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Optimizing the control group for evaluating ART outcomes: can outpatient claims data yield a better control group?
PURPOSE: We previously developed a subfertile comparison group with which to compare outcomes of assisted reproductive technology (ART) treatment. In this study, we evaluated whether insurance claims data in the Massachusetts All Payers Claims Database (APCD) defined a more appropriate comparison gr...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8190220/ https://www.ncbi.nlm.nih.gov/pubmed/33606146 http://dx.doi.org/10.1007/s10815-021-02111-6 |
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author | Stern, Judy E. Liu, Chia-Ling Cui, Xiaohui Gopal, Daksha Cabral, Howard J. Coddington, Charles C. Missmer, Stacey A. Hwang, Sunah S. Farland, Leslie V. Dukhovny, Dmitry Diop, Hafsatou |
author_facet | Stern, Judy E. Liu, Chia-Ling Cui, Xiaohui Gopal, Daksha Cabral, Howard J. Coddington, Charles C. Missmer, Stacey A. Hwang, Sunah S. Farland, Leslie V. Dukhovny, Dmitry Diop, Hafsatou |
author_sort | Stern, Judy E. |
collection | PubMed |
description | PURPOSE: We previously developed a subfertile comparison group with which to compare outcomes of assisted reproductive technology (ART) treatment. In this study, we evaluated whether insurance claims data in the Massachusetts All Payers Claims Database (APCD) defined a more appropriate comparison group. METHODS: We used Massachusetts vital records of women who delivered between 2013 and 2017 on whom APCD data were available. ART deliveries were those linked to a national ART database. Deliveries were subfertile if fertility treatment was marked on the birth certificate, had prior hospitalization with ICD code for infertility, or prior fertility treatment. An infertile group included women with an APCD outpatient or inpatient ICD 9/10 infertility code prior to delivery. Fertile deliveries were none of the above. Demographics, health risks, and obstetric outcomes were compared among groups. Multivariable generalized estimating equations were used to calculate adjusted relative risk (aRR) and 95% confidence intervals (CI). RESULTS: There were 70,726 fertile, 4,763 subfertile, 11,970 infertile, and 7,689 ART-treated deliveries. Only 3,297 deliveries were identified as both subfertile and infertile. Both subfertile and infertile were older, and had more education, chronic hypertension, and diabetes than the fertile group and less than the ART-treated group. Prematurity (aRR = 1.15–1.17) and birthweight (aRR = 1.10–1.21) were increased in all groups compared with the fertile group. CONCLUSION: Although the APCD allowed identification of more women than the previously defined subfertile categorization and allowed us to remove previously unidentified infertile women from the fertile group, it is not clear that it offered a clinically significantly improved comparison group. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10815-021-02111-6. |
format | Online Article Text |
id | pubmed-8190220 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-81902202021-06-11 Optimizing the control group for evaluating ART outcomes: can outpatient claims data yield a better control group? Stern, Judy E. Liu, Chia-Ling Cui, Xiaohui Gopal, Daksha Cabral, Howard J. Coddington, Charles C. Missmer, Stacey A. Hwang, Sunah S. Farland, Leslie V. Dukhovny, Dmitry Diop, Hafsatou J Assist Reprod Genet Assisted Reproduction Technologies PURPOSE: We previously developed a subfertile comparison group with which to compare outcomes of assisted reproductive technology (ART) treatment. In this study, we evaluated whether insurance claims data in the Massachusetts All Payers Claims Database (APCD) defined a more appropriate comparison group. METHODS: We used Massachusetts vital records of women who delivered between 2013 and 2017 on whom APCD data were available. ART deliveries were those linked to a national ART database. Deliveries were subfertile if fertility treatment was marked on the birth certificate, had prior hospitalization with ICD code for infertility, or prior fertility treatment. An infertile group included women with an APCD outpatient or inpatient ICD 9/10 infertility code prior to delivery. Fertile deliveries were none of the above. Demographics, health risks, and obstetric outcomes were compared among groups. Multivariable generalized estimating equations were used to calculate adjusted relative risk (aRR) and 95% confidence intervals (CI). RESULTS: There were 70,726 fertile, 4,763 subfertile, 11,970 infertile, and 7,689 ART-treated deliveries. Only 3,297 deliveries were identified as both subfertile and infertile. Both subfertile and infertile were older, and had more education, chronic hypertension, and diabetes than the fertile group and less than the ART-treated group. Prematurity (aRR = 1.15–1.17) and birthweight (aRR = 1.10–1.21) were increased in all groups compared with the fertile group. CONCLUSION: Although the APCD allowed identification of more women than the previously defined subfertile categorization and allowed us to remove previously unidentified infertile women from the fertile group, it is not clear that it offered a clinically significantly improved comparison group. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10815-021-02111-6. Springer US 2021-02-19 2021-05 /pmc/articles/PMC8190220/ /pubmed/33606146 http://dx.doi.org/10.1007/s10815-021-02111-6 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Assisted Reproduction Technologies Stern, Judy E. Liu, Chia-Ling Cui, Xiaohui Gopal, Daksha Cabral, Howard J. Coddington, Charles C. Missmer, Stacey A. Hwang, Sunah S. Farland, Leslie V. Dukhovny, Dmitry Diop, Hafsatou Optimizing the control group for evaluating ART outcomes: can outpatient claims data yield a better control group? |
title | Optimizing the control group for evaluating ART outcomes: can outpatient claims data yield a better control group? |
title_full | Optimizing the control group for evaluating ART outcomes: can outpatient claims data yield a better control group? |
title_fullStr | Optimizing the control group for evaluating ART outcomes: can outpatient claims data yield a better control group? |
title_full_unstemmed | Optimizing the control group for evaluating ART outcomes: can outpatient claims data yield a better control group? |
title_short | Optimizing the control group for evaluating ART outcomes: can outpatient claims data yield a better control group? |
title_sort | optimizing the control group for evaluating art outcomes: can outpatient claims data yield a better control group? |
topic | Assisted Reproduction Technologies |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8190220/ https://www.ncbi.nlm.nih.gov/pubmed/33606146 http://dx.doi.org/10.1007/s10815-021-02111-6 |
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