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患者和医疗保健系统特征与台湾结核病病例的延迟治疗相关。

Patient and health care system characteristics are associated with delayed treatment of tuberculosis cases in Taiwan.

机构信息

Center for Applied Artificial Intelligence Research, Soochow University, Taipei, Taiwan.

Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan.

出版信息

BMC Health Serv Res. 2019 Nov 19;19(1):846. doi: 10.1186/s12913-019-4702-0.

DOI:10.1186/s12913-019-4702-0
PMID:31744504
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6862853/
Abstract

BACKGROUND

The decline of the incidence rate of tuberculosis in Taiwan has been partly attributed to the launch of the directly observed therapy short course (DOTS) program in 2006, followed by the DOTS-Plus in 2007. However, with the phasing out of the specialized tuberculosis care system and the declining incidence, clinical workers in Taiwan might become less familiar with the presentation of tuberculosis. Complementing the patient-pathway analysis with health system delay estimates, the objective of this study is twofold: to estimate the alignment between patient care initiation and the availability of prompt diagnostic and treatment services, and to identify the risk factors of delayed tuberculosis treatment.

METHODS

The study population included all Taiwanese patients with incident tuberculosis in 2013. We (1) identified 11,507 incident tuberculosis patients from the 2013 National TB Registry, and (2) linked 10,932 Taiwanese from the registry to the 2012-2013 National Health Insurance Research Database. We assessed patient's care-seeking pathways and associated the determinants of health system delay in a Cox model.

RESULTS

The overall health system delay was 46 days. We found that 20.5 and 3.5% of 10,932 tuberculosis patients were diagnosed and treated respectively at the initial visit to seek care for TB-related symptoms. Risk factors related to the prolonged health system delay included female gender (adjusted HR = 0.921, 95% CI: 0.884, 0.960), age > =65 years (adjusted HR = 0.720, 95% CI: 0.692, 0.750), non-severe (chest X-ray without cavities) (adjusted HR =0.721, 95% CI 0.683-0.760), chronic respiratory diseases (adjusted HR = 0.544, 95% CI: 0.522, 0.566), living in long-term care facilities (adjusted HR = 0.580, 95% CI: 0.525,0.640), an initial visit at a primary care clinic (adjusted HR = 0.588, 95% CI: 0.565, 0.612), and living in southern Taiwan (adjusted HR = 0.887, 95% CI: 0.798, 0.987).

CONCLUSIONS

The low access to TB diagnostic and treatment services at the initial visit and the prolonged health system delay indicate inefficiency in the health care system. Strengthening training of physicians at public hospitals and health workers at nursing homes might improve the efficiency and timeliness of tuberculosis diagnosis and treatment in Taiwan.

摘要

背景

台湾结核病发病率的下降部分归因于 2006 年推出的直接观察治疗短期疗程(DOTS)计划,随后在 2007 年推出了 DOTS-Plus。然而,随着专门结核病护理系统的逐步淘汰和发病率的下降,台湾的临床工作者可能对结核病的表现不太熟悉。通过对患者路径分析与卫生系统延迟估计的补充,本研究的目的有两个:一是估计患者护理开始与及时诊断和治疗服务的提供之间的一致性,并确定结核病治疗延迟的风险因素。

方法

研究人群包括 2013 年所有台湾新发病例结核病患者。我们(1)从 2013 年国家结核病登记处确定了 11507 例新发结核病患者,(2)将登记处的 10932 名台湾人链接到 2012-2013 年国家健康保险研究数据库。我们评估了患者的护理寻求途径,并在 Cox 模型中确定了卫生系统延迟的决定因素。

结果

总体卫生系统延迟为 46 天。我们发现,10932 例结核病患者中有 20.5%和 3.5%分别在因与结核病相关的症状首次就诊时被诊断和治疗。与卫生系统延迟延长相关的风险因素包括女性(调整后的 HR=0.921,95%CI:0.884,0.960)、年龄≥65 岁(调整后的 HR=0.720,95%CI:0.692,0.750)、非严重(胸部 X 光无空洞)(调整后的 HR=0.721,95%CI 0.683-0.760)、慢性呼吸道疾病(调整后的 HR=0.544,95%CI:0.522,0.566)、长期护理机构居住(调整后的 HR=0.580,95%CI:0.525,0.640)、首次就诊于基层医疗机构(调整后的 HR=0.588,95%CI:0.565,0.612)和居住在台湾南部(调整后的 HR=0.887,95%CI:0.798,0.987)。

结论

首次就诊时获得结核病诊断和治疗服务的机会较低以及卫生系统延迟延长表明卫生保健系统效率低下。加强公立医院医生和疗养院卫生工作者的培训,可能会提高台湾结核病诊断和治疗的效率和及时性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fdd/6862853/9970077f7948/12913_2019_4702_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fdd/6862853/d88664c981e4/12913_2019_4702_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fdd/6862853/9970077f7948/12913_2019_4702_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fdd/6862853/d88664c981e4/12913_2019_4702_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fdd/6862853/b759f425d24a/12913_2019_4702_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fdd/6862853/5dafc31b504e/12913_2019_4702_Fig3_HTML.jpg
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