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From patients to policy: innovative epidemiology for implementation science

从患者到政策：实施科学的创新流行病学

基本信息

批准号：
8756024
负责人：
Daniel J Westreich
金额：
$ 228万
依托单位：
UNIV OF NORTH CAROLINA CHAPEL HILL
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-09-15 至 2019-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8756024
关键词：
Address Affect Area Caring Complex Data Databases Disease Effectiveness Epidemiologic Methods Epidemiology Etiology Exposure to Goals HIV HIV Seropositivity Health Health Policy Highly Active Antiretroviral Therapy Individual International Intervention Joints Life Style Literature Methods Morbidity - disease rate Myocardial Infarction Observational Study Outcome Patients Plant Roots Policies Population Positioning Attribute Pregnancy Probability Public Health Public Policy Randomized Risk Smoking Smoking Cessation Intervention South Africa Structural Models Time Translating Translations United States Weight Woman Work antiretroviral therapy clinical care high reward high risk hormonal contraception implementation science innovation mortality population based population health public health relevance research study response smoking cessation tool unintended pregnancy uptake

项目摘要

DESCRIPTION (provided by applicant): The overall goal of this proposal is to accelerate the translation of scientific results from observational and experimental studies into public health policy. Epidemiology is at a crossroads. The vast majority of studies of exposure-outcome relationships in observational and randomized settings alike ask questions about exposure effects: questions which relate to individuals, and to lifestyle choices. For example, a study might ask about how smoking cessation affects risk of heart attack in people with HIV - a question relating largely to exposure-disease etiology. Such estimates are useful, but they are only the first step in making effective public policy, which requires the articulation of a specifi health intervention, and issues of the uptake of the intervention and its real world effectiveness. At present, few methods exist for assessing interventional effects in complex longitudinal data with time-varying exposures: the mainstay of modern epidemiology. This proposal aims to develop and apply innovative epidemiologic methods to create policy-ready, actionable epidemiologic results. Specifically, we will develop and extend two of the g-methods: the parametric g-formula, and inverse probability weighted marginal structural models. We will apply these methodological innovations to critical and timely problems within HIV in both domestic and international contexts. First, we will examine smoking-associated morbidity and mortality among HIV-positive individuals in the United States from the national CNICS database, and estimate the impact of specific smoking cessation interventions on all-cause mortality in this population. Second, we will examine the joint effects of hormonal contraception and pregnancy on response to highly active antiretroviral therapy among HIV-positive women in South Africa, and estimate the impact of specific interventions to reduce unintended pregnancy in this population on population health outcomes including response to treatment. The proposed methods work will help to bridge the gaps between epidemiology and implementation science, and will thus have extremely broad application: not only to the critical issues in HIV, but to epidemiology and public health as a whole. The proposed substantive work will fill needed gaps in the HIV literature, and our approach - rooted in the methods we will develop - will be well-positioned to drive public health policy in these areas. Thus, we propose a high-risk, high-reward effort to create methods to move from exposures to interventions and from patients to policy: through clearly communicated and usable methodological innovation, and high-impact substantive applications.

该提案的总体目标是加速将观察和实验研究的科学结果转化为公共卫生政策。流行病学正处于十字路口。绝大多数在观察和随机环境中进行的关于风险-结果关系的研究都提出了关于暴露效应的问题：这些问题与个人和生活方式选择有关。例如，一项研究可能会询问戒烟如何影响艾滋病毒感染者心脏病发作的风险--这一问题主要与艾滋病病因有关。这种估计是有用的，但它们只是制定有效公共政策的第一步，这需要阐明具体的卫生干预措施，以及干预措施的采用及其真实的世界效力的问题。目前，很少有方法存在于复杂的纵向数据随时间变化的暴露评估干预效果：现代流行病学的支柱。该提案旨在开发和应用创新的流行病学方法，以创建政策准备，可操作的流行病学结果。具体来说，我们将开发和扩展两个g方法：参数g公式和逆概率加权边际结构模型。我们将把这些方法创新应用于国内和国际艾滋病毒领域的关键和及时问题。首先，我们将从国家CNICS数据库中检查美国HIV阳性个体与吸烟相关的发病率和死亡率，并估计特定戒烟干预措施对该人群全因死亡率的影响。其次，我们将研究激素避孕和怀孕对南非艾滋病毒阳性妇女对高效抗逆转录病毒治疗反应的联合影响，并估计减少这一人群意外怀孕的具体干预措施对人口健康结果的影响，包括对治疗的反应。拟议的方法工作将有助于弥合流行病学和实施科学之间的差距，因此将有非常广泛的应用：不仅对艾滋病毒的关键问题，但流行病学和公共卫生作为一个整体。拟议的实质性工作将填补艾滋病毒文献中所需的空白，我们的方法-植根于我们将开发的方法-将能够很好地推动这些领域的公共卫生政策。因此，我们提出了一个高风险，高回报的努力，创造方法，从接触到干预措施，从病人到政策：通过明确沟通和可用的方法创新，和高影响力的实质性应用。