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ICD-10-CM合并症综合评分的适应性与验证

Adaptation and Validation of the Combined Comorbidity Score for ICD-10-CM.

作者信息

Sun Jenny W, Rogers James R, Her Qoua, Welch Emily C, Panozzo Catherine A, Toh Sengwee, Gagne Joshua J

机构信息

*Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School†Department of Epidemiology, Harvard T.H. Chan School of Public Health‡Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA.

出版信息

Med Care. 2017 Dec;55(12):1046-1051. doi: 10.1097/MLR.0000000000000824.

Abstract

BACKGROUND

The combined comorbidity score, which merges the Charlson and Elixhauser comorbidity indices, uses the ninth revision of the International Classification of Diseases, Clinical Modification (ICD-9-CM). In October 2015, the United States adopted the 10th revision (ICD-10-CM).

OBJECTIVE

The objective of this study is to examine different coding algorithms for the ICD-10-CM combined comorbidity score and compare their performance to the original ICD-9-CM score.

METHODS

Four ICD-10-CM coding algorithms were defined: 2 using General Equivalence Mappings (GEMs), one based on ICD-10-CA (Canadian modification) codes for Charlson and Elixhauser measures, and one including codes from all 3 algorithms. We used claims data from the Clinfomatics Data Mart to identify 2 cohorts. The ICD-10-CM cohort comprised patients who had a hospitalization between January 1, 2016 and March 1, 2016. The ICD-9-CM cohort comprised patients who had a hospitalization between January 1, 2015 and March 1, 2015. We used logistic regression models to predict 30-day hospital readmission for the original score in the ICD-9-CM cohort and for each ICD-10-CM algorithm in the ICD-10-CM cohort.

RESULTS

Distributions of each version of the score were similar. The algorithm based on ICD-10-CA codes [c-statistic, 0.646; 95% confidence interval (CI), 0.640-0.653] had the most similar discrimination for readmission to the ICD-9-CM version (c, 0.646; 95% CI, 0.639-0.653), but combining all identified ICD-10-CM codes had the highest c-statistic (c, 0.651; 95% CI, 0.644-0.657).

CONCLUSIONS

We propose an ICD-10-CM version of the combined comorbidity score that includes codes identified by ICD-10-CA and GEMs. Compared with the original score, it has similar performance in predicting readmission in a population of United States commercially insured individuals.

摘要

背景

合并共病评分融合了查尔森共病指数和埃利克斯豪泽共病指数,采用《国际疾病分类,临床修订版第九版》(ICD - 9 - CM)。2015年10月,美国采用了第十版(ICD - 10 - CM)。

目的

本研究的目的是检验ICD - 10 - CM合并共病评分的不同编码算法,并将其性能与原始ICD - 9 - CM评分进行比较。

方法

定义了四种ICD - 10 - CM编码算法:两种使用通用等效映射(GEMs),一种基于用于查尔森和埃利克斯豪泽测量的ICD - 10 - CA(加拿大修订版)编码,还有一种包含来自所有三种算法的编码。我们使用来自临床信息学数据集市的索赔数据来确定两个队列。ICD - 10 - CM队列包括2016年1月1日至2016年3月1日期间住院的患者。ICD - 9 - CM队列包括2015年1月1日至2015年3月1日期间住院的患者。我们使用逻辑回归模型来预测ICD - 9 - CM队列中原始评分以及ICD - 10 - CM队列中每种ICD - 10 - CM算法的30天再入院情况。

结果

每个版本评分的分布相似。基于ICD - 10 - CA编码的算法(c统计量,0.646;95%置信区间[CI],0.640 - 0.653)在再入院判别方面与ICD - 9 - CM版本最为相似(c,0.646;95% CI,0.639 - 0.653),但合并所有识别出的ICD - 10 - CM编码具有最高的c统计量(c,0.651;95% CI,0.644 - 0.657)。

结论

我们提出了一种ICD - 10 - CM版本的合并共病评分,其中包括由ICD - 10 - CA和GEMs识别出的编码。与原始评分相比,它在预测美国商业保险人群的再入院情况方面具有相似的性能。

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