Study Setting
After an initial start-up in two large cities namely, Bengaluru in Karnataka and Hyderabad in Telangana, the project in the third year, refined its approach and scaled up to other select towns and cities in Karnataka, Telangana and Andhra Pradesh states. This paper pertains to analyses of patients only from Karnataka and Telangana, the states with a consistent presence, since the start of the project. The selected geographies covered a total population of 18.6 million urban people in 15 districts of Karnataka and 8.1 million urban people in 6 districts of Telangana. In total, this covered 69 cities/towns and that included 61 in Karnataka and 8 in Telangana. In these selected cities/town the project recruited Community Health Workers (CHWs) who are local residents, to conduct systematic and consistent outreach activities. The outreach activities included, awareness generation on TB, referrals of symptomatic cases, risk and need assessment of patients initiated on TB treatment, treatment follow-ups, contact screening and counselling as required.
Study tools
In consultation with RNTCP staff, the project developed two tools for the TB patients who were initiated on treatment. One tool is known as the Risk and Needs Assessment (RANA) tool and is used to identify the persons with probable risks and those who expressed specific needs during the TB treatment. The second tool is known as Prevention Care and Support Card (PCS) and is used to register the patient for follow-up visits and record the information on activities, test results and actions taken, during each follow-up visit until the treatment outcome is declared.
The project technical team trained the CHWs for a week to administer the tools, using classroom and field sessions. This was followed up by on-the-job supportive supervision by a cadre of cluster coordinators (CC), who were recruited in the ratio of 1 CC: 5 CHWs. The RANA tool was pre-tested for two weeks in Bengaluru and Hyderabad, and adapted for simplicity and uniformity in assessment, recording and interpretation of the data before its administration in the project.
Study procedure
First, we obtained the line list of all the persons diagnosed with TB in the project geographies from the respective RTNCP staff. After that we administered the RANA tools as well as registered the patients who consented for follow-up visits using the PCS. We included only the TB patients who were residing within the towns/cities in the project geographies. The RANA was administered to the patient and in rare instances when the patient was not able to provide the information himself/herself, due to being hearing impairment or being very sick, it was collected from the primary care-giver in the family.
The RANA tool assessed the patient’s understanding of TB and its treatment, explored family level support for the patient, listed social, nutritional and livelihood needs, identified factors that were presumed to be a risk for non-adherence to TB treatment and noted the type of follow-up preferred (in-person or other) by the patient. Each interview took about 25-40 minutes, and was conducted in a venue convenient to the patient, such as the home or the place of treatment. Initially, paper-based entries were computerised onto a Management Information System. Subsequently, the project combined data collection and entry using a mobile app. RANA was administered in Bengaluru and Hyderabad from June, 2018 and in other cities and towns it was administered from August, 2018.
RNTCP Operational definitions
The following provides the RTNCP operational definition of treatment outcomes [11].
Cured: A microbiologically confirmed TB at the beginning of the treatment who was smear or culture‑negative at the end of complete treatment.
Treatment success: TB patients either cured or treatment completed are accounted in the treatment success.
Died: Known to have died from any cause whatsoever while on treatment
Failure: A TB patient whose biological specimen is positive by smear or culture at the end of the treatment.
Lost to follow‑up: A TB patient whose treatment was interrupted for one consecutive month or more.
Not evaluated: A TB patient for whom no treatment outcome is assigned. (Formerly transfer out).
Treatment regimen changed: Previously, it was called as switched over to MDR treatment.
Died, Failure and Lost to follow up were considered together as unfavourable TB treatment outcomes.
Data analysis
We combined three different data sets in order to perform our analysis. For the risk identification we used the data from the RANA. For obtaining the outcome we used the THALI PCS data as well as the official RNTCP data from the Nikshay. The data-sets were linked using a unique identity number and validating it for age and gender. At the beginning of August 2019, we extracted data of patients who were 18 years or older at the time of TB diagnosis and notification, and whose RANA had been carried out in the months of July, August and September 2018. The patients had been initiated on TB treatment, 0-8 months prior to the administration of RANA, with a mean of about 2 months. We restricted the analysis to this cohort of patients mainly in order to ensure that we had treatment outcomes for majority of the patients. We also wanted to avoid the effect of an envisaged differentiated care model that we were piloting for TB patients identified to have a risk for non-adherence to treatment. The treatment outcomes were extracted from the PCS card as on July 31, 2019 or earlier, about 10-12 months after treatment initiation. In case, the treatment outcome was not available in the PCS data, we extracted treatment outcome from the Nikshay data. In the analysis, we included only the patients who had data on outcome declared by the month of July 2019, and who also had both RANA and PCS card. The data analysis included only the patients from Karnataka and Telangana states.
We defined two outcome indicators for the analysis. The first outcome measured was ‘death’, after initiation of TB treatment. The other indicator was ‘unfavourable outcome’ which included death, failure or Lost to Follow Up (LFU). The analysis includes separate results for predefined risk conditions which the individuals have, as well as the risk identified as having one risk or more than one risk.
The data was analysed using Stata version 14. We examined the socio-economic and demographic characteristics of the TB patient cohort as defined. Based on empirical knowledge and available evidence, we considered the following factors as potential risks for non-adherence to treatment: 1) age above 60 years, 2) living alone, 3) co-existing illness including HIV, 4) diabetes and 5) undernutrition, 6) previous treatment for TB, 7) a diagnosis of drug-resistant TB and 8) a history of regular (daily) consumption of alcohol. Information on risk factors listed above were recorded based on patient’s history and/or documented laboratory reports (HIV, diabetes), as applicable.
Undernutrition was not one of the risk factors identified initially. While we aimed to use BMI as our indicator of malnutrition, anthropometric measurements were not feasible for a large number of patients. Hence, we used weight at the time of treatment initiation as our measure and categorised it based on whether it was below or equal to and greater than the median weight of TB patients as recorded in the National Guideline on Nutrition and TB, viz., 43 kg for males and 38 kg for females [12].
We first conducted bivariate analysis to understand whether the presence of any of the above considered risk factors were associated with the two outcome indicators, viz., death and unfavourable TB treatment outcome. Subsequently, we applied multivariate logistic regression to determine the independent effect of each of the individual risk factors, as well as combined risk factor on the two outcomes. We considered two multivariate logistic regression models. In the first multivariate logistic regression model, we considered the risk characterisation based on all the seven stated risks as well as the other background characteristics of the patient. In the second model, we considered the individual risk factors along with the other background characteristics of the patient.
Ethical approval
Ethics approval for program data review and analysis was obtained from the Institutional Ethics Committee of St John’s Medical College and Hospital. Regulatory approval for access to Nikshay data and to interview of patients and subsequent follow-up visits, was provided by the State TB office and local RNTCP officials in the two states.