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EXAMINING EVIDENCE IN U.S. PAYER COVERAGE POLICIES FOR MULTI-GENE PANELS AND SEQUENCING TESTS

Published online by Cambridge University Press:  25 October 2017

James D. Chambers
Affiliation:
Center for the Evaluation of Value and Risk in Health, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Tufts University School of Medicinejchambers@tuftsmedicalcenter.org
Cayla J. Saret
Affiliation:
Center for the Evaluation of Value and Risk in Health, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center
Jordan E. Anderson
Affiliation:
Center for the Evaluation of Value and Risk in Health, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center
Patricia A. Deverka
Affiliation:
American Institutes for Research, Department of Research and Evaluation
Michael P. Douglas
Affiliation:
University of California at San Francisco, Department of Clinical Pharmacy
Kathryn A. Phillips
Affiliation:
University of California at San Francisco, Department of Clinical Pharmacy UCSF Philip R. Lee Institute for Health Policy and UCSF Helen Diller Family Comprehensive Cancer Center

Abstract

Objectives: The aim of this study was to examine the evidence payers cited in their coverage policies for multi-gene panels and sequencing tests (panels), and to compare these findings with the evidence payers cited in their coverage policies for other types of medical interventions.

Methods: We used the University of California at San Francisco TRANSPERS Payer Coverage Registry to identify coverage policies for panels issued by five of the largest US private payers. We reviewed each policy and categorized the evidence cited within as: clinical studies, systematic reviews, technology assessments, cost-effectiveness analyses (CEAs), budget impact studies, and clinical guidelines. We compared the evidence cited in these coverage policies for panels with the evidence cited in policies for other intervention types (pharmaceuticals, medical devices, diagnostic tests and imaging, and surgical interventions) as reported in a previous study.

Results: Fifty-five coverage policies for panels were included. On average, payers cited clinical guidelines in 84 percent of their coverage policies (range, 73–100 percent), clinical studies in 69 percent (50–87 percent), technology assessments 47 percent (33–86 percent), systematic reviews or meta-analyses 31 percent (7–71 percent), and CEAs 5 percent (0–7 percent). No payers cited budget impact studies in their policies. Payers less often cited clinical studies, systematic reviews, technology assessments, and CEAs in their coverage policies for panels than in their policies for other intervention types. Payers cited clinical guidelines in a comparable proportion of policies for panels and other technology types.

Conclusions: Payers in our sample less often cited clinical studies and other evidence types in their coverage policies for panels than they did in their coverage policies for other types of medical interventions.

Type
Policies
Copyright
Copyright © Cambridge University Press 2017 

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References

REFERENCES

1. Berg, JS, Khoury, MJ, Evans, JP. Deploying whole genome sequencing in clinical practice and public health: Meeting the challenge one bin at a time. Genet Med. 2011;13:499504.Google Scholar
2. Dotson, WD, Bowen, MS, Kolor, K, Khoury, MJ. Clinical utility of genetic and genomic services: context matters. Genet Med. 2016;18:672674.Google Scholar
3. Obama, President Barack. State of the Union Address. 2015 January 20 [cited 2017 February 28]. https://www.whitehouse.gov/the-press-office/2015/01/30/fact-sheet-president-obama-s-precision-medicine-initiative (accessed February 28, 2017).Google Scholar
4. Consolidated Appropriations Act, 2016, H.R.2029. Public Law No: 114-113. December 18, 2015. https://www.gpo.gov/fdsys/pkg/CPRT-114HPRT98369/pdf/CPRT-114HPRT98369.pdf (accessed June 5, 2017).Google Scholar
5. House Energy & Commerce Committee. H.R.34 - 21st Century Cures Act. Public Law No: 114–255, December 13, 2016. https://www.congress.gov/bill/114th-congress/house-bill/34 (accessed June 5, 2017).Google Scholar
6. Phillips, KA, Trosman, JR, Kelley, RK, et al. Genomic sequencing: Assessing the health care system, policy, and big-data implications. Health Aff (Millwood). 2014;33:12461253.Google Scholar
7. Choi, M, Scholl, UI, Ji, W, et al. Genetic diagnosis by whole exome capture and massively parallel DNA sequencing. Proc Natl Acad Sci U S A. 2009;106:1909619101.CrossRefGoogle ScholarPubMed
8. Dewey, FE, Grove, ME, Pan, C, et al. Clinical interpretation and implications of whole-genome sequencing. JAMA. 2014;311:10351045.Google Scholar
9. Gagan, J, Van Allen, EM. Next-generation sequencing to guide cancer therapy. Genome Med. 2015;7:80.CrossRefGoogle ScholarPubMed
10. Hresko, A, Haga, SB. Insurance coverage policies for personalized medicine. J Pers Med. 2012;2:201216.Google Scholar
11. Graf, MD, Needham, DF, Teed, N, Brown, T. Genetic testing insurance coverage trends: A review of publicly available policies from the largest US payers. J Pers Med. 2013;10.Google Scholar
12. Chakradhar, S. Insurance companies are slow to cover next-generation sequencing. Nat Med. 2015;21:204205.Google Scholar
13. Khoury, MJ, Coates, RJ, Evans, JP. Evidence-based classification of recommendations on use of genomic tests in clinical practice: Dealing with insufficient evidence. Genet Med. 2010;12:680683.Google Scholar
14. Khoury, MJ, Berg, A, Coates, R, et al. The evidence dilemma in genomic medicine. Health Aff (Millwood). 2008;27:16001611.Google Scholar
15. Trosman, JR, Weldon, CB, Kelley, RK, Phillips, KA. Challenges of coverage policy development for next-generation tumor sequencing panels: Experts and payers weigh in. J Natl Compr Canc Netw. 2015;13:311318.Google Scholar
16. Deverka, PA, Dreyfus, JC. Clinical integration of next generation sequencing: coverage and reimbursement challenges. J Law Med Ethics. 2014;42 (Suppl 1):2241.Google Scholar
17. University of California San Francisco Department of Clinical Pharmacy. TRANSPERS Center for Translational and Policy Research on Personalized Medicine. March 2, 2016. http://pharm.ucsf.edu/transpers/node/5471 (accessed February 28, 2017).Google Scholar
18. Atlantic Information Services. Atlantic Information Services' Directory of Health Plans 2015. http://aishealth.com/marketplace/aiss-directory-health-plans (accessed February 28, 2017).Google Scholar
19. Trosman, J, Weldon, C, Douglas, M, et al. Payer coverage of hereditary cancer panels: Barriers, opportunities, and implications for the precision medicine initiative. J Natl Compr Canc Netw. 2017:15:219228.CrossRefGoogle ScholarPubMed
20. Phillips, KA, Deverka, PA, Trosman, JR, et al. Payer coverage policies for multigene tests. Nat Biotechnol. 2017;35 (7):614617.Google Scholar
21. Clain, E, Trosman, JR, Douglas, MP, Weldon, CB, Phillips, KA. Availability and payer coverage of BRCA1/2 tests and gene panels. Nat Biotechnol. 2015;33:900902.Google Scholar
22. Dervan, AP, Deverka, PA, Trosman, JR, et al. Payer decision making for next-generation sequencing-based genetic tests: Insights from cell-free DNA prenatal screening. Genet Med. 2017;19:559567.Google Scholar
23. Chambers, JD, Chenoweth, MD, Neumann, PJ. Mapping US commercial payers' coverage policies for medical interventions. Am J Manag Care. 2016;22:e323–e328Google Scholar
24. Desmond, A, Kurian, AW, Gabree, M, et al. Clinical actionability of multigene panel testing for hereditary breast and ovarian cancer risk assessment. JAMA Oncol. 2015;1:943951.Google Scholar
25. Swisher, EM. Usefulness of multigene testing: Catching the train that's left the station. JAMA Oncol. 2015;1:951952.Google Scholar
26. Wang, G, Beattie, MS, Ponce, NA, Phillips, KA. Eligibility criteria in private and public coverage policies for BRCA genetic testing and genetic counseling. Genet Med. 2011;13:10451050.Google Scholar
27. Messner, DA, Al Naber, J, Koay, P, et al. Barriers to clinical adoption of next generation sequencing: Perspectives of a policy Delphi panel. Appl Transl Genom. 2016;10:1924.Google Scholar
28. Evans, BJ, Burke, W, Jarvik, GP. The FDA and genomic tests–getting regulation right. N Engl J Med. 2015;372:22582264.Google Scholar
29. Deverka, PA, Messner, DA, McCormack, R et al. Generating and evaluating evidence of the clinical utility of molecular diagnostic tests in oncology. Genet Med. 2016;18:780787.Google Scholar
30. Shirts, BH, Jacobson, A, Jarvik, GP, Browning, BL. Large numbers of individuals are required to classify and define risk for rare variants in known cancer risk genes. Genet Med. 2014;16:529534.Google Scholar
31. Centers for Medicare and Medicaid Services (CMS). National Coverage Determination (NCD) for Pharmacogenomic Testing for Warfarin Response (90.1). August 3, 2009. https://www.cms.gov/medicare-coverage-database/details/ncd-details.aspx?NCDId=333&bc=AgAAQAAAAAAA&ncdver=1 (accessed February 28, 2017).Google Scholar
32. Molecular Evidence Development Consortium (MED-C). Molecular Evidence Development Consortium (MED-C). March 2, 2016. https://med-c.org/ (accessed February 28, 2017).Google Scholar
33. Center for Medical Technology Policy. Green Park Collaborative (GPC-USA). March 2, 2016. Available from: http://www.cmtpnet.org/news-room/view/gpc-to-develop-evidence-standards-for-ngs-testing-oncology/ (accessed February 28, 2017).Google Scholar
34. Molecular Diagnostic Program (MolDX®). Palmetto GBA. May 2016. http://palmettogba.com/Palmetto/moldx.Nsf/files/MolDX_Manual.pdf/$File/MolDX_Manual.pdf (accessed February 28, 2017).Google Scholar
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