How are health plans overpaying for genetic tests?

Inappropriate genetic test claims are often mistakenly paid, because claims systems are
unable to identify the actual test(s) performed and apply correct policy. We typically find
15-30% overpayment of genetic test claims when we analyze health plan data. Typical drivers
of genetic test overpayment include:

• Inaccurate coding of genetic testing claims

• Lack of medical necessity

• Volume overbilling, including panel testing

• Wide variation in pricing

Doesn’t preauthorization prevent all unnecessary genetic test spend?

No. Many health plans, including our clients, do successfully manage appropriate genetic
test selection with ordering providers via preauthorization. However, claims
involve a different player: the billing provider.

Our analyses and actual results are based on addressing billing practices that blur the actual test/panel identity. This approach is wholly separate from managing the ordering provider decision pre-test.

What is Genetic Test Payment Integrity?

As the authority on the appropriate use of genetic tests, we have applied our 12+ years of experience to develop Genetic Test Payment Integrity algorithms for use in health plan claims processing. These algorithms unlock test and panel identity, so that coverage and reimbursement policy can be correctly applied before tests are mistakenly paid.

How Does It Work?

Our algorithms are based on combinations of procedure codes, diagnosis codes, performing lab, volumes and patient demographics. The algorithms can be implemented directly into your claims environment, or accessed through solutions maintained by our payment integrity vendor partners, on either a pre-pay or post-pay basis. Implementation typically takes just 2-3 months.

What results has your solution achieved?

After just its first year in operation, our solution has achieved an average $0.25 PMPM in savings across 9 million covered lives through denials of inappropriate genetic test claims. These are claims that previously were being paid because the claims systems were unable to identify the actual tests or test panels performed in order to apply appropriate policy. Some other key results of our solution include:

Actual annual results across 9M lives