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The landscape of pharmacogenetic testing in a US managed care population
PURPOSE: Little is known about how many insured patients receive pharmacogenetic testing. We describe trends of single-gene pharmacogenetic testing in a US managed care population, and demographic and clinical characteristics of patients who received a test. METHODS: We leveraged a random sample of...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group US
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7332417/ https://www.ncbi.nlm.nih.gov/pubmed/32291400 http://dx.doi.org/10.1038/s41436-020-0788-3 |
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author | Anderson, Heather D. Crooks, Kristy R. Kao, David P. Aquilante, Christina L. |
author_facet | Anderson, Heather D. Crooks, Kristy R. Kao, David P. Aquilante, Christina L. |
author_sort | Anderson, Heather D. |
collection | PubMed |
description | PURPOSE: Little is known about how many insured patients receive pharmacogenetic testing. We describe trends of single-gene pharmacogenetic testing in a US managed care population, and demographic and clinical characteristics of patients who received a test. METHODS: We leveraged a random sample of nearly 11 million patients from a data set of paid medical and pharmacy claims to identify patients with at least one claim indicating receipt of at least one of these single-gene pharmacogenetic tests: CYP2C19, CYP2D6, CYP2C9, VKORC1, UGT1A1, and HLA class 1 typing. RESULTS: From 1 January 2013 to 30 September 2017, 5712 patients received at least one pharmacogenetic test (55% female; mean age = 43 years). The median number of tests per patient was 3 (mean = 2.7, max = 12); 54% were processed through Managed Medicare/Medicaid, while 45% were processed through commercial insurance. The total number of pharmacogenetic tests received more than doubled from 2013 (n = 1955) to 2015 (n = 4192), then decreased slightly in 2016 (n = 3946). The most common test was CYP2C19 (n = 4719), and “long-term (current) use of other medications” was the most common diagnosis. CONCLUSION: Pharmacogenetic testing through patients’ insurance was low, but more than doubled from 2013 to 2016. This study highlights the need to better understand utilization patterns and insurance coverage for pharmacogenetic tests. |
format | Online Article Text |
id | pubmed-7332417 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group US |
record_format | MEDLINE/PubMed |
spelling | pubmed-73324172020-07-10 The landscape of pharmacogenetic testing in a US managed care population Anderson, Heather D. Crooks, Kristy R. Kao, David P. Aquilante, Christina L. Genet Med Article PURPOSE: Little is known about how many insured patients receive pharmacogenetic testing. We describe trends of single-gene pharmacogenetic testing in a US managed care population, and demographic and clinical characteristics of patients who received a test. METHODS: We leveraged a random sample of nearly 11 million patients from a data set of paid medical and pharmacy claims to identify patients with at least one claim indicating receipt of at least one of these single-gene pharmacogenetic tests: CYP2C19, CYP2D6, CYP2C9, VKORC1, UGT1A1, and HLA class 1 typing. RESULTS: From 1 January 2013 to 30 September 2017, 5712 patients received at least one pharmacogenetic test (55% female; mean age = 43 years). The median number of tests per patient was 3 (mean = 2.7, max = 12); 54% were processed through Managed Medicare/Medicaid, while 45% were processed through commercial insurance. The total number of pharmacogenetic tests received more than doubled from 2013 (n = 1955) to 2015 (n = 4192), then decreased slightly in 2016 (n = 3946). The most common test was CYP2C19 (n = 4719), and “long-term (current) use of other medications” was the most common diagnosis. CONCLUSION: Pharmacogenetic testing through patients’ insurance was low, but more than doubled from 2013 to 2016. This study highlights the need to better understand utilization patterns and insurance coverage for pharmacogenetic tests. Nature Publishing Group US 2020-04-15 2020 /pmc/articles/PMC7332417/ /pubmed/32291400 http://dx.doi.org/10.1038/s41436-020-0788-3 Text en © American College of Medical Genetics and Genomics 2020 Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, and provide a link to the Creative Commons license. You do not have permission under this license to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/. |
spellingShingle | Article Anderson, Heather D. Crooks, Kristy R. Kao, David P. Aquilante, Christina L. The landscape of pharmacogenetic testing in a US managed care population |
title | The landscape of pharmacogenetic testing in a US managed care population |
title_full | The landscape of pharmacogenetic testing in a US managed care population |
title_fullStr | The landscape of pharmacogenetic testing in a US managed care population |
title_full_unstemmed | The landscape of pharmacogenetic testing in a US managed care population |
title_short | The landscape of pharmacogenetic testing in a US managed care population |
title_sort | landscape of pharmacogenetic testing in a us managed care population |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7332417/ https://www.ncbi.nlm.nih.gov/pubmed/32291400 http://dx.doi.org/10.1038/s41436-020-0788-3 |
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