Understanding and addressing geographic barriers to accessing TB services in a high-burden urban setting

了解并解决在高负担城市环境中获得结核病服务的地理障碍

• 批准号: 10657154
• 负责人: Helen E. Jenkins
• 金额: $ 60.34万
• 依托单位: BOSTON UNIVERSITY MEDICAL CAMPUS
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-02-01 至 2028-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10657154
• 关键词: Address; Affect; Area; Award; Catchment Area; Cause of Death; Censuses; Characteristics; Cities; Communicable Diseases; Communities; Country; Data; Diagnosis; Diagnostic; Diagnostic Services; Disease; Employment Status; Equation; Evidence based treatment; Face; Geography; Goals; Health; Health Services Accessibility; Health care facility; Incidence; Income; Individual; Intervention; Knowledge; Measures; Methods; Modeling; Morbidity - disease rate; National Institute of Allergy and Infectious Disease; Network-based; Outcome; Participant; Patients; Persons; Peru; Research; Research Priority; Risk; Sampling; Services; Surveys; Symptoms; Time; Travel; Treatment outcome; Tuberculosis; Tuberculosis diagnosis; United States National Institutes of Health; Visit; design; economic disparity; economic indicator; effective therapy; experimental study; geographic barrier; health care availability; high risk; improved; innovation; models and simulation; mortality; poor health outcome; preference; prevent; programs; research study; sex; simulation; social disparities; socioeconomics; surveillance data; therapy design; tool; transmission process; tuberculosis diagnostics; tuberculosis treatment; urban setting

SUMMARY Each year, over 10 million people become sick with tuberculosis (TB), and around 1.4 million die from the disease. Around 86% of people with TB live in middle-income countries, with a large proportion living in cities. To substantially decrease the global burden of TB, it is necessary to ensure that people are diagnosed quickly and treated successfully. Geographic barriers to accessing health services – such as living far from a health center – can lead to poor health outcomes. However, there is limited knowledge about how geographic access barriers impact TB diagnosis and treatment outcomes in middle-income country urban settings. Health facilities are generally present in these settings, but people with TB, who are often socially and economically disadvantaged, face barriers in accessing them. We also lack tools for designing and targeting interventions that address access barriers and thus improve TB diagnosis and treatment. This proposal seeks to address these knowledge gaps using the “5 A’s” conceptual framework, which describes five domains that drive health care access: availability, accessibility, accommodation, affordability, acceptability. To help understand how geographic accessibility barriers and other types of access barriers contribute to delayed TB diagnosis, we will apply structural equation modeling and simulation methods to data from TB patient surveys based on the 5 A’s framework. To help programs target interventions to communities that are most at risk for delayed TB diagnosis and incomplete TB treatment, we will create community-level risk scores that incorporate measures of geographic accessibility as well as socioeconomic and demographic census data. To help programs develop effective treatment support interventions, we will conduct a discrete choice experiment to identify optimal packages of interventions aimed at addressing different types of access barriers during treatment, assessing how preferences differ among different demographic groups. This proposal is significant because the results will help TB programs to identify interventions that would be most effective for improving TB diagnosis and treatment, and target these interventions to the individuals and communities that need them most. This proposal is innovative because prior quantitative TB research studies have not used a health care access conceptual framework, structural equation modeling or conjoint analysis to understand how to address access barriers, or community risk scores to target interventions. In the long term, this research will help TB programs reduce delays to diagnosis and incomplete treatment rates, thus reducing the global burden of TB morbidity and mortality.

概括 每年，超过1000万人因结核病（TB）生病，约有140万人死于 疾病。大约有86％的结核病患者居住在中等收入国家，在城市中居住着很大比例。 为了大大减少结核病的全球伯恩，有必要确保迅速诊断的人 并成功地对待。获得卫生服务的地理障碍 - 例如远离健康服务 中心 - 可能导致健康状况不佳。但是，关于如何访问地理的知识有限 障碍会影响中等收入国家城市环境中的结核病诊断和治疗结果。卫生设施 通常存在于这些环境中，但是结核病的人通常在社会和经济上是 处于弱势群体时，面对障碍。我们还缺少设计和定位干预措施的工具 该解决访问障碍，从而改善结核病诊断和治疗。该建议旨在解决 这些知识差距使用“ 5 A”的概念框架，该框架描述了五个驱动健康的领域 护理访问：可用性，可访问性，住宿，可用性，可用性。帮助了解如何 地理可及性障碍和其他类型的访问障碍有助于TB诊断延迟，我们将 根据5 A的结构方程建模和仿真方法将TB患者调查的数据应用于数据 框架。帮助计划针对最有可能延迟结核病风险的社区进行干预措施 诊断和不完整的结核病治疗，我们将创建社区级的风险分数，以纳入措施 地理可及性以及社会经济和人口普查数据。帮助程序发展 有效的治疗支持干预措施，我们将进行离散选择实验以识别最佳 干预措施旨在解决治疗期间不同类型的访问障碍的包装 不同人口组之间的偏好如何不同。该提议很重要，因为结果 将帮助结核病计划确定最有效地改善结核病诊断和最有效的干预措施 治疗，并将这些干预措施针对最需要它们的个人和社区。 提案具有创新性，因为先前的定量结核病研究尚未使用医疗保健 概念框架，结构方程建模或联合分析，以了解如何解决访问 障碍或社区风险得分以目标干预措施。从长远来看，这项研究将帮助结核病计划 减少诊断和不完整治疗率的延迟，从而减少了结核病发病率的全球负担 和死亡率。