Julia R Trosman1, Michael P Douglas2, Su-Ying Liang3, Christine B Weldon4, Allison W Kurian5, Robin K Kelley6, Kathryn A Phillips7. 1. Center for Translational and Policy Research on Personalized Medicine, University of California at San Francisco, San Francisco, CA, USA; Center for Business Models in Healthcare, Chicago, IL, USA. Electronic address: trosman@centerforbusinessmodels.com. 2. Center for Translational and Policy Research on Personalized Medicine, University of California at San Francisco, San Francisco, CA, USA. 3. Palo Alto Medical Foundation Research Institute, Palo Alto, CA, USA. 4. Center for Translational and Policy Research on Personalized Medicine, University of California at San Francisco, San Francisco, CA, USA; Center for Business Models in Healthcare, Chicago, IL, USA. 5. Departments of Medicine & of Health Research & Policy, Stanford University, Palo Alto, CA, USA. 6. Philip R. Lee Institute for Health Policy, University of California, San Francisco, San Francisco, CA, USA. 7. Center for Translational and Policy Research on Personalized Medicine, University of California at San Francisco, San Francisco, CA, USA; Philip R. Lee Institute for Health Policy, University of California, San Francisco, San Francisco, CA, USA; Helen Diller Family Comprehensive Cancer Center, University of California at San Francisco, San Francisco, CA, USA.
Abstract
OBJECTIVES: To examine the temporal trajectory of insurance coverage for next-generation tumor sequencing (sequencing) by private US payers, describe the characteristics of coverage adopters and nonadopters, and explore adoption trends relative to the Centers for Medicare and Medicaid Services' National Coverage Determination (CMS NCD) for sequencing. METHODS: We identified payers with positive coverage (adopters) or negative coverage (nonadopters) of sequencing on or before April 1, 2019, and abstracted their characteristics including size, membership in the BlueCross BlueShield Association, and whether they used a third-party policy. Using descriptive statistics, payer characteristics were compared between adopters and nonadopters and between pre-NCD and post-NCD adopters. An adoption timeline was constructed. RESULTS: Sixty-nine payers had a sequencing policy. Positive coverage started November 30, 2015, with 1 payer and increased to 33 (48%) as of April 1, 2019. Adopters were less likely to be BlueCross BlueShield members (P < .05) and more likely to use a third-party policy (P < .001). Fifty-eight percent of adopters were small payers. Among adopters, 52% initiated coverage pre-NCD over a 25-month period and 48% post-NCD over 17 months. CONCLUSIONS: We found an increase, but continued variability, in coverage over 3.5 years. Temporal analyses revealed important trends: the possible contribution of the CMS NCD to a faster pace of coverage adoption, the interdependence in coverage timing among BlueCross BlueShield members, the impact of using a third-party policy on coverage timing, and the importance of small payers in early adoption. Our study is a step toward systematic temporal research of coverage for precision medicine, which will inform policy and affordability assessments.
OBJECTIVES: To examine the temporal trajectory of insurance coverage for next-generation tumor sequencing (sequencing) by private US payers, describe the characteristics of coverage adopters and nonadopters, and explore adoption trends relative to the Centers for Medicare and Medicaid Services' National Coverage Determination (CMS NCD) for sequencing. METHODS: We identified payers with positive coverage (adopters) or negative coverage (nonadopters) of sequencing on or before April 1, 2019, and abstracted their characteristics including size, membership in the BlueCross BlueShield Association, and whether they used a third-party policy. Using descriptive statistics, payer characteristics were compared between adopters and nonadopters and between pre-NCD and post-NCD adopters. An adoption timeline was constructed. RESULTS: Sixty-nine payers had a sequencing policy. Positive coverage started November 30, 2015, with 1 payer and increased to 33 (48%) as of April 1, 2019. Adopters were less likely to be BlueCross BlueShield members (P < .05) and more likely to use a third-party policy (P < .001). Fifty-eight percent of adopters were small payers. Among adopters, 52% initiated coverage pre-NCD over a 25-month period and 48% post-NCD over 17 months. CONCLUSIONS: We found an increase, but continued variability, in coverage over 3.5 years. Temporal analyses revealed important trends: the possible contribution of the CMS NCD to a faster pace of coverage adoption, the interdependence in coverage timing among BlueCross BlueShield members, the impact of using a third-party policy on coverage timing, and the importance of small payers in early adoption. Our study is a step toward systematic temporal research of coverage for precision medicine, which will inform policy and affordability assessments.
Authors: Julia R Trosman; Christine B Weldon; Michael P Douglas; Allison W Kurian; R Kate Kelley; Patricia A Deverka; Kathryn A Phillips Journal: J Natl Compr Canc Netw Date: 2017-02-10 Impact factor: 11.908
Authors: Kathryn A Phillips; Julia R Trosman; Robin K Kelley; Mark J Pletcher; Michael P Douglas; Christine B Weldon Journal: Health Aff (Millwood) Date: 2014-07 Impact factor: 6.301
Authors: Al B Benson; Alan P Venook; Mahmoud M Al-Hawary; Lynette Cederquist; Yi-Jen Chen; Kristen K Ciombor; Stacey Cohen; Harry S Cooper; Dustin Deming; Paul F Engstrom; Ignacio Garrido-Laguna; Jean L Grem; Axel Grothey; Howard S Hochster; Sarah Hoffe; Steven Hunt; Ahmed Kamel; Natalie Kirilcuk; Smitha Krishnamurthi; Wells A Messersmith; Jeffrey Meyerhardt; Eric D Miller; Mary F Mulcahy; James D Murphy; Steven Nurkin; Leonard Saltz; Sunil Sharma; David Shibata; John M Skibber; Constantinos T Sofocleous; Elena M Stoffel; Eden Stotsky-Himelfarb; Christopher G Willett; Evan Wuthrick; Kristina M Gregory; Deborah A Freedman-Cass Journal: J Natl Compr Canc Netw Date: 2018-04 Impact factor: 11.908
Authors: Elizabeth Clain; Julia R Trosman; Michael P Douglas; Christine B Weldon; Kathryn A Phillips Journal: Nat Biotechnol Date: 2015-09 Impact factor: 54.908
Authors: Andrew P Dervan; Patricia A Deverka; Julia R Trosman; Christine B Weldon; Michael P Douglas; Kathryn A Phillips Journal: Genet Med Date: 2016-09-22 Impact factor: 8.822
Authors: Christine Y Lu; Stephanie Loomer; Rachel Ceccarelli; Kathleen M Mazor; James Sabin; Ellen Wright Clayton; Geoffrey S Ginsburg; Ann Chen Wu Journal: J Pers Med Date: 2018-05-16
Authors: Michael P Douglas; Stephanie L Parker; Julia R Trosman; Anne M Slavotinek; Kathryn A Phillips Journal: Genet Med Date: 2018-07-12 Impact factor: 8.822
Authors: Kathryn A Phillips; Julia R Trosman; Michael P Douglas; Bruce D Gelb; Bart S Ferket; Lucia A Hindorff; Anne M Slavotinek; Jonathan S Berg; Heidi V Russell; Beth Devine; Veronica Greve; Hadley Stevens Smith Journal: Genet Med Date: 2021-11-30 Impact factor: 8.822
Authors: Daniel M Sheinson; William B Wong; Craig S Meyer; Stella Stergiopoulos; Katherine T Lofgren; Carlos Flores; Devon V Adams; Mark E Fleury Journal: JAMA Netw Open Date: 2021-12-01
Authors: Eleanor O Caplan; William B Wong; Erin Ferries; Rebecca Hulinsky; Vicky T Brown; Kristine Bordenave; Brandon T Suehs Journal: JCO Precis Oncol Date: 2021-05-05