Adherence Improvement and Measurement- AIM- System. Challenge Topic 10-MH-101

依从性改进和测量 - AIM - 系统。

• 批准号: 7815262
• 负责人: JAMES S KAHN
• 金额: $ 49.94万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2011-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7815262
• 关键词: AIDS/HIV problem; Address; Adherence; Anti-HIV Agents; Anti-Retroviral Agents; Area; Biological Markers; Caring; Cellular Phone; Chronic Disease; Clinical; Complex; Counseling; Data; Development; Diabetes Mellitus; Disease; Disease Progression; Drug Exposure; Education; Employee; Employment; Event; Feedback; Gold; HIV; HIV Infections; Hair; Health; Healthcare; Hypertension; Indium; Information Systems; Information Technology; Intervention; Intervention Trial; Measurement; Measures; Medical; Mental Health; Mental disorders; Methods; Modeling; Monitor; Outcome; Patient Care; Patient Self-Report; Patients; Personal Health Records; Persons; Pharmaceutical Preparations; Pharmacists; Primary Health Care; Process; Provider; Public Health; Randomized Clinical Trials; Randomized Controlled Trials; Registries; Reminder Systems; Research; Resources; Role; Sampling; San Francisco; Self Management; Services; Source; Surveys; System; Technology; Time; Toxic effect; Treatment Efficacy; Treatment Protocols; Trust; United States Agency for Healthcare Research and Quality; Upper arm; Viral Load result; Wireless Technology; Work; base; chronic care model; common treatment; depression; firewall; health information technology; hypercholesterolemia; improved; medication compliance; mortality; novel; pill; public health relevance; response; safety net; treatment adherence

DESCRIPTION (provided by applicant): This application addresses broad Challenge Area (10) Information Technology for Processing Health Care Data for Research and specific Challenge Topic, 10-MH-101: Technologies to improve treatment adherence for mental disorders and HIV/AIDS Persons receiving care in safety-net settings, with complex diseases and chronic conditions often have significant health burdens including complicated treatment regimens, limited access to health information and inadequate health information technology to support their care. Thus, applying the chronic care model (CCM) may improve the care for these patients and applying this model may offer important new research opportunities. Clinical information systems (CIS) are a key element in the CCM and have three important roles: reminder systems; feedback mechanisms; and registries. While CIS have focused on the provider as the recipient of data, we believe that a CIS might just as importantly provide data to patients (the consumers of information and healthcare). The personal health record (PHR) is a recent, increasingly common application acting as a CIS for patients. Patients can use PHRs to receive and understand information and respond to research questions, in essence self-managing their health. Adherence is critically important for patients to achieve the maximal benefits of antiretroviral medications, but an adherence intervention trial must rely on good measures of adherence to assess the efficacy of the intervention. Typical measures used to assess adherence, including self-report, pill counts and medication event monitoring systems, are limited, and a independent "biomarker" of drug adherence would be useful. There is no gold standard or even optimal method for the assessment of drug exposure; however, our group has recently shown that the strongest independent predictor for virologic response is hair concentrations of the anchor antiretroviral medication. Hair concentrations were stronger predictors of response than self-reported adherence. In this project, we will work directly with underserved patients in a safety-net setting to conduct a randomized clinical trial of standard-of-care adherence counseling versus a novel adherence intervention embedded in an existing PHR that uses cellular phone short message service (SMS) reminders and patient responses to the reminders. We will compare adherence rates in both arms as assessed by antiretroviral medication concentrations in hair samples and self-report; clinical outcomes will also be compared in the two arms. The project will examine medication adherence for antiretroviral medications and treatments of common conditions such as depression, hypertension, diabetes and hypercholesterolemia. Our hypotheses are that persons receiving private and individualized automated reminders for medication adherence from trusted personal health records (the self-management intervention) will have improved rates of adherence, contributing to better clinical outcomes. PUBLIC HEALTH RELEVANCE: Primary care for persons in the safety net setting and specifically for persons with HIV infection relies on complex sources of information. There are now thirty-one approved anti-HIV agents from five classes of medications, and these medications substantially reduce mortality and disease progression but have significant toxicities. Our project will develop an application to promote medication adherence using wireless technology. Specifically the project will examine the medication adherence for antiretroviral medications and common medical and mental health conditions such as depression, hypertension, diabetes and hypercholesterolemia.

描述（由申请人提供）：本申请解决了广泛的挑战领域（10）用于处理研究和特定挑战主题的医疗保健数据的信息技术，10-MH-101：在安全网环境中接受护理的患有复杂疾病和慢性病的人往往有沉重的健康负担，包括复杂的治疗方案，获得保健信息的机会有限，保健信息技术不足以支持他们的护理。因此，应用慢性病护理模式（CCM）可以改善这些患者的护理，应用这种模式可以提供重要的新的研究机会。临床信息系统（CIS）是CCM的关键要素，具有三个重要作用：提醒系统;反馈机制;和登记。虽然CIS专注于将提供者作为数据的接收者，但我们认为CIS可能同样重要地向患者（信息和医疗保健的消费者）提供数据。个人健康记录（PHR）是一个最近，越来越常见的应用程序作为一个CIS的病人。患者可以使用PHR接收和理解信息，并回答研究问题，本质上是自我管理他们的健康。依从性对于患者实现抗逆转录病毒药物的最大益处至关重要，但依从性干预试验必须依赖于良好的依从性措施来评估干预的有效性。用于评估依从性的典型措施，包括自我报告，药丸计数和药物事件监测系统，是有限的，一个独立的药物依从性的“生物标志物”将是有用的。没有金标准，甚至是最佳的方法来评估药物暴露;然而，我们的小组最近表明，最强的独立预测病毒学反应是头发浓度的锚抗逆转录病毒药物。头发浓度比自我报告的依从性更强的预测反应。在这个项目中，我们将直接与安全网环境中服务不足的患者合作，进行一项随机临床试验，比较标准护理依从性咨询与嵌入现有PHR中的新型依从性干预，该PHR使用手机短信服务（SMS）提醒和患者对提醒的反应。我们将通过头发样本中抗逆转录病毒药物浓度和自我报告来比较两组的依从率;还将比较两组的临床结局。该项目将检查抗逆转录病毒药物和抑郁症、高血压、糖尿病和高胆固醇血症等常见疾病治疗的服药依从性。我们的假设是，从可信的个人健康记录（自我管理干预）中接收私人和个性化的药物依从性自动提醒的人将提高依从率，有助于更好的临床结果。 公共卫生相关性：安全网中的人，特别是艾滋病毒感染者的初级保健依赖于复杂的信息来源。现在有来自五类药物的31种批准的抗HIV药物，这些药物大大降低了死亡率和疾病进展，但具有显著的毒性。我们的项目将开发一个应用程序，以促进使用无线技术的药物依从性。具体而言，该项目将检查抗逆转录病毒药物的服药依从性以及抑郁症、高血压、糖尿病和高胆固醇血症等常见医疗和心理健康状况。