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基于索赔的算法识别替诺福韦酯和恩曲他滨处方的暴露前预防指征(2012-2014 年):验证研究。

Claims-Based Algorithm to Identify Pre-Exposure Prophylaxis Indications for Tenofovir Disoproxil Fumarate and Emtricitabine Prescriptions (2012-2014): Validation Study.

机构信息

Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, United States.

Universidad Espiritu Santo, Guayaquil, Ecuador.

出版信息

JMIR Form Res. 2024 Nov 4;8:e55614. doi: 10.2196/55614.

Abstract

BACKGROUND

To monitor the use of tenofovir disoproxil fumarate and emtricitabine (TDF/FTC) and related medicines for pre-exposure prophylaxis (PrEP) as HIV prevention using commercial pharmacy data, it is necessary to determine whether TDF/FTC prescriptions are used for PrEP or for some other clinical indication.

OBJECTIVE

This study aimed to validate an algorithm to distinguish the use of TDF/FTC for HIV prevention or infectious disease treatment.

METHODS

An algorithm was developed to identify whether TDF/FTC prescriptions were for PrEP or for other indications from large-scale administrative databases. The algorithm identifies TDF/FTC prescriptions and then excludes patients with International Classification of Diseases (ICD)-9 diagnostic codes, medications, or procedures that suggest indications other than for PrEP (eg, documentation of HIV infection, chronic hepatitis B, or use of TDF/FTC for postexposure prophylaxis). For evaluation, we collected data by clinician assessment of medical records for patients with TDF/FTC prescriptions and compared the assessed indication identified by the clinician review with the assessed indication identified by the algorithm. The algorithm was then applied and evaluated in a large, urban, community-based sexual health clinic.

RESULTS

The PrEP algorithm demonstrated high sensitivity and moderate specificity (99.6% and 49.6%) in the electronic medical record database and high sensitivity and specificity (99% and 87%) in data from the urban community health clinic.

CONCLUSIONS

The PrEP algorithm classified the indication for PrEP in most patients treated with TDF/FTC with sufficient accuracy to be useful for surveillance purposes. The methods described can serve as a basis for developing a robust and evolving case definition for antiretroviral prescriptions for HIV prevention purposes.

摘要

背景

为了利用商业药房数据监测替诺福韦二吡呋酯富马酸和恩曲他滨(TDF/FTC)和相关药物在暴露前预防(PrEP)中的使用情况,以作为 HIV 预防措施,有必要确定 TDF/FTC 处方是用于 PrEP 还是用于其他临床指征。

目的

本研究旨在验证一种算法,以区分 TDF/FTC 用于 HIV 预防还是用于传染病治疗。

方法

开发了一种算法,以从大规模行政数据库中识别 TDF/FTC 处方是用于 PrEP 还是用于其他指征。该算法确定 TDF/FTC 处方,然后排除具有国际疾病分类(ICD-9)诊断代码、药物或程序的患者,这些代码或程序表明指征不是 PrEP(例如,记录 HIV 感染、慢性乙型肝炎或 TDF/FTC 用于暴露后预防)。为了评估,我们通过临床医生对 TDF/FTC 处方患者的病历评估来收集数据,并将临床医生审查确定的指征与算法确定的指征进行比较。然后在一家大型城市社区性健康诊所中应用和评估该算法。

结果

PrEP 算法在电子病历数据库中具有高敏感性和中度特异性(99.6%和 49.6%),在城市社区卫生诊所的数据中具有高敏感性和特异性(99%和 87%)。

结论

PrEP 算法在大多数接受 TDF/FTC 治疗的患者中对 PrEP 指征的分类具有足够的准确性,可用于监测目的。所描述的方法可以为开发用于 HIV 预防目的的抗逆转录病毒处方的稳健且不断发展的病例定义提供基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9466/11574499/5bd0bece1f60/formative_v8i1e55614_fig1.jpg

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