Abstract

ObjectiveThis study assesses the diagnostic delay, treatment duration and treatment outcomes of tuberculosis (TB) patients since the implementation of the integrated model of TB control in a county in eastern China. It further identifies factors associated with diagnostic delay and treatment duration in the integrated model.MethodsWe collected data through the Chinese Tuberculosis Information Management System (TBIMS) for Cangnan County in Zhejiang Province. Chi-square and Mann-Whitney tests were adopted to identify factors associated with duration of treatment and treatment delay for TB patients within the integrated model. Multiple regression analysis was subsequently performed to confirm the identified factors.ResultsIn the integrated model from 2012 to 2018, the median health system delay was maintained at 1 day, and the median patient delay decreased from 14 to 9 days and the median total delay decreased from 15 to 11 days. In addition, the proportion of patients who experienced patient delay > 14 days and total delay > 28 days decreased from 49% to 35% and from 32% to 29% respectively. However, the proportion of patients who had health system delay > 14 days increased from 0.2% to 13% from 2012 to 2018. The median treatment duration increased from 199 to 366 days and the number of TB patients lost to follow-up showed an overall upward trend from 2012 to 2018. The multivariable regression analysis indicated that migrant TB patients and TB patients initially diagnosed in hospitals at the prefectural level and above tended to experience total delay > 28 days (p < 0.001). Linear regression analysis confirmed that new TB patients>60 years tended to have longer treatment duration (p < 0.05).ConclusionsWhile our study may suggest the potential of the integrated model in early detection and diagnosis of TB, it also suggests the importance of strengthening supervision and management of designated hospitals to optimize the treatment duration and improve retention of patients in TB care. Enhancing health education for TB patients, especially amongst migrant patients, and training in TB identification and referral for non-TB doctors are also key for early TB detection and diagnosis in the integrated model.

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