Abstract:

Objective To explore the influencing factors of patient delay, diagnosis delay in pulmonary tuberculosis (PTB) patients in schools of Tongzhou District of Beijing, and to provide evidence for strengthening intervention measures. Methods One hundred fifty-two new PTB patients detected from 2014 to 2019 in schools of Tongzhou District of Beijing were selected as study subjects. Retrospective study method was used to collect the medical record data from the Chinese TB Management Information System, the case investigation data using uniform questionairre across Beijing and other school-related data.Chi-squared test and multivariate logistic regression were used to analyze the influencing factors of patient delay (from symptom onset to seeking health care >14 days), diagnosis delay(from seeking medical service to diagnosis >14 days) in those PTB patients. Results The median days (quartiles) from symptom onset to seeking health care was 4.0 (0.0,11.0) days while the median days (quartiles) from seeking medical service to diagnosis was 10.5 (6.0,19.0) days. The proportions of patient delay, diagnosis delay among all patients were 16.4% (25/152),34.9% (53/152), respectively. Multivariate logistic regression analysis showed that, the risk of patient delay for PTB patients in schools without morning and afternoon symptom examination was higher (OR (95%CI)=26.900 (3.188-226.978)) than those in schools with this practice; in contrast to passive detection, the risk of patient delay was lower among school PTB patients identified by health examination (OR (95%CI)=0.049 (0.005-0.436)) and by close contact screening (OR (95%CI)=0.088 (0.010-0.802)); patients whose symptoms onset in the second and third quarter of year had a lower risk of patient delay than that in the fourth quarter (OR (95%CI)=0.089 (0.020-0.391),OR (95%CI)=0.169 (0.036-0.801)); the risk of diagnosis delay was higher for patients who were firstly diagnosed in non-TB-designated medical institutions than in special TB medical institutions (OR (95%CI)=2.638(1.203-5.785)); compared with passive detection, the risk of diagnosis delay of patients detected by close contact screening was lower (OR (95%CI)=0.169(0.037-0.785)). Conclusion The influencing factors of patient delay, diagnosis delay of PTB patients in schools of Tongzhou District of Beijing were factors about patients, medical institutions and schools. Intervention should be strengthened targeting at those influencing factors. While improving the diagnosis ability and awareness of detecting TB in non-TB-designated medical institutions, we should focus on interventions for school related factors such as morning and afternoon symptom examination system and regular health examination system to reduce the chance of delay.

Key words: Tuberculosis, Schools, Patient delay, Delayed diagnosis, Factor analysis, statistics