HIV Treatment Error Reduction Using a Genotype Database

使用基因型数据库减少 HIV 治疗错误

• 批准号: 6448603
• 负责人: RICHARD M NOVAK
• 金额: $ 30.85万
• 依托单位: UNIVERSITY OF ILLINOIS AT CHICAGO
• 依托单位国家: 美国
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-09-24 至 2003-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6448603
• 关键词: AIDS therapy; antiAIDS agent; automated medical record system; biomedical equipment development; clinical research; evaluation /testing; health service demonstration project; human immunodeficiency virus; human subject; low socioeconomic status; molecular biology information system; outpatient care; patient safety /medical error; pharmacogenetics; urban area; virus genetics

Combination anti-HIV drugs (HAART) have dramatically reduced the morbidity and mortality due to HIV and AIDS in the developed world. A major shortcoming with HAART is the development of drug resistance. Genotypic resistance testing is regularly used in clinical practice, producing clinically useful but complex data. Misinterpreting or overlooking such data can lead to adverse outcomes. The advent of electronic medical records presents an opportunity to better integrate complex genotypic testing data into the management of HIV infection, increasing the safety and effectiveness of HAART. This project will create a prototype for future integration of pharmacogenomic information into the electronic medical record for the purpose of improving patient safety and quality of care using HIV genotype as a model system. This proposal has two aims. First is to design and implement an automated system that will integrate HIV genotypic testing results with corresponding patient medication data within an electronic medical record system in order to reduce antiretroviral prescribing errors and improving antiretroviral drug selection. This will be accomplished by developing an automated process to store genotypic testing data within the electronic medical record, creating and implementing "expert rules" to recognize instances of an incorrect or sub-optimal antiretroviral drug selection in the context of genotypic data, creating a mechanism to alert care providers when the expert rules are triggered, and validating the rules. The second aim is to assess the efficacy and usability of this system in a community-based, Ryan White-funded outpatient setting serving a predominantly urban, minority, and low-income population. Data to be measured and analyzed are the frequency of rules triggered, provider responses to alerts, and clinical outcomes measured by HIV viral load. Clinical outcomes will be statistically analyzed as success or failure by two different definitions of success: viral load of <400 and decrease in log (viral load) of _>0.5. Both analyses will look at correlation of success or failure with the presence or absence of an alert and the provider response to alerts. Analyses will be carried out using Fisher's Exact Test. System usabili b providers will also be assessed qualitatively.

抗HIV药物（HAART）大大降低了由于发达国家的艾滋病毒和艾滋病引起的发病率和死亡率。 HAART的主要缺点是耐药性的发展。基因型耐药性测试定期用于临床实践，可产生临床有用但复杂的数据。误解或忽略此类数据可能会导致不良结果。电子病历的出现为更好地整合了复杂的基因型测试数据与HIV感染的管理，从而提高了HAART的安全性和有效性。该项目将创建一个原型，以将药物基因组信息的未来整合到电子病历中，以改善使用HIV基因型作为模型系统的患者安全和护理质量。该提议有两个目标。首先是设计和实施一个自动化系统，该系统将在电子病历系统中将HIV基因型测试结果与相应的患者药物数据整合在一起，以减少抗逆转录病毒处方错误并改善抗逆转录病毒药物的选择。这将通过开发一个自动化过程来将基因型测试数据存储在电子病历中，创建和实施“专家规则”，以识别基因型数据中不正确或次优的抗逆转录病毒药物选择的实例，并在基因型数据的背景下，在专家规则触发规则时创建一种机制，以使警告提供机制，并触发规则。第二个目的是评估该系统在基于社区的，瑞安白人资助的门诊环境中的功效和可用性，该设置主要为城市，少数群体和低收入人口。要测量和分析的数据是触发规则的频率，提供者对警报的响应以及通过HIV病毒负荷测量的临床结果。临床结果将通过两个不同的成功定义统计地分析为成功或失败：<400的病毒载量和对数（病毒载荷）的减少_> 0.5。两种分析都将考虑成功或失败的相关性与警报的存在和提供者对警报的响应。分析将使用Fisher的精确测试进行。系统USABILI B提供商也将进行定性评估。