Testing the Effectiveness of Individualized Disease Prevention for Middle-Aged Adults

项目摘要/摘要 这项建议旨在帮助50岁的中年人(Y)在知情的情况下做出健康决定。 最有可能促进寿命更长、更健康的护理服务。目前有26个基于证据的 预防或管理中年慢性病的服务，但很难做到所有这些服务。患者需要 有助于更好地了解服务之间的权衡。 为了克服这些障碍，我们目前正在进行R21，以确定预防性服务与 对预期寿命的影响最大，并使患者和提供者共同参与决策。病人 提供商高度重视该框架。我们还在开发概念验证，以访问和打印 结果出现在电子健康记录中。 这项提议有三个目标。首先，我们将采用以前发布的分析模型来衡量 质量调整后的预期寿命与坚持26项主要预防护理服务中的24项有关。结果 将根据患者的年龄和风险因素进行个性化。第二，我们将整合之前开发的一个 通过电子健康记录辅助决策。我们将进行迭代测试，以确保准确性和 有用处。第三，我们将进行一项随机试验，以测试决策辅助对中老年人的有效性。 老年患者在不同初级保健诊所的行为。在临床访问期间，患者和医生将讨论 该决策有助于并参与共同决策，以确定预防保健目标的优先顺序。我们将衡量 干预组与对照组预防性护理利用的变化。 这项建议建立在我们的跨学科团队在临床研究、数学和数学方面的坚实基础上 建模、共享决策和信息技术。成功的干预应该有助于 从根本上改变美国的预防性保健提供，以最大限度地促进健康和预防疾病 中年人口。

Project Summary/Abstract This proposal seeks to help middle-aged adults (aged 50-64 y) make an informed decision about the health care services that are most likely to promote a longer, healthier life. There are currently 26 evidence-based services to prevent or manage chronic disease in middle-age, but it is difficult to follow them all. Patients need help to better understand the tradeoffs between services. To overcome these barriers, we are currently conducting an R21 that identifies the preventive services with the greatest impact on life expectancy, and engages patients and providers in shared decision-making. Patients and providers highly value the framework. We also are developing proof-of-concept to access and print the results in the electronic health record. This proposal has 3 aims. First, we will adapt a previously-published analytic model to measure the gain in quality-adjusted life expectancy associated with adherence to 24 of 26 major preventive care services. Results will be individualized for a patient’s age and risk factors. Second, we will integrate a previously-developed decision aid with the electronic health record. We will conduct iterative testing to ensure accuracy and usefulness. Third, we will conduct a randomized trial to test the effectiveness of the decision aid on middle- aged patient behavior in diverse primary care clinics. During clinical visits, patients and physicians will discuss the decision aid and engage in shared decision making, to prioritize preventive care goals. We will measure the change in preventive care utilization between intervention and control patients. This proposal builds upon our inter-disciplinary team’s strong foundation in clinical research, mathematical modeling, shared decision-making and information technology. A successful intervention should help to fundamentally change preventive care delivery in the United States, to maximize health and prevent illness in the middle-aged population.