External Validation of the Neiman Imaging Comorbidity Index in Medicare, Medicaid, and Private Payer Claims Data.

Casey E Pelzl, Alexandra Drake, Andrew B Rosenkrantz, Elizabeth Y Rula, Eric W Christensen
{"title":"External Validation of the Neiman Imaging Comorbidity Index in Medicare, Medicaid, and Private Payer Claims Data.","authors":"Casey E Pelzl, Alexandra Drake, Andrew B Rosenkrantz, Elizabeth Y Rula, Eric W Christensen","doi":"10.1016/j.jacr.2024.11.007","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>The Neiman Imaging Comorbidity Index (NICI) was developed and validated in a claims dataset encompassing >10 million privately insured beneficiaries, in which it outperformed the commonly used Charlson Comorbidity Index (CCI) in predicting advanced imaging use. This external validation assessed the broader generalizability of NICI for predicting receipt of advanced imaging in nationally representative populations, including patients insured by Medicare, Medicaid, and private payers.</p><p><strong>Methods: </strong>All 2018 to 2019 patient-level claims from the CMS Medicare 5% Research Identifiable File, CMS Medicaid 100% Research Identifiable File, and private insurance (commercial and Medicare Advantage) claims from Inovalon Insights, LLC, were included. Using 2018 comorbidity data, beneficiaries were assigned CCI and NICI. Area under the receiver operator characteristic curves (AUCs) measured index performance predicting advanced imaging in 2019. AUCs for NICI and CCI were compared overall, across age groups, and after adjusting for age and sex.</p><p><strong>Results: </strong>A total of 108,846,549 beneficiaries were included across Medicare (n = 2,536,403), Medicaid (n = 49,685,052), and private insurance (n = 56,625,094) datasets. NICI outperformed CCI in Medicare (AUC: 0.7709, 95 confidence interval [CI]: 0.7702-0.7716 versus AUC: 0.7503, 95% CI: 0.7496-0.7510; P < .001), Medicaid (AUC: 0.6876, 95% CI: 0.6874-0.6878 versus AUC: 0.6798 95% CI: 0.6796-0.6800]; P < .001), and private insurance data (AUC: 0.6658, 95% CI: 0.6656-0.6660 versus AUC: 0.6479, 95% CI: 0.6477-0.6481; P < .001). NICI outperformed CCI in adjusted models and in nearly all age strata across the three cohorts.</p><p><strong>Discussion: </strong>The NICI outperformed CCI in predicting advanced imaging in populations insured by numerous different payers. Validation data support NICI as the preferred index to adjust for patient comorbidities when studying advanced imaging as an outcome, but further investigations are warranted.</p>","PeriodicalId":73968,"journal":{"name":"Journal of the American College of Radiology : JACR","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the American College of Radiology : JACR","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.jacr.2024.11.007","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Objective: The Neiman Imaging Comorbidity Index (NICI) was developed and validated in a claims dataset encompassing >10 million privately insured beneficiaries, in which it outperformed the commonly used Charlson Comorbidity Index (CCI) in predicting advanced imaging use. This external validation assessed the broader generalizability of NICI for predicting receipt of advanced imaging in nationally representative populations, including patients insured by Medicare, Medicaid, and private payers.

Methods: All 2018 to 2019 patient-level claims from the CMS Medicare 5% Research Identifiable File, CMS Medicaid 100% Research Identifiable File, and private insurance (commercial and Medicare Advantage) claims from Inovalon Insights, LLC, were included. Using 2018 comorbidity data, beneficiaries were assigned CCI and NICI. Area under the receiver operator characteristic curves (AUCs) measured index performance predicting advanced imaging in 2019. AUCs for NICI and CCI were compared overall, across age groups, and after adjusting for age and sex.

Results: A total of 108,846,549 beneficiaries were included across Medicare (n = 2,536,403), Medicaid (n = 49,685,052), and private insurance (n = 56,625,094) datasets. NICI outperformed CCI in Medicare (AUC: 0.7709, 95 confidence interval [CI]: 0.7702-0.7716 versus AUC: 0.7503, 95% CI: 0.7496-0.7510; P < .001), Medicaid (AUC: 0.6876, 95% CI: 0.6874-0.6878 versus AUC: 0.6798 95% CI: 0.6796-0.6800]; P < .001), and private insurance data (AUC: 0.6658, 95% CI: 0.6656-0.6660 versus AUC: 0.6479, 95% CI: 0.6477-0.6481; P < .001). NICI outperformed CCI in adjusted models and in nearly all age strata across the three cohorts.

Discussion: The NICI outperformed CCI in predicting advanced imaging in populations insured by numerous different payers. Validation data support NICI as the preferred index to adjust for patient comorbidities when studying advanced imaging as an outcome, but further investigations are warranted.

求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信