Journal of Clinical and Diagnostic Research, ISSN - 0973 - 709X

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Short Communication
Table of Contents - Year : 2016 | Month : June | Volume : 10 | Issue : 6 | Page : LM01 - LM03

Health System Delay among the Pulmonary Tuberculosis Patients Presenting in the DOTS Centers of Nepal LM01-LM03

Wongsa Laohasiriwong, Roshan Kumar Mahato, Rajendra Koju

Dr. Wongsa Laohasiriwong,
Associate Professor, Faculty of Public Health, Khon Kaen University, Khon Kaen-40002, Thailand.

Introduction: Health system delay is the time for complete diagnosis of the disease after patient approaches a health care provider.

Aim: The study aims to identify the characteristics and the determinants of unacceptable health system delay (= 7 days delay from health system) in diagnosis of new pulmonary tuberculosis patients attending in Direct Observation Treatment Short course (DOTS) centers of Nepal.

Materials and Methods: An analytical cross-sectional study was conducted by administrating a structured questionnaire interview and reviewing the medical record of the new sputum smear positive pulmonary tuberculosis cases during January–May 2015. The generalized linear model (GLM) was applied to control the clustering effects. Multiple logistic regressions were performed to identify the association between variables with = 7 days of unacceptable health system delay.

Results: Of the 374 new sputum smear positive pulmonary tuberculosis cases, the factors that were associated with unacceptable health system delay (time = 7 days) were doing business (adj.OR= 1.61, 95% CI: 1.22-2.11; p-value <0.001) and unemployed (adj.OR= 3.04, 95% CI: 1.53-6.04; p-value <0.001) had chances of health system delay. However, getting support from parents (adj.OR= 0.55, 95% CI: 0.44-0.68; p-value <0.001), consultation with the private practitioners/ pharmacists (adj.OR= 0.24, 95% CI: 0.07-0.81; p-value 0.021), visiting government health facilities (adj.OR= 0.31, 95% CI: 0.13-0.73; p-value 0.008), using X-ray (adj.OR= 0.69, 95% CI: 0.49-0.97; p-value 0.032) and advance technologies for diagnosis of TB (adj.OR= 0.60, 95% CI: 0.39-0.94; p-value 0.024) were found contributing to reduce health system delay while controlling socio-economic, knowledge, presence of symptoms and attitude factors.

Conclusion: About a quarter of new TB patients faced health system delay problems. Socioeconomic factors, unemployment, influences the health system delay when controlled for other covariates.