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What Your Members' DNA Could Mean for Plan Costs

Clinical Insights
May 29, 2026
What Your Members' DNA Could Mean for Plan Costs
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What you need to know - key highlights:

  • 1 in 10 members engage with PGx when a clinician calls—vs. <2% with digital outreach alone
  • Every tested member had actionable genetic insight; 42% required medication changes
  • PGx-guided care delivered ~$1,573 in estimated savings per member tested

Your members are taking medications you are paying for that may not be working. Not because of a bad diagnosis or a careless prescriber, but because of something no traditional pharmacy benefit may offer: insight into their pharmacogenetics.

Most members who could benefit from pharmacogenomic (PGx) testing never get it, largely because nobody ever explains why it matters or where to start. The Judi Health clinical team wanted to understand what would change if someone did. That question is at the heart of Rx Helix, our pharmacogenomics program powered by Judi®, our cloud-native enterprise health platform, and YouScript®, a clinical decision support tool that maps drug-gene interactions at the individual level.

At the 2026 PQA Annual Meeting, Caitlin Munro, PharmD, BCPS, Clinical Partnerships Lead, presented research examining how a direct conversation with a trained clinician before PGx testing can increase member participation, and what that could mean for cost avoidance.

Cait Munro (right) discusses the poster with PQA attendees.

The Information Gap Traditional PBMs Can't Close

PGx testing reveals how an individual's genetic makeup affects the way they process drugs. Two people can fill the same prescription at the same dose and have completely different outcomes based on their DNA alone. One processes the drug effectively so that it works. The other does not, and the plan keeps paying regardless. Traditional pharmacy benefit management was never designed to intervene.

Through Judi, Rx Helix identifies program-eligible members in real-time when pharmacy claims are adjudicated at the pharmacy point-of-sale. Members are then sent information about the program and in some cases, pharmacists and pharmacy technicians proactively outreach to members to have an informed, personalized conversation to help them decide whether to participate.

To measure the impact of this outreach, the clinician-led team reviewed two years of pharmacy claims data to identify members taking medications with known drug-gene interaction potential, followed by an 8.5-month intervention period from February through November 2025. Members were divided into two groups: those who received written outreach only, including welcome letters, SMS texts, or mailers, and those who received telephonic outreach from a pharmacist or pharmacy technician in addition to the written outreach.

For those members who decided to participate in Rx Helix, drug-gene interaction insights were assessed using YouScript®, and cost avoidance was estimated using a validated framework based on historical comparator data.1

When Genetics Enter the Conversation

In the group that received written outreach only, fewer than 2% of members completed PGx testing. In the group that received a phone call in addition to written outreach, that figure rose to 10%, a difference that is statistically significant.  

The difference points to something plan sponsors often underestimate: members are not resistant to managing their health but often missing the right information and the right person to walk them through it. This is the role our clinical team was built to fill, with pharmacists and pharmacy technicians who engage members directly, translating data into action at the individual level through programs like Rx Helix.

Caitlin Munro, PharmD, BCPS

What Testing Revealed

Among the 128 members who completed PGx testing, the findings were striking:

  • Every tested member had at least one genetic variant that could impact how their medications work. 95% had two or more.
  • 799 drug-gene interaction insights were identified across all 128 members and their medications.
  • 73 of those insights required clinical attention, with 54 individuals identified as needing a medication change.
  • The medications most commonly flagged included antidepressants, cardiovascular drugs, proton-pump inhibitors, and pain medications, some of the most widely prescribed drug classes in commercially insured populations.
  • Estimated cost avoidance in this cohort averaged $1,573 per tested member, or $185 per member per month, based on a validated framework of historical comparator data.1

The members in this study were not outliers. They were commercially insured adults taking commonly prescribed medications for chronic conditions; the same population most plan sponsors are already managing. When clinicians have access to PGx data alongside pharmacy claims, this combination is the right information to support the right medication decisions, for the right members, at the right time.

Dig Into the Data

The research was conducted by Caitlin Munro, PharmD, BCPS; Houda Hachad, PharmD, M.Res.; Jessica Savieo, M.PGx.; Joseph Spinelli, BS; Dina Barghout, MS; Haleh Campbell, PharmD; Nash Albadarin, PharmD, MBA; Lauren Carroll, PharmD, BCACP; Bonnie Hui-Callahan, PharmD, CDCES; Jay Tran, PharmD, MHA; and Sara Izadi, PharmD.

Click to enlarge.

Building the Evidence Base

PGx test results are not a one-time insight. They compound in value as members age, start taking new medications, and move throughout their healthcare journey. To help build a fuller picture of PGx value beyond pharmacy alone, the research team has identified opportunity to further assess medical claims data and post-test member satisfaction and self-reported healthcare utilization surveys as next steps.  

For plan sponsors evaluating their clinical program strategy, understanding the genetic variability within your population is a meaningful place to start. To learn how Rx Helix can help, talk to our team today.

References

  1. Brixner, D., Biltaji, E., Bress, A., Unni, S., Ye, X., Mamiya, T., Ashcraft, K., & Biskupiak, J. (2016). The effect of pharmacogenetic profiling with a clinical decision support tool on healthcare resource utilization and estimated costs in the elderly exposed to polypharmacy. Journal of Medical Economics, 19(3), 213–228. https://doi.org/10.3111/13696998.2015.1110160

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