#AGBTPH – Patricia Deverka, Payer perspectives on NIPT.

University of North Carolina.

Payer framework for coverage of diagnostic tests.

  • Analytic Validity (CLIA, FDA, Payers)
  • Clinical Validity (FDA, Payers)
  • Clinical Utility. (Payers)

Clinical coverage criteria:  Mostly looking at publications, look at expert opinions, and independent technology assessments.  Have test developers done their own studies?  Other health care organizations.

Key questions: How to evaluate the benefits and risks that analyze many different genes and variants at once?  (And how do you design the tests that get you there?) When evaluating, why are more genes better?  How can they support appropriate clinical integration?

Challenges: What are barriers?  Data sharing, and different payers have different evidentiary standards for assessing clinical utility.

Beyond common trisomies, how do you use the information in the screens?

We need standards to have greater predictability – what is the evidence required to have consistent payer adoption.

Coverage policy study background.  cfDNA screening has been rapidly integrated into clinical practice.  Decision making process has not been systematically examined.

Method, First looked at 5 payers, covering 128Million people!   Second version had 19 payers, covering [180Million?] people.

Some insights into U.S. insurance… Blue Cross/Blue Shield is a dominant player.

Looked into every policy and details.

All private payers cover high risk.  8/19 cover average risk pregnancies.  None cover micro deletions.  One covers sex chromosome aneuploidy.  None require prior authorization from genetic councillor.

10/19 looked at analytic validity, but recognized they have no way to do it indecently.  Lack access to public data and standards to do validation. Lack of FDA regulation.  Majority referenced blue cross/blue shield study.

Most of them emphasized clinical validity.  Rich evidence base for clinical validity.

Payers looking at the same evidence for average risk pregnancies came to different results – 8 consider it medically necessary, the rest don’t.

Modelled data is enough for determining that outcomes are worth it.  Models may not have included test failures.

Clinical validity: constantly defined as “change in health outcomes.”

Conclusions:

  • For non-invasive prenatal testing, vast majorities are using standard analytic framework for understanding tests.
  • they are evaluating evidence for each chromosome abnormality separately, even if bundled.
  • payers cite same evidence, but can come to different conclusions.
  • Most payers couldn’t independently asses validity.

Medicare covers almost half of births in U.S.  Hard to interpret policy.

Blue Cross Blue Shield say that different [chapters?] make decisions separately, but there is dependence between them, judging by the data.

Summary:

  • cfDNA screening adopted rapidly in certain indications
  • Payers used standard framework for making decisions.
  • Genetic counselling a foreseeable bottleneck.

 

 

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