Genomic data may be the key to optimizing decision-making and streamlining healthcare delivery for payers

Precision medicine is revolutionizing the healthcare industry, and payers are starting to pay attention and recognize the value genomic data holds. In recent years, payers have started to apply insights gleaned from actionable genomic data to optimize decision-making and, consequently, reduce costs and improve patient outcomes.

The value of genomic data for payers

Genomic data offers a deeper understanding of patients’ genetic makeup and ability to stratify patients into risk categories. For example, payers can identify patient cohorts likely to respond well to specific therapies or prevention strategies. With this knowledge, payers can better choose when to engage plan members, what interventions and therapies to cover and how, and at what reimbursement rates.

In another example, the FoundationOne CDx genomic profiling test can help identify targeted treatments for patients with cancer. Several payers, including Medicare and Blue Cross Blue Shield, cover the cost of the test for certain cancer indications. These coverage decisions were based in part on real-world evidence showing that use of the test can improve treatment outcomes and reduce healthcare costs. As genomic data becomes incorporated into clinical care beyond Oncology, we expect to see payers using more sophisticated data granularity to accurately identify high-risk patients, optimize the healthcare journey, reduce readmissions, and improve outcomes.

How is genomic data being used to solve reimbursement and value based care challenges?

Payers are using genomic data to inform the restructuring of reimbursement mechanisms and policies so they can adequately accommodate newer, higher cost precision medicines. One way they’re doing this is by tying reimbursement more strongly to clinical outcomes for new drugs that have been priced with the assumption that they work nearly all the time, but in fact, work best in subsets of the population.

Over the past decade, payers have also been slowly migrating toward value-based care models which use precise insight from inputs like genomic data to assess how much value patients can get from specific treatments. Some payers are developing precision medicine-focused programs to promote the utilization of patient genetic information in treatment decision-making. Last year, the HMO Blue Care Network launched a precision medicine program that will use pharmacogenomics to ensure providers can effectively personalize medication treatment as early as possible. In 2019, Aetna partnered with other healthcare players to establish the Transform Oncology Care (TOC) program. The program aims to improve precision medicine accessibility and empower informed treatment decision-making based on clinical and genetic profiles from broad panel gene sequencing.

Payers with initiatives like these may start to see lower costs as providers in their network deliver more effective targeted treatments— resulting in slower disease progression, reduced readmissions, and improved outcomes.

Impact to pharma companies and drug reimbursement

Payers increasing adoption of genomic data will likely impact pharma companies and drug reimbursement by raising the demand for targeted therapies and redefining the way drug value is determined:

• Clinical Value: As payers accept more targeted therapies under formulary, pharma companies will need to continue to prove the clinical utility of their molecules. This may lead to more robust clinical trials and post-market studies that consider genetic and genomic profiling when demonstrating drug efficacy in target populations.
• Economic Value: Payers may also use genomic data to determine the value of a particular drug. For instance, if a drug is ascertained to be effective for only a small subset of patients with a specific genetic profile, payers may want to negotiate tiered pricing for different populations. Pharma companies will need to provide substantial economic data to support their drugs’ value proposition.
• Expanded Access: Finally, payers will likely expand coverage for genetic tests and targeted therapies as patient access to and provider demand for them rises. This will expand populations eligible for targeted therapies and improve access for patients.

Use case: Payers use pharmacogenomic data to predict response to drugs in Inflammatory Bowel Disease

Commercial payers in the U.S. have worked pharmacogenomics testing into their coverage policies for therapies that can be effective for specific subsets of patients. For example, Thiopurines, a class of immunosuppressive drugs commonly used in the treatment of IBD, can cause serious side effects in some patients. Pharmacogenomic testing can help identify patients who are at increased risk of thiopurine-induced toxicity. Seeing an opportunity to reduce risk, insurers like Aetna have initiated coverage policies that include pharmacogenomic testing for thiopurine therapy in patients with IBD. Cigna has a coverage policy that includes genetic testing in patients with Crohn’s disease or ulcerative colitis who may be eligible for infliximab. Genetic testing can show a patient’s likelihood of response to Infliximab, a biologic drug that targets TNF-alpha and helps the insurer target effective therapy at patients that will benefit the most.

Use case: Payers use genomic data to guide treatment of early breast cancer

The use of genomic assays like the Oncotype DX test made by Exact Sciences, which is covered by Medicare, Medicaid, and many commercial payers in the U.S., has been shown to provide valuable information to guide treatment for early breast cancer in the Netherlands. In this case researchers found that testing with Oncotype DX test in patients with early-stage breast cancer proved to be cost-saving versus MammaPrint and no genomic profiling tests. They also found that those patients who received the Oncotype Dx test had fewer adverse events, sick days, practice visits, and hospitalizations compared to MammaPrint and no genomic profiling. They concluded that introducing the Oncotype DX test to this particular Dutch clinical setting would likely reduce the economic resources that were required to treat early breast cancer patients. As researchers continue to identify biomarkers and oncogenes that strongly predict recurrence and treatment responses, payers that incorporate these learnings into their approach will be well-positioned to optimize care for patients.

The Bottom Line

Payers are already using genomic data to deliver more precise therapy and increasingly effective preventive healthcare strategies which have the potential to improve patient outcomes. We expect to see payers use genomic and genetic data to tailor engagement with plan members, determine interventions and therapies to cover on formulary, and set reimbursement rates as the use of genomic diagnostics and data grow. Accordingly, pharma companies and other stakeholders in the healthcare industry must proactively fine-tune their strategies and facilitate collaboration to account for the myriad of ways genomic data will factor into payer decision-making.

The author Marty Miller is the Chief Revenue Officer for Ovation. Prior to Ovation, Marty was the Chief Growth Officer for Life Sciences, Provider Analytics and State Government at Optum, a subsidiary of UnitedHealth Group.

Resources

• “Precision Reimbursement for Precision Medicine: Using Real-World Evidence to Evolve From Trial-and-Project to Track-and-Pay to Learn-and-Predict”, January 1, 2022.
• Emerson, Jakob. “Blue Care Network Launches Genetic Testing Pilot Program to Personalize Members’ Medicine.”, April 25, 2022.
• CVS Health Payor Solutions. “How CVS Health® and Aetna® are transforming cancer care.”
• CVS Health Payor Solutions. “Supporting a New Personal Best in Cancer Care | CVS Health Payor Solutions,” January 7, 2020.
• “Cost and Clinical Benefits Associated with Oncotype DX® Test in Patients with Early-Stage HR+/HER2- Node-Negative Breast Cancer in the Netherlands,” September 22, 2022.
• Exact Sciences. Billing and financial coverage information.