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

IF 2 Q3 HEALTH CARE SCIENCES & SERVICES JMIR Formative Research Pub Date : 2024-11-04 DOI:10.2196/55614
Patrick Sean Sullivan, Robertino M Mera-Giler, Staci Bush, Valentina Shvachko, Eleanor Sarkodie, Daniel O'Farrell, Stephanie Dubose, David Magnuson
{"title":"Claims-Based Algorithm to Identify Pre-Exposure Prophylaxis Indications for Tenofovir Disoproxil Fumarate and Emtricitabine Prescriptions (2012-2014): Validation Study.","authors":"Patrick Sean Sullivan, Robertino M Mera-Giler, Staci Bush, Valentina Shvachko, Eleanor Sarkodie, Daniel O'Farrell, Stephanie Dubose, David Magnuson","doi":"10.2196/55614","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Objective: </strong>This study aimed to validate an algorithm to distinguish the use of TDF/FTC for HIV prevention or infectious disease treatment.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":null,"pages":null},"PeriodicalIF":2.0000,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JMIR Formative Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2196/55614","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0

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.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
美国2012-2014年基于索赔的算法验证,以确定替诺福韦酯/恩曲他滨处方的暴露前预防适应症:通过病历审查验证算法。
背景:为了利用商业药房数据监测用于暴露前预防(PrEP)的替诺福韦酯/恩曲他滨(TDF/FTC)及相关药物作为艾滋病预防药物的使用情况,有必要确定 TDF/FTC 处方是用于 PrEP,还是用于其他临床适应症:目的:验证一种算法,以区分 TDF/FTC 是用于艾滋病预防还是用于传染病治疗:方法:开发了一种算法,用于从大规模行政数据库中识别 TDF/FTC 处方是用于 PrEP 还是用于其他适应症。该算法可识别 TDF/FTC 处方,然后排除具有《国际疾病分类》(ICD)-9 诊断代码、用药或治疗过程等表明非 PrEP 适应症的患者(例如,记录有 HIV 感染、慢性乙型肝炎 (CHB),或将 TDF/FTC 用于暴露后预防 (PEP))。为了进行评估,我们通过临床医生对使用 TDF/FTC 患者的医疗记录进行评估来收集数据,并将临床医生审查确定的评估适应症与算法确定的评估适应症进行比较。然后在一家大型城市社区性健康诊所应用并评估了该算法:结果:PrEP 算法在电子病历数据库中显示出较高的灵敏度和中等程度的特异性(99.6%,49.6%),在城市社区卫生诊所的数据中显示出较高的灵敏度和特异性(99%,87%):PrEP 算法对大多数接受 TDF/FTC 治疗者的 PrEP 适应症进行了分类,其准确性足以用于监测目的。所述方法可作为制定稳健且不断发展的病例定义的基础,用于预防艾滋病的抗逆转录病毒处方:临床试验:无要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
JMIR Formative Research
JMIR Formative Research Medicine-Medicine (miscellaneous)
CiteScore
2.70
自引率
9.10%
发文量
579
审稿时长
12 weeks
期刊最新文献
Insights From the Development of a Dynamic Consent Platform for the Australians Together Health Initiative (ATHENA) Program: Interview and Survey Study. Remote Patient Monitoring and Digital Therapeutics Enhancing the Continuum of Care in Heart Failure: Nonrandomized Pilot Study. A Deep Learning Model to Predict Breast Implant Texture Types Using Ultrasonography Images: Feasibility Development Study. A Food Intake Estimation System Using an Artificial Intelligence-Based Model for Estimating Leftover Hospital Liquid Food in Clinical Environments: Development and Validation Study. Codesigning a Digital Type 2 Diabetes Risk Communication Tool in Singapore: Qualitative Participatory Action Research Approach.
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1