|Year : 2022 | Volume
| Issue : 5 | Page : 60-65
Diagnostic and treatment delay among new pulmonary tuberculosis patients in Southern India: A cross-sectional study
Arjun Balasubramnian1, Paul T Francis2, K Leelamoni2, PS Rakesh3, Jishnu Sathees Lalu4
1 RPO, Office of DG AFMS, Ministry of Defence, Kerala, India
2 Professor, Department of Community Medicine, Amrita Institute of Medical Sciences, Amrita Vishwa Vidyapeetham, Kerala, India
3 Medical Consultant, WHO NTEP Technical Support Network, Kerala, India
4 Officer-in-Charge, Station Health Organisation Port Blair, Indian Navy, India
|Date of Submission||09-Aug-2022|
|Date of Decision||24-Aug-2022|
|Date of Acceptance||25-Aug-2022|
|Date of Web Publication||11-Nov-2022|
49 Five Furlong Road, Guindy, Chennai - 600 032, Tamil Nadu
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: Delay in diagnosis and treatment enhances tuberculosis (TB) transmission and mortality. Understanding causes for delay can help in TB elimination by 2025, the stated goal of India. Objectives: Estimate diagnostic and treatment delay in Ernakulam district of Kerala, identify associated factors, and determine health-seeking behavior and knowledge regarding TB among new pulmonary TB patients. Materials and Methods: Community-based cross-sectional study among the new pulmonary TB patients registered under Revised National TB Control Program. Patients interviewed in-person and data collected using pretested semi-structured questionnaire. Descriptive statistics expressed as frequency, percent, interquartile range, median, and mean. The Chi-square test was used to assess statistical significance (P < 0.05) of association. Backward conditional method logistic regression done using variables with P < 0.2 in univariate analysis and adjusting for possible confounders. Results: Two hundred and twenty-nine patients interviewed and the median patient, health-care system, and treatment delay were 25 days, 22 days, and 1 day, respectively. While the patient delay (>30 days) and treatment delay (>2 days) were seen in 47.6% and 41% of patients, respectively, health-care system delay was seen in 79.9% of the patients. Choosing pharmacy for initial treatment (adjusted odds ratio [aOR] = 5.217), unskilled occupation (aOR = 3.717), female gender (aOR = 3.467), previously not heard about TB (aOR = 3.410), and lower education level (aOR = 2.774) were the independent predictors of the patient delay. Visiting two or more doctors (aOR = 5.855) and initially visiting a doctor of undergraduate qualification (aOR = 3.650) were the independent predictors of health-care system delay. The diagnosis in private sector (aOR = 8.989), not being admitted (aOR = 3.441), and age above 60 years (aOR = 0.394) was the independent predictors of treatment delay. Conclusion: Initial treatment from pharmacy, consulting multiple physicians, and diagnosis by private sector cause significant delay in diagnosis and treatment of pulmonary TB.
Keywords: Delay, National Tuberculosis Elimination Program, patient delay, revised national tuberculosis control program, treatment delay, tuberculosis
|How to cite this article:|
Balasubramnian A, Francis PT, Leelamoni K, Rakesh P S, Lalu JS. Diagnostic and treatment delay among new pulmonary tuberculosis patients in Southern India: A cross-sectional study. Indian J Public Health 2022;66, Suppl S1:60-5
|How to cite this URL:|
Balasubramnian A, Francis PT, Leelamoni K, Rakesh P S, Lalu JS. Diagnostic and treatment delay among new pulmonary tuberculosis patients in Southern India: A cross-sectional study. Indian J Public Health [serial online] 2022 [cited 2022 Dec 4];66, Suppl S1:60-5. Available from: https://www.ijph.in/text.asp?2022/66/5/60/360646
| Introduction|| |
An individual's risk of being infected with tubercle bacilli is directly proportional to the number of active pulmonary tuberculosis (TB) cases in the community, the duration of their infectiousness, and the frequency of interactions with the active case. It is estimated that an untreated smear-positive pulmonary TB patient can infect 10–15 contacts annually and about 20 during the natural history of the disease until death. Therefore, the period of infectivity of the active TB cases is the most important factor in contributing to the risk of the general population becoming infected and thereby spreading the disease. Thus, early diagnosis and prompt treatment are the most effective control strategy. A delay in the diagnosis and treatment not only enhances TB transmission but can also contribute to drug resistance, advanced disease status at presentation, poor treatment response, adverse sequelae, and overall increase in mortality.
The causes for delay in case-finding are multi-factorial, broadly grouped under two categories: delay arising due to the patient (patient delay) and delay arising from the health system (health system delay). The causes are not uniform and vary greatly between high prevalence and low prevalence countries. While in a low prevalence country, the unlikely clinical suspicion of TB coupled with disintegration of previous infrastructure for TB control is the attributable factors for delay, the causes for delay in a high prevalence country like India can be related to both the patients and the physicians.
Studies have demonstrated that there is considerable delay in India. The risk factors for delay vary among regions not only due to the socioeconomic and cultural diversity but also due to the heterogeneity in the health-care delivery system. Understanding the causes for the delay can help strengthen the TB control program and improve case detection. This study was conducted with the primary objective of estimating the diagnostic and treatment delay in Ernakulam district of Kerala, India and identify its associated factors. The secondary objectives were to determine the health-seeking behavior and knowledge regarding TB among the new pulmonary TB patients.
| Materials and Methods|| |
A community-based cross-sectional study was conducted in Ernakulam district among the new pulmonary TB patients registered under Revised National TB Control Program (RNTCP) in 2016.
All patients aged 18 years and above were included in the study.
The following criteria were excluded from the study:
- Patients who could not be contacted despite two attempts
- Patients who are not in-station during the data collection period.
Time interval between the onset of symptoms and labeling of the patient as a TB patient (TB diagnosis).
Time interval between the onset of symptom and presentation to a health-care provider [Figure 1].
Health-care system delay
Time interval between the date of health-seeking behavior to a health-care provider and date of TB diagnosis [Figure 1].
Time interval between TB diagnosis and initiation of anti-TB drugs [Figure 1].
Based on a study done by Datta and Jobby among TB patients in Kottayam district in Kerala which reported a mean diagnostic delay of 73.98 days and standard deviation of 73.88 days, the minimum sample size was 170 using the formula: 
n = ([(Z1–α/2)2s2]/d2) with 95% confidence and 15% allowable error.
Adjusting for 10% nonresponse rate, the minimum sample size was 187. All adult new pulmonary TB patients were taken. To minimize recall bias, only patients registered up to 2 months before data collection were included in the study. Applying this criteria, a total of 264 patients were available in the sample frame.
Data were collected using a pretested semi-structured questionnaire adapted from the WHO multi-country study to estimate the diagnostic and treatment delay in TB. Eight patients were interviewed either at their homes or at a public health institution as preferred by the patient.
Data were tabulated using MS EXCEL and analyzed using IBM SPSS Statistics for Windows, Version 20.0. Armonk, NY: IBM Corp. Cutoff for patient delay was set at 30 days; while for health system delay, it was set at 10 days considering a duration of 1 week for a course of antibiotics and additional 3 days for diagnostic sputum smear microscopy. The cutoff for treatment delay was set at 2 days as patients diagnosed in the private sector need to be referred and tested in a Designated Microscopy Center before initiating treatment. Level of significance was set at P < 0.05. Using backward conditional method, logistic regression was done using variables with P < 0.2 in univariate analysis and adjusting for all possible confounders.
Ethical approval was obtained from the Institutional Ethics Committee. Informed and written consent printed in the native language was taken from all the respondents in the study before the interview.
| Results|| |
Of the 264 patients in the sample frame, 229 patients were included in the study. Thirty-five patients were excluded as per criteria (17-did not consent; eight-expired; five– more than two attempts made; and five-out of station during data collection).
The mean age was 51.21 ± 13.79 years, majority males (84.7%), Hindu (69.9%), and resided in pucca house (94.3%) in rural area (52.4%).
The median patient delay was 25 days (interquartile range [IQR]: 14–45); health-care system delay was 22 days (IQR: 10.5–45) and treatment delay was 1 day (IQR: 1–3). While the patient delay (>30 days) and treatment delay (>2 days) were seen in 47.6% and 41% of the patients, respectively, health-care system delay was seen in 79.9% of the patients. Univariate analysis of significant associated factors is given in [Table 1].
The independent predictors of delay are given in [Table 2]. Choosing pharmacy for initial treatment (adjusted odds ratio [aOR] = 5.217, 95% confidence interval [CI] 2.567–10.605), unskilled occupation (aOR = 3.717, 95% CI 1.558–8.867), female gender (aOR = 3.467, 95% CI 1.371–8.769), previously not heard about TB (aOR = 3.410, 95% CI 1.152–10.095), and lower education level (aOR = 2.774, 95% CI 1.291–5.959) were the independent predictors of patient delay.
|Table 2: Logistic regression analysis for independent predictors of delay|
Click here to view
Visiting two or more doctors (aOR = 5.855, 95% CI 2.716–12.619) and initially visiting a Doctor of Undergraduate qualification (aOR = 3.650, 95% CI 1.711–7.789) were the independent predictors of the health-care system delay.
A diagnosis in the private sector (aOR = 8.989, 95% CI 4.563–17.708), not being admitted (aOR = 3.441, 95% CI 1.259–9.403), and age above 60 years (aOR = 0.394, 95% CI 0.167–0.929) was the independent predictors of treatment delay.
| Discussion|| |
The Government of India is committed to the ambitious goal of eliminating TB by year 2025. Achieving the goal requires improving the performance of all parameters of the program. Analyzing the causes for the delay in diagnosis and initiation of treatment will be critical to take remedial measures necessary for the success of TB elimination.
Late diagnosis and late treatment perpetuate TB transmission in the community and is associated with worse prognosis. The patient delay in this study was 25 days (IQR 14–45) lower than the acceptable duration set in this study as well as in other studies., Studies from other parts of the country have estimated patient delay from 20 days in Tamil Nadu to 95 days in Maharashtra., However, in a review study by Sreeramareddy et al., the median patient delay in India was 18.4 days (IQR 14.3–27.0) which was lower than the estimate in the present study. In a low incidence country like France, the median patient delay was 14 days (IQR 0–53). However, even in some developed countries such as USA and UK, the median patient delay ranged from 22 to 54 days which were comparable or higher than our study.,
In our study, females (aOR = 3.467, 95% CI 1.371–8.769) experienced greater delay in seeking a health-care provider as compared to men. This gender disparity was also seen in studies done in Pakistan and Bangladesh. Although, in our study, gender was a significant factor to patient delay only, it remained an insignificant factor for health-care system and treatment delay.
According to this study, patients who first took treatment from a pharmacy had greater odds (aOR = 5.217, 95% CI 2.567–10.605) of having patient delay. In a study by Satyanarayana et al., which assessed the medical advice and drug dispensing practices of pharmacies in three cities of India using standardized patient cases, only 13% of the pharmacies correctly referred the patient to a health facility without dispensing medicine.
In this study, lower educational status (aOR = 2.774, 95% CI 1.291–5.959) was a significant risk factors for patient delay. This was similar to studies conducted in rural China and Brazil, which also reported higher proportion of patient delay among the illiterates/less educated., Patients employed in an unskilled occupation (aOR = 3.717, 95% CI 1.558–8.867) had greater odds for patient delay. A study conducted in Gujarat also had unskilled occupation as a risk factor for patient delay. In this study, if a patient had previously heard about TB, it was taken as a proxy indicator of patient's prior knowledge about TB. Moreover, not having previously heard about TB (aOR = 3.410, 95% CI 1.152–10.095) was found to be a significant risk factor for patient delay.
In the present study, the median health-care system delay was 22 days (IQR 10.5–45) which was much lower than a delay of 31 days (IQR 24.5–35.4) as estimated from a systematic review by Sreeramareddy et al. The estimate in this study was also lower than studies by Uplekar et al. in Pune, where the health-care system delay was 36.7 days.Furthermore, in this study, consulting more than one doctor was a significant risk factor for delay in the diagnosis (aOR = 5.855, 95% CI 2.716–12.619). This was again similar to the findings from the study done in Maharashtra by Tamhane et al. In the present study, it took a median duration of only 1 day (IQR 1–3) to initiate treatment, once diagnosis was made. The finding was similar to the results from other parts of the country like Wardha, where the median treatment delay was 1.8. A systematic review of studies in India showed a median estimate of 2.5 days (IQR 1.9–3.6). Being diagnosed in the private sector was a significant risk factor for treatment delay (OR = 8.989, 95% CI 4.563–17.708).
The limitation of the study is that patients not notified under RNTCP were not included in the study.
Understanding the factors causing delay in the diagnosis and treatment of pulmonary TB patients can help program managers devise specific solutions to remove the barriers to the early diagnosis and treatment. The effectiveness of future public health interventions against TB may be assessed in terms of reduction in delay and this study can provide a baseline information about delays in the diagnosis and treatment of TB patients in the district.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Thakur R, Murhekar M. Delay in diagnosis and treatment among TB patients registered under RNTCP Mandi, Himachal Pradesh, India, 2010. Indian J Tuberc 2013;60:37-45.
Long NH, Johansson E, Lönnroth K, Eriksson B, Winkvist A, Diwan VK. Longer delays in tuberculosis diagnosis among women in Vietnam. Int J Tuberc Lung Dis 1999;3:388-93.
Rajeswari R, Chandrasekaran V, Suhadev M, Sivasubramaniam S, Sudha G, Renu G. Factors associated with patient and health system delays in the diagnosis of tuberculosis in South India. Int J Tuberc Lung Dis 2002;6:789-95.
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.
World Health Organisation. Diagnostic and Treatment Delay in Tuberculosis. Geneva: World Health Organisation: 2006.
Datta S, Jobby A. Diagnostic delay and health seeking behaviour among tuberculosis patients under revised national tuberculosis control programme in Kottayam, Kerala. J Evol Med Dent Sci 2013;2:6228-34.
Goel K, Kondagunta N, Soans SJ, Bairy AR, Goel P. Reasons for patient delays & health system delays for tuberculosis in South India. Indian J Community Health 2012;23:87-9.
Demissie M, Lindtjorn B, Berhane Y. Patient and health service delay in the diagnosis of pulmonary tuberculosis in Ethiopia. BMC Public Health 2002;2:23.
Yimer S, Bjune G, Alene G. Diagnostic and treatment delay among pulmonary tuberculosis patients in Ethiopia: A cross sectional study. BMC Infect Dis 2005;5:112.
Bawankule S, Quazi SZ, Gaidhane A, Khatib N. Delay in DOTS for new pulmonary tuberculosis patient from the rural area of Wardha District, India. Online J Health Allied Sci 2010;9:5.
Pezzotti P, Pozzato S, Ferroni E, Mazzocato V, Altieri AM, Gualano G, et al.
Delay in diagnosis of pulmonary tuberculosis: A survey in the Lazio region, Italy. Epidemiol Biostat Public Health 2015;12:1-10.
Golub JE, Bur S, Cronin WA, Gange S, Baruch N, Comstock GW, et al
. Patient and health care system delays in pulmonary tuberculosis diagnosis in a low-incidence state. Int J Tuberc Lung Dis 2005;9:992-8.
Thorson A, Hoa NP, Long NH. Health-seeking behaviour of individuals with a cough of more than 3 weeks. Lancet 2000;356:1823-4.
Qureshi SA, Morkve O, Mustafa T. Patient and health system delays: Health-care seeking behaviour among pulmonary tuberculosis patients in Pakistan. J Pak Med Assoc 2008;58:318-21.
Satyanarayana S, Kwan A, Daniels B, Subbaraman R, McDowell A, Bergkvist S, et al
. Use of standardised patients to assess antibiotic dispensing for tuberculosis by pharmacies in urban India: A cross-sectional study. Lancet Infect Dis 2016;16:1261-8.
Xu B, Jiang QW, Xiu Y, Diwan VK. Diagnostic delays in access to tuberculosis care in counties with or without the National tuberculosis control programme in rural China. Int J Tuberc Lung Dis 2005;9:784-90.
Trigueiro D, Nogueira J, Sá L, Monroe A, Anjos U, Villa T, et al.
The influence of individual determinants in the delay of the tuberculosis diagnosis. Texto Contexto Enferm 2014;23:1022-31.
Damor R, Jankar D, Rathod S, Gosaliya V, Patel J, Singh MP. Delay in diagnosis and treatment among pulmonary tuberculosis patients in bhavnagar city – A cross sectional study. Int J Res Med 2015;4:38-43.
Uplekar M, Juvekar S, Morankar S, Rangan S, Nunn P. Tuberculosis patients and practitioners in private clinics in India. Int J Tuberc Lung Dis 1998;2:324-9.
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.
[Table 1], [Table 2]