Challenges with scale-up of GeneXpert MTB/RIF® in Uganda: a health systems perspective
Challenges with scale-up of GeneXpert MTB/RIF® in Uganda: a health systems perspective
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DOI：
10.1186/s12913-020-4997-x
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发表时间：
2020-03-04
影响因子：
2.8
通讯作者：
Katamba, Achilles
中科院分区：
文献类型：
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作者：
Nalugwa, Talemwa;Shete, Priya B.;Katamba, Achilles
背景：许多高负担国家正在使用轮辐模式扩大GeneXpert (R) MTB/RIF （Xpert）结核病检测。然而，扩大规模对减少结核病的影响有限。我们试图描述乌干达各地基于转诊的Xpert结核病检测实施的变化特征，并确定可能加强或阻止Xpert检测服务高质量实施的卫生系统因素。在2016年11月至2017年5月期间，我们对与15个Xpert测试点之一相关的23个社区卫生中心的定量和定性数据源进行了横断面研究，以评估中心辐射型Xpert测试的卫生系统基础设施。数据来源包括标准化现场评估调查、常规结核病通报数据和现场访问的现场记录。结果：在诊断评估过程的每一步，Xpert的实施都存在挑战，导致测试的总体使用率较低。在符合结核病检测条件的2192名患者中，只有574名（26%）开始检测的患者被转介进行Xpert检测。其中，54例（9.4%）Xpert确诊阳性，不到一半的患者在14天内开始治疗（n = 25,46%）。23个社区卫生中心在支持轮辐系统所需的基础设施方面存在差距，包括缺乏用于痰液检测的冷藏设备（n = 14.61%）和缺乏电话/移动通信（n = 21.91%）。负责运送痰液到专家站点的摩托车骑手每周分别在10个（43%）、9个（39%）和4个（17%）健康中心进行一次、两次或三次旅行。工作人员仅在一个保健中心将Xpert结果记录在结核病实验室登记簿上，并仅在两个保健中心呼叫结果呈阳性的患者。在15个Xpert测试点中，有5个（33%）至少有一个功能不正常的模块。每天测试的中位数为3.57次（IQR 2.06-4.54）， 10个（67%）站点的错误/无效率为0.5%。尽管Xpert设备现在在乌干达广泛分布，但从检测转诊到结果报告和治疗开始的连续体卫生系统因素阻碍了对到周边卫生中心就诊的患者有效实施Xpert检测。对扩大创新技术的支持应包括对通信、协调和卫生系统一体化的支持。
Background Many high burden countries are scaling-up GeneXpert (R) MTB/RIF (Xpert) testing for tuberculosis (TB) using a hub-and-spoke model. However, the effect of scale up on reducing TB has been limited. We sought to characterize variation in implementation of referral-based Xpert TB testing across Uganda, and to identify health system factors that may enhance or prevent high-quality implementation of Xpert testing services. Methods We conducted a cross-sectional study triangulating quantitative and qualitative data sources at 23 community health centers linked to one of 15 Xpert testing sites between November 2016 and May 2017 to assess health systems infrastructure for hub-and-spoke Xpert testing. Data sources included a standardized site assessment survey, routine TB notification data, and field notes from site visits. Results Challenges with Xpert implementation occurred at every step of the diagnostic evaluation process, leading to low overall uptake of testing. Of 2192 patients eligible for TB testing, only 574 (26%) who initiated testing were referred for Xpert testing. Of those, 54 (9.4%) were Xpert confirmed positive just under half initiated treatment within 14 days (n = 25, 46%). Gaps in required infrastructure at 23 community health centers to support the hub-and-spoke system included lack of refrigeration (n = 14, 61%) for sputum testing and lack of telephone/mobile communication (n = 21, 91%). Motorcycle riders responsible for transporting sputum to Xpert sites operated variable with trips once, twice, or three times a week at 10 (43%), nine (39%) and four (17%) health centers, respectively. Staff recorded Xpert results in the TB laboratory register at only one health center and called patients with positive results at only two health centers. Of the 15 Xpert testing sites, five (33%) had at least one non-functioning module. The median number of tests per day was 3.57 (IQR 2.06-4.54), and 10 (67%) sites had error/invalid rates > 5%. Conclusions Although Xpert devices are now widely distributed throughout Uganda, health system factors across the continuum from test referral to results reporting and treatment initiation preclude effective implementation of Xpert testing for patients presenting to peripheral health centers. Support for scale up of innovative technologies should include support for communication, coordination and health systems integration.