|Ahead of print publication
Risk Factors associated with delays in seeking treatment and diagnosis of tuberculosis patients at dots center of a tertiary care institute in Himachal Pradesh
Resham Singh, Dineshwar Singh Dhadwal, Anjali Mahajan, Vijay Kumar Barwal
Department of Community Medicine, Indira Gandhi Medical College, Shimla, Himachal Pradesh, India
|Date of Submission||03-Feb-2020|
|Date of Decision||20-Sep-2020|
|Date of Acceptance||22-Sep-2020|
Vijay Kumar Barwal,
Department of Community Medicine, Indira Gandhi Medical College, Shimla, Himachal Pradesh
Source of Support: None, Conflict of Interest: None
Background: Delays in diagnosis of tuberculosis (TB) is still a problem at all levels of health care. Understanding the etiology of these delays is essential for all stakeholders involved in TB control. This study was done to find the delays related to health-care seeking behavior, diagnosis, and major contributors to such delays among newly diagnosed patients of TB. Methods: This cross-sectional study was conducted from August 1, 2018, to July 2019 among the patients of TB diagnosed at Indira Gandhi Medical College, Shimla. A consecutive sample of 105 patients was enrolled for the study. Newly diagnosed cases aged 18 years and above were included in the study. Prevalence ratio with 95% confidence interval was calculated for risk factors associated with the identified delays. Results: At the patient level around 55% reported a delay of more than 14 days in seeking care with a median delay of 45 days (interquartile range [IQR] of 30–60 days). Nearly 67% patients were found to have a diagnostic delay of more than 7 days at the health-care provider level (Median 30 days; IQR 12.5–54.7 days). Delayed initiation of treatment after 7 days of diagnosis was found in 6.6% cases (Median 10 days; IQR 8–15 days) and all of these were patients of extra pulmonary TB. Delay was significantly associated (P = 0.01) with patients who travelled <5 km to reach the health facility. Conclusion: Inter-sectoral coordination, refresher trainings of health-care providers, patient education and capacity building for diagnostics at peripheral institutions can reduce delay in diagnosis and treatment of TB.
Keywords: Prevalence of patient delays, risk factors, tuberculosis
|How to cite this URL:|
Singh R, Dhadwal DS, Mahajan A, Barwal VK. Risk Factors associated with delays in seeking treatment and diagnosis of tuberculosis patients at dots center of a tertiary care institute in Himachal Pradesh. Med J DY Patil Vidyapeeth [Epub ahead of print] [cited 2021 Dec 6]. Available from: https://www.mjdrdypv.org/preprintarticle.asp?id=321282
| Introduction|| |
Globally, tuberculosis (TB) is a major public health problem and is one of the top 10 causes of death worldwide. It is also the main cause of deaths related to antimicrobial resistance and leading killer of people with HIV. According to the World Health Organization (WHO) TB report 2019, an estimated 10 million people fell ill with TB in 2018.
India accounts for more than one-fourth (27%) of the global TB burden. Drug resistance continues to be a threat with an estimated incidence of multidrug resistance being 484,000 globally and 130,000 in India. Government of India has set the target to eliminate TB by 2025 whereas Himachal Pradesh has kept this target even closer and it aspires to achieve it by the year 2021.,
Understanding the causes behind delay in seeking care, diagnosis and treatment is essential for all partners involved in TB control. Delays affecting TB control occurs as patient delay and health system delay. Factors influencing delays can be categorized into “factors influencing health-seeking behavior” and “factors influencing the health system effectiveness.”
The aim of the present study was to assess the extent of delay in seeking health care, diagnosis, and treatment of these patients. We also wanted to identify the major contributors to such delays among the newly diagnosed TB patients at the directly observed treatment, short-course (DOTS) center of Indira Gandhi Medical College (IGMC) Shimla.
| Methods|| |
This cross-sectional study was conducted among the patients of TB diagnosed at IGMC Shimla from August 1, 2018, to July 31, 2019. A consecutive sample of 105 patients was taken after satisfying the inclusion and exclusion criteria. All the newly diagnosed cases aged 18 years and above were included in the study after obtaining informed consent. Relapse, failure, defaulters, patients who were seriously ill and transfer in patients were excluded from the study since it was difficult to ascertain the date of onset of symptoms and measure their delays.
Study tool and variables
A structured, validated, and pretested survey tool adapted from the WHO multicountry TB treatment delay survey was used to interview the patients at DOTS center at the time of registration for initiation of treatment. The study tool contains basic demographic profile of patients, type of TB, history of smoking and associated comorbidities, TB knowledge and their attitude toward the disease. It sought information regarding potential delays at three levels – health-care seeking, health-care provider and at the level of treatment. Delay in health-care seeking was taken as more than 14 days between onset of symptoms to first contact with the health-care provider. At the health-care provider level, the delay was defined as more than 7 days between first contact with the health-care provider and diagnosis of TB. The treatment delay was defined as more than 7 days of time interval between TB diagnosis and initiation of anti-TB drugs.
Data were entered into Microsoft Excel worksheet and checked for accuracy. The statistical tests were performed using Epi Info version 7.2.2 software of Centre for Disease Control and Prevention (CDC), Atlanta, Georgia, United States (US) and descriptive statistics were calculated as frequencies and percentages. As the data were not distributed normally, median (interquartile range [IQR]) was used instead of the mean (standard deviation [SD]). We also calculated the prevalence ratios along with their 95% confidence intervals. The association between two categorical variables was determined using Pearson Chi-square test. A two-tailed P < 0.05 was considered statistically significant throughout the analysis.
We carried out this study after taking due permission from the Institutional Ethics Committee of IGMC Shimla and the state TB officer, Himachal Pradesh. Identifiers were omitted to maintain confidentiality and anonymity. An informed consent was taken from the participants. Each patient was adequately informed of the aims, methods, the anticipated benefits and potential risks the study may entail to him/her.
| Results|| |
Socio-demographic characteristics of study participants
Among 105 participants in the study, 57 (54.3%) were diagnosed as extrapulmonary TB (EPTB). Male participants were 55 (52.3%), while 63 (60%) were from rural areas and majority were married. The median (IQR) age of the participants was 32 (24–48) years with a range of 18–82 years. Only 11 (10.4%) were elderly (age >60 years). Among all the participants, 63 (60%) were educated above primary level. History of smoking was present in 36 (34.2%) participants. Only 10 (9.5%) were smokeless tobacco users and diabetes mellitus was detected in 15 (14.2%) participants. Out of the total participants 92 (87.6%) consulted a health-care provider at a public health facility, 11 (10.4%) went to a private hospital and 2 (1.9%) sought treatment at an ayurvedic hospital [Table 1].
Delay at the patient level and associated risk factors
Median (IQR) delay at the level of patient for seeking care was 45 (30–60) days. Patient level delay of more than 14 days was found in 58 (55.2%) participants. Regarding the reason for delay in seeking treatment, 31% thought that their symptoms would go away on their own and 22.2% had economic constraints. Risk factors for association explored were age, sex, education, type of TB, history of smoking, and income. Prevalence ratio of smoker was 1.08 (0.70–1.44) and in low-income patients it was 1.20 (0.81–1.73) [Table 2].
Delay at the level of health-care provider
Median (IQR) delay at the level of health-care provider for diagnosis of TB was 30 (12.5–54.7) days. Delay of more than 7 days was found in 70 (66.7%) participants. Out of these, reasons cited for delay at the provider level was late diagnosis in 29, referral of patients from peripheral health institutions due to lack of facility for diagnosis in 26 and another 13 patients could not be diagnosed at private/Ayurvedic hospital, while delay in laboratory reporting was found in two patients. In terms of type of health facility, public hospitals caused delay in 57, while private and ayurvedic hospitals caused delay in all the patients who visited them, i.e., 11 and two patients respectively. Risk factors explored for delay were age, sex, type of TB, history of smoking, education, and distance to reach nearest health facility for treatment. Participants who had to travel <5 km to reach the nearest health facility showed a statistically significant longer delay (P = 0.01), in comparison to those who travelled more than 5 km [Table 3].
Delayed initiation of treatment after 7 days of diagnosis was found in 6.6% cases (Median 10 days; IQR 8–15 days) and all of these were patients of EPTB. The main reasons of delay were late collection of reports and shortage of drugs at the DOTS center. No treatment delay was found in participants with pulmonary TB.
| Discussion|| |
Himachal Pradesh is a small hilly state where majority of the health-care needs of the population (83%) are catered to by the public health facilities People have good faith in public hospitals and hence they choose these facilities over private health facilities. Similarly, in our study, also 87.6% of the total participants consulted a health-care provider at a public health facility while only 10.4% went to a private hospital. This is different from the Indian data which shows that only half of the respondents had attended a public hospital for TB care.
The total median delay from onset of symptoms to initiation of treatment was 67 days (IQR 43–103 days). Contrary to this, studies by Das et al., Konda et al., and Sreeramareddy et al., found the median delay to be shorter at 37, 50, and 57.5 days, respectively. The WHO has also reported a median duration of delay ranging from 50.5 to 66.5 days in various countries. A longer delay of 97 days and 150 days was reported in studies conducted by Hussen et al. in Southeast Ethiopia and Saifodine et al. in Mozambique, respectively.,
A median delay of 45 days (IQR 30–60) was observed for health-care seeking. Contrary to this, most of the studies in India,,, found a shorter delay ranging from 10 to 37 days. A study from Nepal reported a median patient delay of 50 days which is slightly higher than our findings. We found a longer delay in females for seeking care at a health facility. Similar findings were seen by Das et al., in West Bengal.
In our study, the EPTB was found in 54.23% study participants. In concordance to our study, Singh et al. in Lucknow (India) also found a higher percentage of EPTB cases varying from 30% to 53% in tertiary care hospitals. There is lack of facilities for diagnosis of EPTB in peripheral health institutions of Himachal Pradesh. IGMC Shimla is a referral center for diagnosis of such cases which explains the high proportion of EPTB in the present study. These findings do not conform to previous studies conducted by Grover et al., and Das et al., in India, and Karim et al. in Bangladesh, who reported that diagnostic delay was significantly higher among pulmonary patients. It was also revealed in our study that patients of pulmonary TB had longer delay for seeking care. This may be due to the reason that smokers neglect the symptoms of cough and sputum, which is a common finding in pulmonary TB.
We found a median delay of 30 days (IQR 12.5–54.7) at the level of health-care provider for diagnosis of TB. A similar median delay of 30 (10.3–60) days and 31 days was also reported in studies conducted in Mumbai, India, and South Africa, respectively. Health-care provider delays (interval between reporting to health-care facility and diagnosis) have been reported to be lower, ranging from 5 days to 17 days in studies from West Bengal, Sikkim, Wardha, and Navi Mumbai. Although in Himachal Pradesh first point of contact is generally a public health facility and there is not much scope of shopping around, still longer delays have been observed. This might be due to referral of patients from peripheral health institutes for want of diagnostic infrastructure, or late diagnosis due to shortage of trained workforce in these facilities. At variance with our study, a longer median delay of 37 days, (IQR 3–170) was reported by Paramasivam et al. in Tamil Nadu, India.
This study showed longer delay at health care provider level in patients who had to travel <5 km to reach the first health facility. This may be due to lack of diagnostics at the first contact health facility. This finding is contrary to the study done in Ethiopia where they found the delay to be shorter if the first contacted health facility was nearby.
Our study revealed median treatment delay of 10 days (IQR 8–15) in EPTB cases. It was higher as compared to the findings of Mundra et al., in Wardha and Bhatt and Manjunath, in Tamil Nadu, who found a median delay of 2 days and 4 days (IQR 3–8 days), respectively. We found no treatment delay in pulmonary TB cases. It was due to the fact that they were immediately put on treatment on priority basis to stop the further transmission of infection. On the other hand occasionally due to limited availability of drugs, EPTB cases that were “transferred out” were asked to take the drugs and start treatment from that respective facility. This caused some delay in initiation of treatment.
One of the limitations of our study is that the information regarding duration of onset of symptoms is self-reported by patients and therefore it may be affected by recall bias. Furthermore, the study design is cross sectional one and it is limited by only providing a snap shot therefore causal inference about associations are difficult to make. Owing to the short study duration, we were able to enroll a limited number of patients. Even though multiple logistic regression would have been the preferable statistical analysis for identifying the delays, we were not able to go beyond univariate analysis owing to insufficient sample. A high proportion of EPTB cases in our study may be due to the study area being a referral center. Also due to slow progression of disease in EPTB cases, the calculation of delays poses a significant challenge.
| Conclusion|| |
Delay in seeking treatment and diagnosis are still a challenge for control of TB at all levels of health care. Intersectoral co-ordination, refresher trainings of health-care providers, patient education and capacity building for diagnostics at peripheral institutions can reduce delay in diagnosis of TB. We need to sustain as well as strengthen the existing mechanisms of information, education and communication of the community at large for addressal of delays at all levels. These small but significant steps can aid in achieving the milestone of eliminating TB from India by 2025 as envisaged in India National Strategic Plan for TB 2017-2025.
Authors of this study want to give sincere thanks to State TB officer, RNTCP, Himachal Pradesh, for his kind permission as well as for providing funds to conduct this study. We gratefully acknowledge all the individuals who consented to participate in our study and spent their valuable time with us.
Financial support and sponsorship
We are grateful to the State TB Officer, RNTCP, Himachal Pradesh, for providing funds to conduct this study.
Conflicts of interest
There are no conflicts of interest.
| References|| |
World Health Organization. Regional Office for the Eastern Mediterranean. Diagnostic and Treatment Delay in Tuberculosis. World Health Organization; 2006. Available from: https://apps.who.int/iris/handle/10665/116501
. [Last accessed on 2020 Jan 23].
Report of the State Health Commission. Himachal Pradesh. Report of the State Health Commission; October, 2015. p. 22.
Hazarika A. Role of private sector in providing tuberculosis care: Evidence from a population-based survey in India. J Glob Infect Dis 2011;3:19-24.
Das S, Basu M, Mandal A, Roy N, Chatterjee S, Dasgupta A. Prevalence and determinants of delay in diagnosis of pulmonary tuberculosis in Darjeeling district of West Bengal. J Fam Med Prim Care 2017;6:627-35.
Konda SG, Melo CA, Giri PA, Behera AB. Determinants of delays in diagnosis and treatment of pulmonary tuberculosis in a new urban township in India: A cross-sectional study. Int J Med Sci Public Health 2014;3:140-5.
Sreeramareddy CT, Qin ZZ, Satyanarayana S, Subbaraman R, Pai M. Delays in diagnosis and treatment of pulmonary tuberculosis in India: A systematic review. Int J Tuberc Lung Dis 2014;18:255-66.
Diagnostic and Treatment Delay in Tuberculosis. An in-Depth Analysis of the Health-Seeking Behaviour of Patients and Health System Response in Seven Countries of the Eastern Mediterranean Region. World Health Organization. Available from: http://applications.emro.who.int/dsaf/dsa710.pdf
. [Last accessed on 2020 Feb 01].
Hussen A, Biadgilign S, Tessema F, Mohammed S, Deribe K, Deribew A. Treatment delay among pulmonary tuberculosis patients in pastoralist communities in Bale Zone, Southeast Ethiopia. BMC Res Notes 2012;5:320.
Saifodine A, Gudo PS, Sidat M, Black J. Patient and health system delay among patients with pulmonary tuberculosis in Beira city, Mozambique. BMC Public Health 2013;13:559.
Mundra A, Kothekar P, Deshmukh PR, Dongre A. Why tuberculosis patients under revised national tuberculosis control programme delay in health-care seeking? A mixed-methods research from Wardha District, Maharashtra. Indian J Public Health 2019;63:94-100.
] [Full text]
Bhatt AN, Manjunath K. Delays are still a challenge in Tuberculosis control Cross-sectional study from South India. Indian J Basic Applied Med Res 2016;1:307-13.
Nimbarte SB, Wagh V, Selokar D. Health seeking behaviour among pulmonary tuberculosis patients in rural part of central India. Int J Biol Med Res 2011;2:394-7.
Purty AJ, Chauhan RC, Natesan M, Cherian J, Singh Z, Sharma Y. Patient and health system delays among adult smear-positive tuberculosis patients diagnosed at medical colleges of Puducherry in south India. Indian J Public Health 2016;60:77-80.
] [Full text]
Yamasaki-Nakagawa M, Ozasa K, Yamada N, Osuga K, Shimouchi A, Ishikawa N, et al
. Gender difference in delays to diagnosis and health care seeking behaviour in a rural area of Nepal. Int J Tuberc Lung Dis 2001;5:24-31.
Singh P, Kant S, Gaur P, Tripathi A, Pandey S. Extra pulmonary tuberculosis: An overview and review of literature. Int J Life Sci Scienti Res 2018;4:1539-41.
Grover M, Bhagat N, Sharma N, Dhuria M. Treatment pathways of extrapulmonary patients diagnosed at a tertiary care hospital in Delhi, India. Lung India 2014;31:16-22.
] [Full text]
Karim F, Islam MA, Chowdhury AM, Johansson E, Diwan VK. Gender differences in delays in diagnosis and treatment of tuberculosis. Health Policy Plan 2007;22:329-34.
Tamhane A, Ambe G, Vermund SH, Kohler CL, Karande A, Sathiakumar N. Pulmonary tuberculosis in Mumbai, India: Factors responsible for patient and treatment delays. Int J Prev Med 2012;3:569-80.
Meintjes G, Schoeman H, Morroni C, Wilson D, Maartens G. Patient and provider delay in tuberculosis suspects from communities with a high HIV prevalence in South Africa: A cross-sectional study. BMC Infect Dis 2008;8:72.
Tobgay KJ, Sarma PS, Thankappan KR. Predictors of treatment delays for tuberculosis in Sikkim. Natl Med J India 2006;19:60-3.
Paramasivam S, Thomas B, Chandran P, Thayyil J, George B, Sivakumar CP. Diagnostic delay and associated factors among patients with pulmonary tuberculosis in Kerala. J Family Med Prim Care 2017;6:643-8.
] [Full text]
Adenager GS, Alemseged F, Asefa H, Gebremedhin AT. Factors Associated with Treatment Delay among Pulmonary Tuberculosis Patients in Public and Private Health Facilities in Addis Ababa, Ethiopia. Tuberculosis Research and Treatment; 2017. Available from: http://downloads.hindawi.com/journals/trt/2017/5120841.pdf
. [Last accessed on 2020 Feb 15].
[Table 1], [Table 2], [Table 3]