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

摘要 每年有超过1000万人患上结核病，约有140万人死于 疾病。大约86%的结核病患者生活在中等收入国家，其中很大一部分生活在城市。 为了大幅减轻全球结核病的负担，有必要确保人们迅速得到诊断 并得到了成功治疗。获得医疗服务的地理障碍--例如居住在远离健康的地方 中心--可能导致不良的健康结果。然而，关于地理访问如何实现的知识有限 障碍影响中等收入国家和城市环境中的结核病诊断和治疗结果。卫生设施 通常出现在这些环境中，但结核病患者，他们通常在社会和经济上 处于不利地位的国家在获取这些资源方面面临障碍。我们也缺乏设计和确定干预措施的工具。 这解决了获取障碍，从而改善了结核病的诊断和治疗。这项提案旨在解决 这些知识差距使用了“5A”概念框架，该框架描述了推动健康的五个领域 护理可获得性：可获得性、可及性、住宿性、可负担性、可接受性。以帮助理解如何 地理上的可及性障碍和其他类型的可及性障碍导致结核病诊断的延误，我们将 将结构方程建模和模拟方法应用于基于5A的结核病患者调查数据 框架。帮助项目针对延迟结核病风险最高的社区进行干预 对于确诊和未完成的结核病治疗，我们将创建包含措施的社区级风险评分 关于地理上的可及性以及社会经济和人口普查数据。帮助项目开发 有效的治疗支持干预措施，我们将进行离散选择实验，以确定最佳 一揽子干预措施，旨在解决治疗期间不同类型的准入障碍，评估 不同人口群体的偏好有何不同。这项提议意义重大，因为结果是 将帮助结核病项目确定最有效的干预措施，以改善结核病诊断和 治疗，并将这些干预措施针对最需要的个人和社区。这 这项提议是创新的，因为之前的定量结核病研究没有使用医疗保健服务 概念框架、结构方程建模或联合分析，以了解如何解决访问问题 目标干预的障碍或社区风险分数。从长远来看，这项研究将有助于结核病规划 减少诊断延误和未完成治疗率，从而减轻结核病发病率的全球负担 和死亡率。

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.