Wongsa Laohasiriwong1, Roshan Kumar Mahato2, Rajendra Koju3. 1. Associate Professor, Board Committee of Research and Training Centre for Enhancing Quality of Life of Working Age People (REQW), Khon Kaen University; Faculty of Public Health, Khon Kaen University , Khon Kaen, Thailand . 2. MPH (International Health) Faculty of Public Health, Khon Kaen University , Khon Kaen, Thailand . 3. Professor, Department of Internal Medicine, Dhulikhel Hospital, Kathmandu University Hospital , Nepal .
Abstract
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.
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 tuberculosispatients 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 TBpatients faced health system delay problems. Socioeconomic factors, unemployment, influences the health system delay when controlled for other covariates.
Entities:
Keywords:
Central region of Nepal; Cross sectional study; Delay in diagnosis
Authors: Luigi Segagni Lusignani; Gianluca Quaglio; Andrea Atzori; Joseph Nsuka; Ross Grainger; Maria Da Conceiçao Palma; Giovanni Putoto; Fabio Manenti Journal: BMC Infect Dis Date: 2013-04-08 Impact factor: 3.090
Authors: Mohammad Ebrahimi Kalan; Hassan Yekrang Sis; Vinaya Kelkar; Scott H Harrison; Gregory D Goins; Mohammad Asghari Jafarabadi; Jian Han Journal: BMC Public Health Date: 2018-01-24 Impact factor: 3.295