The Population-Based Effectiveness in Asthma and Lung Diseases (PEAL) Network

描述(由申请人提供)：哮喘的负担不成比例地落在弱势群体身上，包括种族/少数民族和儿童。加强哮喘和肺部疾病比较有效性研究的临床基础设施将产生很大影响，因为仍然缺乏信息来解决这些优先人群目前的药物选择问题。为了减少哮喘发病率，我们还需要更好地阐明在不同人群中影响哮喘控制药物处方和依从性的因素。具体目标-我们将：(1)通过创建和链接来自州医疗补助人群和四个健康计划人群的标准化数据集，为哮喘和肺部疾病研究建立一个创新的基础设施；(2)比较不同人群中主要哮喘控制方案的实际依从性和有效性；以及(3)进行一项应用方法学研究，比较不同的设计和分析方法，以进行观察性比较有效性研究。研究设计-对于目标1，我们将通过建立来自我们不同人群的广泛的、目前可用的计算机化数据集-Tenncare Medicaid人群和四个HMO研究网络站点，创建一个新的分布式数据网络用于哮喘和肺部疾病的研究。我们将建立在HMORN的虚拟数据仓库和其他成功网络使用的方法的基础上。对于目标2，我们将使用来自索赔、电子医疗记录(EMR)以及对患者和提供者的调查的数据进行队列和嵌套病例对照研究。目的2分析将评估主要控制方案之间的不良哮喘结局和成本的差异，使用倾向分数加权和替代方法来调整混杂的适应症。对于目标3，我们将进行一项方法论研究，比较各种研究设计和统计分析方法的概括性和有效性，并评估收集患者报告数据的好处。冲击力。该项目在其计划中具有创新性，将所有四个重要的数据源-索赔、急诊医生、患者和提供者-以及州医疗补助人口纳入一个新的哮喘和肺部疾病比较有效性研究网络。这一庞大的、多样化的网络将为慢性病和脆弱人群的比较有效性研究创造一个开创性的模型。目前的项目将解决哮喘的关键临床和政策问题。PEAL网络将为未来以人群为基础的哮喘和肺部疾病研究以及优先人群研究奠定关键基础。 公共卫生相关性：项目简介该项目将创建一个新的基础设施，以加快在不同人群中对哮喘和其他肺部疾病的比较有效性研究。我们将形成基于人群的哮喘和肺部疾病有效性(PEAL)网络，从一个州的医疗补助计划和四个健康计划中创建高度详细、标准化、链接的计算机化数据集。我们将对哮喘控制药物进行比较有效性研究，评估依从性等现实因素。该项目具有创新性，因为我们将把索赔、电子病历、患者和提供者数据联系起来，并将与医疗补助计划建立新的联系，将哮喘负担过重的弱势群体包括在内。

DESCRIPTION (provided by applicant): The burden of asthma falls disproportionately on vulnerable groups including racial/ethnic minorities and children. Enhancing the clinical infrastructure for comparative effectiveness research in asthma and lung diseases will have high impact because there is a continuing dearth of information to address current medication choices for these priority populations. To reduce asthma morbidity, we also need to better elucidate the factors that affect prescribing and adherence to asthma controller medications in diverse populations. Specific Aims - We will: (1) Build an innovative infrastructure for research on asthma and lung diseases by creating and linking standardized datasets from a state Medicaid population and four health plan populations; (2) Compare real-world adherence to and effectiveness of the major asthma controller regimens in diverse populations; and (3) Conduct an applied methodologic study that compares different design and analysis approaches for observational comparative effectiveness research. Research Design - For Aim 1, we will create a new distributed data network for research in asthma and lung diseases by building on extensive, currently available computerized datasets from our diverse populations - the TennCare Medicaid population and four HMO Research Network sites. We will build on the HMORN's Virtual Data Warehouse `and approaches used by other successful networks. For Aim 2, we will conduct cohort and nested case-control studies using data from claims, electronic medical records (EMRs), and surveys of patients and providers. Aim 2 analyses will evaluate variations in the rates of adverse asthma outcomes and costs among the major controller regimens, using propensity score weighting and alternative methods to adjust for confounding by indication. For Aim 3, we will conduct a methodologic study that compares the generalizability and validity of various study designs and statistical analysis approaches, and evaluates the benefits of collecting patient-reported data. Impact. This project is innovative in its plan to include all four important data sources - claims, EMRs, patients, and providers - and a state Medicaid population in a new network for comparative effectiveness research on asthma and lung diseases. This large, diverse network will create a seminal model for comparative effectiveness research in chronic diseases and vulnerable populations. The current project will address key clinical and policy questions in asthma. The PEAL Network will lay a critical foundation for future population-based research in asthma and lung diseases, and research with priority populations. PUBLIC HEALTH RELEVANCE: Project Narrative This project will create a new infrastructure to accelerate comparative effectiveness research in asthma and other lung diseases in diverse populations. We will form the Population-Based Effectiveness in Asthma and Lung Diseases (PEAL) Network, creating highly detailed, standardized, linked computerized datasets from a state Medicaid plan and four health plans. We will conduct comparative effectiveness research on asthma controller medications, evaluating adherence and other real-world factors. This project is innovative in that we will link claims, electronic medical record, patient, and provider data, and will build new linkages with a Medicaid plan to include vulnerable groups who are disproportionately burdened by asthma.