Precision Health Testing

The Precision Medicine Landscape

Experts in the healthcare industry are all over the map with precision medicine. The term means something different for nearly everyone.

And, as is the nature of cutting-edge technology, precision medicine often changes right before our eyes. Unpacking the precision medicine landscape sometimes feels like trying to explain the weather in Utah—blizzards in the morning and a spring breeze by five.

However, there are some commonalities worth discussing.

The Challenges:

Provider organizations hoping to get into precision medicine have a long road ahead. Successful application of precision medicine is not just getting the right infrastructure in, but knowing what the right infrastructure even looks like to begin with.

I spoke with an organization working on incorporating family history into their medical records. There are some reasonably sophisticated tools out there for displaying family history information. However, pushing discrete data from those tools to the EMR is more difficult. (Sound familiar?)

If an organization wants to transform precision medicine from a research domain into an impactful care strategy working in real time, we can’t overstate the importance of incorporating genomic information into clinical workflows in an actionable format. This requires discrete, codified, and structured data, a tall order for such a new, emerging area of medicine.

Precision medicine also requires more than just technology. It can be difficult to find experts in the field who can support precision medicine work. And the workforce required looks different for a cancer center compared to an academic medical center.

What KLAS Is Finding:

KLAS is currently working on forming a more solid picture of how provider organizations utilize precision medicine. We want to help others know what technology is available and in use at health systems today. This covers the full spectrum of applied genomics, everything from the “upstream” tech, such as genetic sequencing and data management to the “downstream” applied tech like analytics and decision support.

The ultimate goal is to move from research, consumer testing, and genomic data curation, on to this emerging area of applied genomics. Health IT should enable providers to affect real patients on a collective and individual basis. By delving into precision medicine, KLAS hopes to help stakeholders answer questions about approaches to a precision medicine program and what technology exists out there to support them.

For example, technology has the potential to help remove major headaches for provider organizations by providing reliable reference content. Genomics data standards are still developing, and that can cause a lot of angst when trying to comb through terabytes of information. Data scientists have trouble finding what they need in the data. Several solutions have arisen that are designed to act as constantly updated, comprehensive genomic-data reference tools; the idea is to structure and access evidence-based material that can easily be queried for clinical and research purposes.

In coming months, KLAS plans to talk to thought leaders using many types of applied genomics capabilities and aggregate their insights to provide clarity and direction into this complex space.