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

总结 每年，超过1000万人患有结核病（TB），约140万人死于结核病。 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。 为了大幅度降低结核病的全球负担，有必要确保人们得到快速诊断 并成功治疗。获得卫生服务的地理障碍-例如居住在远离卫生设施的地方 中心-可能导致不良的健康结果。然而，关于地理访问如何 在中等收入国家的城市环境中，结核病诊断和治疗的障碍影响结核病的诊断和治疗结果。保健设施 通常存在于这些环境中，但结核病患者，他们通常在社会和经济上 弱势群体在获得这些服务方面面临障碍。我们还缺乏设计和针对性干预措施的工具 解决获取障碍，从而改善结核病诊断和治疗。该提案旨在解决 这些知识差距使用“5A”的概念框架，其中描述了五个领域，推动健康 获得护理：可获得性、可获得性、便利性、可负担性、可接受性。为了帮助理解 地理可及性障碍和其他类型的可及性障碍导致结核病诊断延迟，我们将 应用结构方程建模和模拟方法，从基于5A的结核病患者调查数据中获得 框架.帮助项目针对延迟性结核病风险最大的社区进行干预 诊断和不完全的结核病治疗，我们将创建社区一级的风险评分， 地理可达性以及社会经济和人口普查数据。帮助项目发展 有效的治疗支持干预措施，我们将进行离散选择实验，以确定最佳的 旨在解决治疗过程中不同类型的获取障碍的一揽子干预措施，评估 不同人群的偏好有何不同这一建议意义重大，因为其结果 将帮助结核病规划确定对改善结核病诊断最有效的干预措施， 这些干预措施针对最需要的个人和社区。这 该建议是创新的，因为以前的定量结核病研究没有使用卫生保健通道 概念框架、结构方程模型或联合分析，以了解如何解决获取问题 障碍，或社区风险评分，以目标干预措施。从长远来看，这项研究将有助于结核病项目 减少延误诊断和不完全治疗率，从而减轻结核病发病率的全球负担 and mortality.

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.