Mitigating effects of telehealth uptake on disparities in maternal care access, quality, outcomes, and expenditures during the COVID-19 pandemic

减轻 COVID-19 大流行期间远程医疗的采用对孕产妇护理获取、质量、结果和支出差异的影响

• 批准号: 10523364
• 负责人: Peiyin Hung
• 金额: $ 61.28万
• 依托单位: UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-15 至 2027-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10523364
• 关键词: Address; Adopted; Advocate; American; Bayesian Analysis; Big Data; Birth; Black Populations; Black race; COVID-19; COVID-19 impact; COVID-19 mortality; COVID-19 pandemic; COVID-19 pandemic effects; Caring; Clinical; Communication; Community Surveys; Complement; Coronavirus; Cost Savings; Costs and Benefits; Data; Data Reporting; Databases; Death Certificates; Death Rate; Development; Discipline of obstetrics; Economics; Electronic Health Record; Electronic Mail; Epidemiologist; Ethnic Origin; Evidence based practice; Expenditure; Financial Hardship; Florida; Fright; Future; Geography; Goals; Health; Health Insurance; Health Policy; Health Services Accessibility; Healthcare Systems; Hispanic; Hispanic Populations; Hybrids; Income; Infant Health; Internet; Interruption; Location; Machine Learning; Maternal Health; Maternal Health Services; Measures; Medicaid; Methods; Minority; Minority Women; Outcome; Patient Self-Report; Patients; Perinatal; Persons; Policies; Population; Predisposition; Pregnant Women; Provider; Psychologist; Psychosocial Stress; Quality of Care; Race; Regulation; Relaxation; Research; Research Personnel; Resources; Role; Rural; Rural Community; Rural Health; Rural Hospitals; Rural Minority; Rural Population; SARS-CoV-2 infection; Security; Services; Site; South Carolina; Statutes and Laws; Testing; Transportation; Travel; Unemployment; United States; Urban Population; Visual; Woman; asynchronous encounter; behavioral health; clinical decision support; clinical decision-making; cohort; coronavirus disease; cost; data harmonization; data modeling; data sharing; disparity reduction; experience; gaps in access; health care economics; health care quality; health disparity; infant outcome; infection risk; innovation; maternal outcome; models and simulation; multidisciplinary; pandemic disease; population based; postpartum care; pregnant; prenatal; public health emergency; racial and ethnic; racial and ethnic disparities; remote patient monitoring; scale up; simulation; social; synchronous contact; telehealth; transportation access; trend; uptake; urban residence; waiver; women of color

Project Summary The Coronavirus disease 2019 (COVID-19) pandemic has caused significant social, healthcare, and economic devastation in the United States (US), potentially exacerbating the maternal health disparities facing rural women and women of color. Telehealth represents a promising opportunity to reducing disparities in maternal health access, quality, and outcomes, given its substantial range of opportunities, including audiovisual synchronous and asynchronous encounters between patients and providers, remote patient monitoring, facilitating visual communication of evidence-based practice, and supporting clinical decision-making. Yet, multilevel barriers might hinder some underserved women from fully benefiting from telehealth. Expanded federal and state-level telehealth coverage through the Coronavirus Aid, Relief, and Economic Security (CARES) Act and state policies may be mitigating the detrimental effects of this unprecedented pandemic by reducing gaps in access to telehealth and quality maternity care. Although self-reported data indicated abrupt increases in telehealth uptake during the pandemic, limited real-world data are available regarding the role of perinatal telehealth uptake on the pandemic’s effects and the role of state level policy in telehealth adaptation during COVID-19. This longitudinal, real-world data study will use recurring national electronic health records (EHR) data [National COVID Cohort Collaborative (N3C)] and integrated statewide population-based data in South Carolina and Florida which complement the overrepresentation of urban populations in N3C. With multiple innovative approaches using common data modeling, multi-level imputation for missingness, and Bayesian statistics simulation methods, this study aims to: 1) investigate the impact of the COVID-19 pandemic on maternal care access, quality, and maternal and birth outcomes by maternal race/ethnicity and rural/urban residence; 2) examine whether perinatal telehealth uptake mitigates the pandemic's effects on disparities in maternal care access, quality, and outcomes by maternal race/ethnicity and rural/urban residence; and 3) assess how state-level telehealth policies (relaxation for originating sites, reimbursements for store-and- forward services, remote patient monitoring, and provider expansion) – relate to perinatal telehealth uptake by race-ethnicity and rural/urban residence. We will also 4) develop a stochastic simulation model to predict long-term changes in maternal care access, quality, outcomes, and expenditures of maternity care, with and without each respective state telehealth policy. Our overarching goal is to advance the understanding of the three-way intersections among the COVID-19 pandemic, state telehealth policy, and perinatal telehealth uptake on health disparities facing vulnerable maternal populations – rural and racial/ethnic minority women. We have formed a multidisciplinary team of investigators, including maternal health services researchers, health policy analysts, telehealth experts, senior clinical researchers, perinatal epidemiologists, rural health advocates, health psychologist, big data analysts, and machine learning experts to conduct this study.

项目摘要 2019年冠状病毒病（COVID-19）大流行引起了巨大的社会，医疗保健和经济 在美国（美国）的破坏，可能加剧农村面临的物物健康分布 有色妇女。远程医疗是减少产妇分配的有希望的机会 鉴于其大量机会，包括视听 患者与提供者之间的同步和异步相遇，远程患者监测， 促进基于证据的实践的视觉交流，并支持临床决策。然而， 多层障碍可能会阻碍一些服务不足的妇女从远程医疗中完全受益。扩展 通过冠状病毒援助，救济和经济安全，联邦和州级远程医疗覆盖范围 （Cares）法案和国家政策可能正在减轻这种前所未有的大流行的有害影响 减少获得远程医疗和优质产妇护理的差距。尽管自我报告的数据表明突然 大流行期间远程医疗吸收的增加，关于现实世界中的有限数据可用 围产期远程医疗对大流行的影响以及国家一级政策在远程医疗适应中的作用 在Covid-19期间。这项纵向现实世界数据研究将使用经常出现的国家电子健康记录 （EHR）数据[国家共同队列合作（N3C）]和全州范围的基于人群的数据 南卡罗来纳州和佛罗里达州完成了N3C城市人口过多的代表。和 使用常见数据建模，多种遗漏归类的多种创新方法，以及 贝叶斯统计仿真方法，本研究的目的是：1）研究Covid-19的大流行的影响 孕产妇的孕产妇护理访问，质量以及产妇和出生结果 住宅; 2）检查围产期远程医疗摄取是否会减轻大流行对分布的影响 孕产妇的护理访问，质量和成果，孕产妇种族/种族和粗糙/城市居住； 3） 评估州级远程医疗政策如何（用于原始站点的放松，存储的报销 远期服务，远程患者监控和提供者扩展） - 与围产期远程医疗有关 种族种族与农村/城市居住。我们还将4）开发一个随机仿真模型来预测 孕产妇护理的孕产妇护理访问，质量，成果和支出的长期变化，以及 没有每个相对国家远程医疗政策。我们的总体目标是提高对 19009年大流行，国家远程医疗政策和围产期远程医疗摄取的三向交叉路口 关于弱势孕产妇人口面临的健康差异 - 农村和种族/族裔少数民族妇女。我们 已经组成了一个多学科的研究人员，包括Mater Health Services研究人员，健康 政策分析师，远程医疗专家，高级临床研究人员，围产期流行病学家，农村健康倡导者， 健康心理学家，大数据分析师和机器学习专家进行这项研究。