SUD-t Map: A Big Data Digital Platform to Identify and Characterize SUD Treatment Opportunities to Address Health Disparities

SUD-t 地图：一个大数据数字平台，用于识别和描述 SUD 治疗机会，以解决健康差异

• 批准号: 10594828
• 负责人: Timothy Ken Mackey
• 金额: $ 25.94万
• 依托单位: S-3 RESEARCH, LLC
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-15 至 2024-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10594828
• 关键词: Acceleration; Acute; Address; Affect; Big Data; Big Data Methods; Businesses; COVID-19; COVID-19 impact; COVID-19 pandemic; Caring; Centers for Disease Control and Prevention (U.S.); Cessation of life; Characteristics; Client; Communities; Complex; Country; Custom; Data; Databases; Death Records; Economics; Emergency Situation; Ensure; Equity; Ethnic Origin; Face; Funding Opportunities; Future; Geography; Government Agencies; Health; Health Disparities Research; Health Services Accessibility; Homelessness; Imprisonment; Improve Access; Individual; Intelligence; Internet; Interruption; Investments; Link; Low Income Population; Machine Learning; Maps; Measures; Methods; Minority Groups; National Institute of Drug Abuse; Outcome; Outpatients; Overdose; Personal Satisfaction; Pharmaceutical Preparations; Population; Prevention; Private Sector; Public Health; Race; Reduce health disparities; Reporting; Research; Risk; Risk Factors; Services; Social Conditions; Social Environment; Social support; Socioeconomic Status; Substance Use Disorder; Substance abuse problem; System; Technology; Time; Treatment Cost; United States National Institutes of Health; Work; addiction; commercialization; data mining; data visualization; demographic disparity; design; digital; digital platform; digital technology; digital tool; disability; disorder prevention; disparity elimination; disparity reduction; drug relapse; economic disparity; ethnic minority population; experience; health disparity; health equity; high risk; implementation intervention; improved; innovation; insight; interest; minority health; multimodality; opioid epidemic; opioid use disorder; overdose death; pilot test; population health; predictive modeling; prevention service; public health emergency; racial minority population; response; social; social disparities; social health determinants; social stigma; social vulnerability; substance use treatment; tool; treatment center; treatment services; underserved community

1.a. PROJECT SUMMARY/ABSTRACT The proposed project will address a preeminent public health challenge that is acute and immediate: developing innovative commercial digital solutions to positively affect fundamental risk factors associated with health disparities and social determinants of health (SDOH) experienced by communities afflicted with substance use disorder (SUD). With an alarming 81,000 overdose deaths recorded in the 12 months ending on May 2020, it is clear that the current national opioid epidemic is being accelerated and worsened by the ongoing COVID-19 pandemic. As these dual health emergencies collide, communities that are negatively impacted by health disparities remain disproportionately at higher risk for substance use disorders. At the same time, ensuring sufficient and equitable access to SUD prevention and treatment services remains a significant challenge, and few if any tools exist to provide actionable business and public health intelligence needed by different SUD stakeholders, including government agencies, corporate employers, and technology companies, about where and what types of prevention and treatment services are needed. In response, this project will conceptualize, develop and pilot test a multimodal digital tool that will create a comprehensive nationwide database of SUD treatment facilities, combined with an analytical health disparities data layer that can enable SUD-related intelligence. The tool will generate actionable insights on where SUD treatment capacity is insufficient and in turn reduce health disparities related to improving access to SUD treatment specific to priority minority populations and underserved communities. The project will use technology approaches in big data, predictive modeling, and custom data visualization and has the following project aims: Milestone 1: Use advanced methods of data mining to identify and collate a national SUD treatment facility database that includes specific community and business characteristics of interest; Milestone 2: Join, integrate, and analyze SUD treatment facility data with existing demographic, economic, social, and health disparity-related data to enable identification of communities at highest risk of health-related SUDs including a specific focus on identifying communities with insufficient treatment access; and Milestone 3: Build a web-hosted MVP data visualization solution to enable actionable public health and business intelligence identifying SUD health disparity treatment access risks and target use of the solution for customer segments including government agencies, corporate employers, and technology companies. This is a critical opportunity to directly address health disparities related to SUD by developing an innovative digital tool that can help ensure sufficient access to prevention and treatment services in communities who have the greatest need.

1.。项目总结/文摘