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利用国家退伍军人事务部健康信息系统开发并验证一个“虚拟”队列。

Development and verification of a "virtual" cohort using the National VA Health Information System.

作者信息

Fultz Shawn L, Skanderson Melissa, Mole Larry A, Gandhi Neel, Bryant Kendall, Crystal Stephen, Justice Amy C

机构信息

VA Connecticut Health Care System, West Haven, CT 06516, USA.

出版信息

Med Care. 2006 Aug;44(8 Suppl 2):S25-30. doi: 10.1097/01.mlr.0000223670.00890.74.

Abstract

BACKGROUND

The VA's integrated electronic medical record makes it possible to create a "virtual" cohort of veterans with and without HIV infection to monitor trends in utilization, toxicity, and outcomes.

OBJECTIVES

We sought to develop a virtual cohort of HIV-infected veterans by adapting an existing algorithm, verifying this algorithm against independent clinical data, and finally identifying demographically-similar HIV-uninfected comparators.

RESEARCH DESIGN

Subjects were identified from VA administrative data in fiscal years 1998-2003 using a modified existing algorithm, then linked with Immunology Case Registry (ICR, the VA's HIV registry) and Pharmacy Benefits Management (centralized database of outpatient prescriptions) to verify accuracy of identification. The algorithm was modified to maximize positive predictive value (PPV) against ICR. Finally, 2 HIV-uninfected comparators were matched to each HIV-infected subject.

RESULTS

Using a single HIV code, 30,564 subjects were identified (positive predictive value 69%). Modification to require >1 outpatient or 1 inpatient code improved the positive predictive value to 88%. The lack of confirmatory laboratory and pharmacy data for the majority of subjects with a single outpatient code also supported this change. Of subjects identified with the modified algorithm, 89% had confirmatory evidence. When the modified algorithm was applied to fiscal years 1997-2004, 33,420 HIV-infected subjects were identified. Two HIV-uninfected comparators were matched to each subject for an overall cohort sample of 100,260.

CONCLUSIONS

In the HAART era, HIV-related codes are sufficient for identifying HIV-infected subjects from administrative data when patients with a single outpatient code are excluded. A large cohort of HIV-infected subjects and matched comparators can be identified from existing VA administrative datasets.

摘要

背景

美国退伍军人事务部(VA)的综合电子病历使得创建一个包含感染和未感染艾滋病毒退伍军人的“虚拟”队列成为可能,以便监测医疗服务利用情况、毒性和治疗结果的趋势。

目的

我们试图通过改编现有算法来建立一个感染艾滋病毒退伍军人的虚拟队列,根据独立临床数据验证该算法,最后确定在人口统计学上相似的未感染艾滋病毒的对照者。

研究设计

使用改良的现有算法从1998 - 2003财政年度的VA行政数据中识别受试者,然后与免疫学病例登记处(ICR,VA的艾滋病毒登记处)和药房福利管理处(门诊处方集中数据库)相链接,以验证识别的准确性。对该算法进行修改以最大化针对ICR的阳性预测值(PPV)。最后,为每个感染艾滋病毒的受试者匹配2名未感染艾滋病毒的对照者。

结果

使用单一艾滋病毒代码,识别出30564名受试者(阳性预测值69%)。修改为要求有>1个门诊或1个住院代码后,阳性预测值提高到88%。大多数仅有一个门诊代码的受试者缺乏确证实验室和药房数据这一情况也支持了这一改变。使用改良算法识别出的受试者中,89%有确证证据。当将改良算法应用于1997 - 2004财政年度时,识别出33420名感染艾滋病毒的受试者。为每个受试者匹配2名未感染艾滋病毒的对照者,整个队列样本达100260人。

结论

在高效抗逆转录病毒治疗(HAART)时代,当排除仅有一个门诊代码的患者时,与艾滋病毒相关的代码足以从行政数据中识别出感染艾滋病毒的受试者。可以从现有的VA行政数据集中识别出一大群感染艾滋病毒的受试者以及匹配的对照者。

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