医疗保险、医疗补助和私人付款人索赔数据中的内曼影像共病指数的外部验证。

Casey E Pelzl, Alexandra Drake, Andrew B Rosenkrantz, Elizabeth Y Rula, Eric W Christensen
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引用次数: 0

摘要

目的:内曼成像共病指数(NICI)在一个包含1000万私人保险受益人的索赔数据集中开发和验证,其中它在预测高级成像使用方面优于常用的查尔森共病指数(CCI)。该外部验证评估了NICI在全国代表性人群中预测高级影像学接受情况的更广泛的普遍性,包括医疗保险、医疗补助和私人支付者。方法:纳入来自CMS Medicare 5%研究可识别文件、CMS Medicaid 100%研究可识别文件和来自Inovalon Insights, LLC的私人保险(商业和Medicare Advantage)索赔的所有2018年至2019年患者级索赔。使用2018年合并症数据,分配受益人CCI和NICI。接收算子特征曲线下面积(aus)测量指标性能预测2019年先进成像。NICI和CCI的auc进行了总体比较,跨年龄组,并在调整了年龄和性别后。结果:医疗保险(n = 2,536,403)、医疗补助(n = 49,685,052)和私人保险(n = 56,625,094)数据集中共纳入108,846,549名受益人。在Medicare中,NICI优于CCI (AUC: 0.7709, 95可信区间[CI]: 0.7702-0.7716, AUC: 0.7503, 95% CI: 0.7496-0.7510;P < 0.001),医疗补助(AUC: 0.6876, 95% CI: 0.6874-0.6878 vs AUC: 0.6798 (95% CI: 0.6796-0.6800);P < .001)和私人保险数据(AUC: 0.6658, 95% CI: 0.6656-0.6660 vs AUC: 0.6479, 95% CI: 0.6477-0.6481;P < 0.001)。在调整后的模型中,NICI的表现优于CCI,并且在三个队列的几乎所有年龄层中都是如此。讨论:NICI优于CCI在预测由许多不同的支付者投保的人口的高级成像。验证数据支持NICI作为研究晚期影像学结果时调整患者合并症的首选指标,但需要进一步研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
External Validation of the Neiman Imaging Comorbidity Index in Medicare, Medicaid, and Private Payer Claims Data.

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.

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