Comparative Effectiveness Research Diffusion and Mental Health Care Disparities

描述（由申请方提供）：比较有效性研究（CER）比较了不同治疗的受益和风险。然而，鲜为人知的是，大规模CER实施的影响，设想在2010年平价医疗法案（ACA）的公平在跨种族/族裔群体的医疗保健。确定FDA风险警告对精神药物使用差异的影响提供了一个平台，以了解CER如何影响某些情况下的差异。差异方法通常没有考虑到特定的 关于有效性和安全性的建议和警告。随着ACA的出现和对持续差异的持续关注，差异研究必须继续下去 不断发展，以吸收从CER中吸取的经验教训。 我们利用警告和建议中的时间趋势来了解传播差异，旨在确定可能避免将CER纳入常规实践的负权益后果的政策。具体而言，我们1）跟踪不同种族/民族的青少年中抗抑郁药使用以及青少年和成人中抗精神病药物使用的变化，因为它们受到CER生成的风险警告和警告的影响; 2）评估FDA警告中的特定信息是否影响了以下方面的差异趋势：a）CER生成的证据推荐的治疗（例如，氟西汀的使用和抗精神病药物使用者的代谢筛查）;和B）潜在有害的精神药物使用（例如，奥氮平使用）;以及3）确定HMO注册的提供者特征如何作为通过健康风险警告的CER差异扩散的基础机制。 我们实施医学研究所（IOM）对医疗保健差异的定义，以捕捉随着时间的推移差异的趋势，覆盖与抗抑郁药和抗精神病药物相关的警告和建议的时间表。我们通过将总体药物使用的差异分解为FDA警告中提到的具有特定风险或益处的特定类别的差异来调整IOM方法。如果我们发现种族/民族差异的风险警告和宣传，这表明政策制定者应该把重点放在提高少数民族的CER的吸收。如果我们确定某些供应商和HMO成员影响扩散的差异，这将导致政策制定者的可操作政策的建议，以避免将CER纳入日常实践的负资产后果。

DESCRIPTION (provided by applicant): Comparative Effectiveness Research (CER) compares benefits and risks of different treatments. However, little is known about the impact of large-scale CER implementation as conceived in the 2010 Affordable Care Act (ACA) on equity in health care across racial/ethnic groups. Identifying the influence of FDA risk warnings on disparities in psychotropic drug use provides a platform to understand how CER will influence disparities in certain situations. Disparity methods have typically not taken into account specific recommendations and warnings on effectiveness and safety. With the advent of the ACA and continued concern over persistent disparities, it is imperative that disparities research continues to evolve to incorporate lessons learned from CER. We capitalize upon time trends in warnings and advisories to understand disparities in diffusion with the intention of identifying policies tht might avert the negative equity consequences of incorporating CER into routine practice. Specifically, we 1) Track changes in antidepressant use among youth and antipsychotic drug use among youth and adults by racial/ethnic group as they are influenced by CER-generated risk warnings and advisories; 2) Assess whether specific information in FDA warnings influenced disparity trends in a) treatments recommended by CER-generated evidence (e.g., fluoxetine use and metabolic screening for antipsychotic users); and b) psychotropic drug use that is potentially harmful (e.g., olanzapine use); and 3) Identify how provider characteristics an HMO enrollment act as mechanisms that underlie the differential diffusion of CER via health risk warnings. We implement the Institute of Medicine (IOM) definition of healthcare disparities in order to capture trends in disparities over time, overlaying timelines of warnings and recommendations related to antidepressant and antipsychotic drugs. We adapt IOM methods by decomposing disparities in overall drug use into disparities in specific categories of use mentioned by FDA warnings as carrying particular risk or benefit. If we find racial/ethnic disparities in diffusion of risk warnings and advisories, this suggests policymakers should focus on improving uptake of CER among minorities. If we identify that certain providers and HMO membership influences disparities in diffusion, this will lead to recommendations for policymakers of actionable policies to avert the negative equity consequences of incorporating CER into routine practice.