and what health factors I should be aware of now and as I age.

Genomics and the Implications for Precision Health

To help me understand those testing results, I educated myself on some of the basics and the implications for precision health. Here is some of what I learned.

Sequencing DNA is limited today, so the focus is on known genetic markers that are important for validating what can be identified for proactive care. Genetic markers are sequences of DNA located near genes – defective or disease-causing genes, or even genes noted for positive attributes – that can be used to indicate the presence or absence of these genes. Single nucleotide polymorphisms (SNPs) represent a single DNA building block where these variations act as biological markers that help clinicians locate genes that can be associated with a disease.

Sequencing of the genome creates enormous amounts of data, which in the future, needs to be tied to the electronic health record (EHR) in order for diagnosis and treatment plans to be effective. The EHR is effectively the phenotype data repository for a particular patient and a vehicle to facilitate being able to correlate disease with these markers, which is a very active current area of research.

Why is this important? When you break a bone and go to the emergency room, the clinical staff knows what is wrong because that is a fairly simple diagnosis. However, all diagnoses are not that simple, and genetic markers can support more complex diagnosis and treatment.

Doctors already suffer from the “information paradox”— which is having excessive information available in record, but that is not readily available or available in the form needed when it is needed. With enhancements to existing EHRs to allow for information from non-clinical inputs, including genomic testing outside of traditional hospital environments, genomic information has great potential for improving treatments and making more efficient care.

Data Challenges to Proactively Identify At-Risk Health Factors

There are many challenges with genomic and personal health information (PHI), including large and complex data that are recorded either as structured (via databases) and unstructured (via clinical notes) data. To be able to examine and mine these data can require substantial computational support and demand domain-specific knowledge to really understand it. Both informatics and clinical champions must unite to address data analytics and statistics, visualization and user interaction, programming, and system configuration and construction. These champions must be supported by medically knowledgeable domain experts.

Impact on Medical Diagnostics

There are three areas that support improved diagnostics. They include:

Functional genomics: functional analysis of genes to correlate causes and conditions conducive to certain symptoms or disease

Novel diagnostics: linking genes to diseases and to traits in hopes of a better treatments or therapy

Personal genomics: understanding the link between genomics and your personal genomic DNA map

Applying knowledge from learnings – such as making precautionary behavioral changes to diet and exercise, or from environment factors if there is a predisposition to a disease as noted from a genetic marker – might help prevent a disease rather than just treating it when it reaches a critical stage, thereby reducing the need for expensive treatments.

To get to this future state, there are many data challenges being addressed including high dimensionality, semi-structured, distributed and decentralized, subjective errors or incomplete patient information and their correlation to genotypes.


Allow data from other sources that are non-clinical to be part of the personal health record (PHR) component of the patient record. Capturing this information will allow for future improvements in health and care of patients. Making these data available to clinicians can improve the information available for improved diagnosis.

The Genomic Challenge for You

As a leader within healthcare and an advocate for data quality, what are other resolutions you see that we can overcome these challenges?

If you’re not a current HIMSS member, consider joining our organization, connect with other leaders and help drive healthcare toward quality data sharing, aggregation and utilization that enables precision medicine.


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