Disparities in utilization and delivery outcomes for women with perinatal mood and anxiety disorders (PMAD): groundwork for state policymaking

项目摘要/摘要 这项研究直接回应了NIMHD关于少数民族卫生服务研究的计划公告 健康和健康差距(PAR-20-310)。围产期情绪和焦虑症(PMAD)，包括 分娩前一年和/或分娩后一年的抑郁和/或焦虑是怀孕的常见并发症， 在美国，每四名女性中就有一人受到影响，每年的花费超过150亿美元。PMAD可能会产生负面影响 母亲、婴儿和家庭超过围产期，并具有持久的临床和经济影响。PMAD 治疗可以改善产妇和新生儿的健康状况，但很少使用精神卫生服务。 没有全面的数据来源记录：1)震级，2)预测因素，3)差异的差异 种族和民族、社会经济地位和地理位置在医疗保健利用或产科分娩结果中的作用 在患有PMAD的女性中。几乎没有证据证明社区特征对这些 结果。目前还没有关于如何最好地解决PMAD的国家计划，无论是在总体上还是在高风险亚群内。 使用公共(Medicaid)和私人(Optom)参保的PMAD妇女的数据，州调查数据， 来自围产期心理健康服务和政策专家小组的意见，以及对州孕产妇和 婴儿健康(MIH)和MH政策制定者，我们将：1)确定患者级别的临床特征 与MH和围产期总体利用率以及与分娩相关的结局相关的 诊断为PMAD的妇女，并在国家和州一级建立准确的估计 护理模式和结果的差异，包括MH利用率、总体利用率和 分娩-结局；2)确定社区特征对围产儿的贡献 妊娠风险数据在PMAD患者中的利用和分娩结局 评估监测系统(PRMS)、地区卫生资源文件(AHRF)和国家精神卫生 服务业调查(N-MHSS)；以及3)与专家小组合作制定以证据为基础的 PMAD的政策制定指南，我们将用它来采访国家母婴健康 和心理健康政策官员。利用AIM 1-2的调查结果和专家小组的意见，我们将制定EBP PMAD指南。本指南将为采访国家母婴保健和 PMAD治疗和治疗相对绩效高低州的精神卫生政策官员 有助于解释量化结果、调整建议并协助未来PMAD的成果 制定政策的举措。 鉴于缺乏关于解决PMAD及其相关利用和交付方面的差异的研究 结果，以及管理不善的PMAD对母亲和婴儿造成的高额代际成本，这 创新的大规模调查将为未来的政策制定和临床干预提供证据。我们的 研究结果和政策指导可以解决高成本、高风险人群在结果上的差异。

Project Summary/Abstract This study directly responds to NIMHD Program Announcement for Health Services Research on Minority Health and Health Disparities (PAR-20-310). Perinatal mood and anxiety disorders (PMAD), which include depression and/or anxiety in the year before and/or after delivery, are common complications of pregnancy, affecting up to one in four women, with costs over $15 billion per year in the US. PMAD can negatively affect mothers, babies, and families beyond the perinatal period, and have lasting clinical and economic effects. PMAD treatment can improve maternal and neonatal health outcomes, yet mental health services are rarely used. No comprehensive data source documents the: 1) magnitude, 2) predictors, and 3) variation in disparities by race and ethnicity, socioeconomic status, and geography in healthcare utilization or obstetric delivery outcomes among women with PMAD. Almost no evidence documents the impact of community characteristics on these outcomes. There is no national plan for how best to address PMAD, overall, or within high-risk subgroups. Using data from publicly (Medicaid) and privately (Optum) insured women with PMAD, state survey data, input from a panel of perinatal mental health services and policy experts, and interviews with state maternal and infant health (MIH) and MH policy makers, we will: 1) identify patient-level clinical characteristics associated with MH and overall perinatal utilization and delivery-related outcomes among women with diagnosed PMAD, and establish accurate national and state-level estimates of disparities in care patterns and outcomes, including MH utilization, overall utilization, and delivery-outcomes; 2) determine contributions of community-level characteristics to perinatal utilization and delivery outcomes among women with PMAD using data from Pregnancy Risk Assessment Monitoring System (PRAMS), Area Health Resource File (AHRF), and National Mental Health Services Survey (N-MHSS); and 3) collaborate with an expert panel to develop an evidence-based policymaking guide for PMAD, which we will use to interview state maternal and infant health and mental health policy officials. Using Aim 1-2 findings and expert panel input, we will develop an EBP guide for PMAD. This guide will provide structure for interviews with state maternal and infant health and mental health policy officials from states with high and low relative performance on PMAD treatment and outcomes to help interpret quantitative findings, tailor recommendations, and assist in future PMAD policymaking initiatives. Given the dearth of research on disparities in addressing PMAD and associated utilization and delivery outcomes, and the high, inter-generational costs for mother and baby of ineffectively managed PMAD, this innovative, large-scale investigation will provide evidence for future policymaking and clinical interventions. Our findings and policy guidance could address disparities in outcomes for high cost, high risk subpopulations.