Effect of mobile voice calls on treatment initiation among patients diagnosed with tuberculosis in a tertiary care hospital of Puducherry: A randomized controlled trial.

Objective: In India, about one third of tuberculosis (TB) patients diagnosed at tertiary hospitals are missed during a referral to peripheral health institutes for treatment. To address this, we assessed whether mobile voice call reminders to TB patients after diagnosis at a tertiary hospital decrease the proportion of "pretreatment loss to follow-up" (PTLFU), compared with the conventional paper-based referral. Design: A two-group parallel-arm randomized controlled trial was conducted. Setting: The study was conducted in a tertiary care hospital at Puducherry, South India. Participants: All newly diagnosed TB patients, both pulmonary and extrapulmonary, who were referred for treatment from the selected tertiary care hospital and possessed a mobile phone were eligible to participate. The participants were enrolled between March 2015 and June 2016 and were randomized to study groups using the block randomization with allocation concealment. Intervention: The participants in the intervention arm received standardized mobile voice calls reminding them to register for anti-TB treatment on the second and seventh day after referral in addition to the conventional paper-based referral received by the control group. Primary outcomes: Patients not started on anti-TB treatment within 14 days of referral were considered as PTLFU. The outcome of PTLFU was ascertained through phone calls made on the 14th day after referral. The intention-to-treat analysis was used, and the proportion of PTLFU in the study groups and the risk difference with 95% confidence interval (CI) were calculated.
Results: Of the 393 patients assessed for eligibility, 310 were randomized to the intervention (n = 155) and control (n = 155) arms. In the intervention arm, 14 (9%) out of 155 were PTLFU compared with 28 (18%) of the 155 patients in the control arm. The absolute risk difference was 9% (95% CI [1.5, 16.6], P = 0.01).
Conclusion: Mobile voice call reminder to patients is a feasible intervention and can reduce PTLFU among referred TB patients.

Introduction

Globally, tuberculosis (TB) remains a major public health problem with an estimated 10 million incident TB patients in the year 2019.[1] In the same year, an estimated 1.41 million died due to TB, and the death rates due to TB are disproportionately high in low- and middle-income countries (LMICs).[2] In 2019, India accounted for about 26% of the global TB incidence and an estimated 445,500 individuals died of TB.

In 2015, the World Health Assembly passed a resolution to end the global TB epidemic by 2030. The End TB strategy, endorsed “treatment of all people with TB” as one of the key components to end the TB epidemic.[3] Early diagnosis and treatment not only reduce morbidity and mortality among TB patients but also interrupt the transmission of disease.

In India, though the access to diagnosis and treatment has improved, a substantial number of TB patients drop out of the care pathway either during the process of diagnosis, before initiating the treatment, or during the treatment.[4] The dropout of TB patients between diagnosis and treatment is termed as “pretreatment loss to follow-up” (PTLFU). The proportion of PTLFU varies across different settings and ranges between 4% and 38%.[567891011121314] Low levels of knowledge on TB and available treatment among patients,[15] high caseloads at designated microscopic centers, and weak referral mechanisms within health care system together contribute to PTLFU.[1617]

In India, more than 50% of the TB patients in the public sector are diagnosed in tertiary care hospitals and are referred to the peripheral health institutes (PHI) nearest to the patient's residence for initiation of antituberculosis treatment (ATT).[18] Conventionally, this is done through the use of a paper-based referral form, which the patient is expected to share with the providers at the destination health facility. The PTLFU is relatively high among such referred patients because they belong to different administrative units (districts or states), thus posing a challenge for the National TB Programme (NTP) in tracking them.[19] Although a similar situation exists in majority of the LMICs, the interventions targeting PTLFU are scarce. A previous study in Cambodia has shown that tracking TB patients through mobile phone calls has improved treatment initiation rates to 99% among referred TB patients.[20] However, the study did not have a comparison group to completely attribute the difference in initiation rates to mobile voice call intervention. In this regard, we hypothesized that mobile voice call reminders to patients on the second and seventh day after referral might help in reducing the proportion of PTLFU compared with conventional referral system.

To test this hypothesis, we conducted a randomized controlled trial. The key objective was to assess whether mobile voice call reminders to TB patients diagnosed at a tertiary care center and referred to PHIs (peripheral health institutions) decrease the proportion of PTLFU compared with the conventional paper-based referral.

Materials and Methods

Study design

This study was a two-group parallel-arm randomized controlled trial.

Study setting

The study was conducted in Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), a tertiary care teaching hospital located at Puducherry, South India. The study setting is a 2,100-bedded multispecialty hospital with an average outpatient attendance of about 5,500 per day. TB patients are diagnosed and managed as per the guidelines of the Revised National Tuberculosis Control Programme (RNTCP) of India.[21] The presumptive TB patients with symptoms suggestive of TB are detected by clinicians in both outpatient and inpatient departments. The pulmonary TB patients are diagnosed using sputum smear microscopy (fluorescent LED microscopy) at an in-house designated microscopy center (DMC) supported by RNTCP. The extrapulmonary TB patients are diagnosed based on corroborative evidence from clinical, biochemical, radiological, histopathological, and microbiological findings of various organ specimens. All diagnostic procedures are provided free of cost to the patients.

Under the RNTCP, all the TB patients receive anti-TB treatment under the direct observation of a treatment provider (who could be a health care worker or a community volunteer). This requires that either the patient visits the provider daily or the provider has to visit the patient at his or her house.[21] To facilitate this process, treatment services are arranged as close to the patient's home as possible. As the tertiary teaching hospital is not restricted to a selective catchment population, the patients come from far-off places to seek care at the hospital. Thus, the TB patients diagnosed in tertiary teaching hospitals are not started on the anti-TB treatment but referred to their nearby PHIs for initiation of the treatment. There is an RNTCP unit within the tertiary teaching hospitals to facilitate the referral of TB patients. All the TB patients diagnosed by various departments in the hospital are referred to the RNTCP unit for registering and referring patients to their nearest PHI for treatment initiation.

Prior to the referral, the TB patients are counseled by a medical social worker of the RNTCP unit regarding the need for initiating treatment at their nearby PHI. The medical officer provides a referral slip to the patients with information on diagnosis and treatment recorded. The patient has to produce this referral slip to the medical officer of the destination PHI for starting the treatment.

The line list of patients diagnosed at the hospital is compiled and shared with the district TB office every fortnight. The list of patients belonging to various districts is shared with the concerned district TB control officer for feedback on treatment of patients referred. However, the current system of feedback is not functioning optimally under the national program. The flow chart depicting diagnosis, referral of TB patients, potential dropout, and delay is shown in Figure 1.

Figure 1

Depiction of flow of patients diagnosed and referred for treatment in the study setting * Dotted line indicates the existing feedback system Point of dropout and delay: A- Identified presumptive TB patient in getting investigations done; B- Presumptive TB patient collecting the results of investigations; C- TB patient not reaching the RNTCP medical officer/referral unit; D- TB patient referred from tertiary care hospital not reaching the referred PHI; E- TB patient reaching the PHI but not started on treatment

Study population and period

All newly diagnosed TB patients, both pulmonary and extrapulmonary, who were referred for treatment from this tertiary care hospital (DMC) and who possessed a mobile phone, were eligible to participate in the trial. The study participants were enrolled between March 2015 and June 2016.

Sample size, sampling, and randomization

The minimum calculated sample size was 146 in each arm, sufficient to detect a 10% decrease in the rate of PTLFU in the intervention arm compared with 15.3% in the control arm[15] with an alpha error of 0.05 and a power of 80%.

During the study period, the participant recruitment days were preselected using computer-generated random numbers. On the recruitment days, the principal investigator (PI) assessed for eligibility among all the patients receiving referral on the given day. The eligible participants were explained about the study procedure that they may or may not receive voice call reminders on Day 2 and Day 7. Participants were also informed that outcome ascertainment will be done through voice call at the end of 14 days. Participants who consented to participate were randomized to either arm using the block randomization method. The allocation schedule for random assignment was computer generated using random blocks of size two, four, or eight. Allocation into either arm was placed into sequentially numbered, opaque, sealed envelopes, which were opened as and when a new participant was recruited into the study. Since the participant recruitment and the intervention were provided by the same investigator, blinding was not possible. Although the allocation was not revealed to the patient at the time of recruitment into the study, later it was possible for the patient to discern which arm they were allocated to.

Description of the intervention

In the intervention arm, the participants received telephonic voice call reminders in addition to the conventional referral letter and counseling. The participants in the intervention arm were contacted by the investigator through voice calls on the second and seventh day after referral. The content of the voice call was standardized. During the voice call, the investigator confirmed the identity of the patient and enquired about the status of TB treatment at their referred PHI. Those patients who had not visited the health center or those who had visited but were not initiated on TB drugs were provided information such as the importance of starting treatment, duration of therapy, and the nearby health center where TB treatment services can be availed to enable them to start treatment. In case the participant's mobile phone was switched off during the attempted voice call intervention, a maximum of six attempts over 3 days with an interval of at least 6 hours were made to provide the intervention. Those participants who could not be contacted despite six attempts were labeled as “lost to follow-up” for analysis purpose.

Participants in the control group received the conventional form of referral, which included a referral letter provided by the medical officer at the DMC. Prior to the referral, the patients were counseled by a medical social worker about the need for the long-term TB treatment at their nearby PHI.

Outcome ascertainment

On the 14th day of referral, the outcomes were ascertained through mobile voice calls in both the arms. The status of treatment initiation and date of initiation were recorded. Information about the number of visits to the PHI before treatment initiation, place of treatment initiation, and the reasons for not starting treatment was also collected.

Study tool and variables

The data were collected using a pretested structured interview schedule. Information on demographic characteristics, details of comorbid conditions, behavioral risk factors (tobacco and alcohol use), disease characteristics, and details of referral was collected through interview at the time of enrolment and review of clinical records. The primary outcome variable was the proportion of patients initiated on treatment within 14 days of referral. We also collected information on the date of receiving the first dose of treatment and the reasons for not starting on the treatment. The outcome was ascertained through a patient interview over mobile phone calls.

Operational definitions

Pretreatment loss to follow-up: Patients with the diagnosis of TB who had received the referral letter from the DMC but had not started anti-TB treatment in their nearby health center within 14 days of referral were considered “pretreatment loss to follow-up.”

Initiation of treatment: A person was considered as “initiated on treatment” if he or she, upon telephonic interview, self-reported to have registered in the nearby health facility for TB treatment.

Duration of delay in treatment initiation: Treatment delay was calculated as the time gap (in days) between the date of diagnosis and the date of treatment initiation. The treatment delay consisted of two components: (1) from the date of diagnosis to the date of receipt of referral letter at the tertiary care institute and (2) from the date of referral at the tertiary care institute to the date of treatment initiation at PHI.

Statistical analysis

Data were entered using EpiData software (Version 3.1, EpiData Association, Odense, Denmark, 2008).[22] To detect significant differences in the distributions of descriptive variables between the control and intervention arms, we used the Chi-square test or the Fisher's exact test as appropriate for categorical variables and t tests for continuous variables. Both perprotocol analysis and intention-to-treat analysis were employed to compare the proportion of patients not initiated on TB treatment at the end of 14 days in the intervention and the control arms, and the risk difference with 95% CI was calculated. The number needed to treat for averting one PTLFU was estimated as the inverse of absolute risk reduction. In the intention-to-treat analysis, outcomes (status of treatment initiation) of those patients whom we failed to contact were considered as PTLFU. To assess the independent association, a generalized linear model (Poisson regression) with robust variance estimates were used as the log-binomial model failed to achieve convergence. Initially, all the variables were included in the multivariable model. Later, the variables with a variance inflation factor of more than 5 (the cutoff considered for assessing collinearity) were removed from the final model and adjusted relative risks (RR) with 95% CI were calculated as a measure of association. The duration between diagnosis or referral and the initiation of treatment was compared across the groups using Wilcoxon rank-sum test. A P value of less than 0.05 was considered statistically significant. All analyses were carried out using Stata, Version 12.0.[23]

Ethics approval

Ethics approval was obtained from the Institute Ethics Committee of JIPMER (reference No: JIP/IEC/SC/2014/8/633). Permission was sought from the State TB Control Officer of the Puducherry Union Territory for conducting the trial within the routine programmatic setting.

Patient and public Involvement

The PI and the co-investigators interacted with the State TB program officials on the importance of the PTLFU in the region. The program officials encouraged the investigators to design and conduct this study to assess the effect of the intervention. The officials were interested to see the effect of the intervention on PTLFU and were willing to scale up this intervention if found to be effective. The PI discussed the study details with the medical officer in charge and the staff in the DMC of the tertiary hospital before conducting the study. The TB patients were not involved in the designing of this protocol. However, the benefits from this intervention were directly related to the optimal care of the TB patients.

Results

Participant enrolment

Of the total 393 referred TB patients who were assessed for eligibility, about 76 (19.3%) did not possess a mobile phone and/or belonged to states other than Tamil Nadu and Puducherry and hence were excluded. Of the 317 patients who met the inclusion criteria, about 7 (2.2%) patients declined to participate in the study. Of the 310 patients recruited, 155 each were randomized to the intervention arm and control arm. Of the 155 patients in the intervention arm, 148 (95.5%) received the mobile voice call intervention as per the protocol and seven did not receive the intervention because the participant's mobile number was switched off or not reachable despite six attempts [Figure 2]. Outcomes could be assessed only for 148 (95.4%) and 146 (94.2%) participants in the intervention arm and control arm, respectively, because the other participants could not be reached over mobile phone despite six attempts.

Figure 2

CONSORT diagram depicting eligibility screening, enrollment, randomization, and analysis

Baseline characteristics

Demographic and clinical characteristics were similar between the two groups [Tables 1 and 2]. Majority of the study participants were male (69.4%) with a mean (SD) age of 39 (15) years. About two thirds of the participants had more than primary education and about 18% were unemployed. Current use of tobacco products and alcohol was reported by 21% and 27% of the participants, respectively. Overall HIV (human immunodeficiency virus) positivity was 5.8%, and 54% of patients had extrapulmonary TB. About 79% of the participants did not have any coexisting illness, and diabetes was the most commonly reported comorbidity (12%). Previously treated patients accounted for about 10% of the study participants.

Table 1

Baseline demographic characteristics of the study population enrolled in the study (N=310)

Characteristics	Intervention group (N=155)n (%)	Control group (N=155)n (%)	P
Mean (SD) age, years	38 (15)	40 (15)	0.23
Gender
Male	108 (69.7)	107 (69.0)	0.90
Female	47 (30.3)	48 (31.0)
Education#
Primary or less	52 (33.5)	64 (41.3)	0.37
Secondary	77 (49.7)	69 (44.5)
Graduate and above	26 (16.8)	22 (14.2)
Occupation
Employed	79 (51.0)	74 (47.8)	0.14
Unemployed	25 (16.1)	29 (18.7)
Homemaker	25 (16.1)	37 (23.9)
Student	26 (16.8)	15 (9.7)
Marital status
Ever married	117 (75.5)	124 (80.0)	0.34
Never married	38 (24.5)	31 (20.0)
Residence
Within the state*	26 (16.8)	25 (16.2)	0.88
Outside the state	129 (83.2)	130 (83.8)

# Education based on International Standard Classification of Education (primary - class 1 to 5, secondary - class 6 to 12, tertiary - diploma, graduates, and master’s degrees). * Within state represents Puducherry and outside denotes all other neighboring states

Table 2

Baseline clinical and behavioral characteristics of the study participants enrolled in the trial (N=310)

Characteristics	Intervention group (N=155)n (%)	Control group(N=155)n (%)	P
Current tobacco use$
Yes	37 (23.9)	29 (18.7)	0.27
No	118 (76.1)	126 (81.3)
Current alcohol use@
Yes	45 (29.0)	40 (25.8)	0.52
No	110 (71.0)	115 (74.2)
HIV status
Positive	7 (4.5)	11 (7.1)	0.42
Negative	148 (95.5)	144 (92.9)
Type of tuberculosis (TB)
Smear-positive TB	59 (38.1)	57 (36.8)	0.31
Smear-negative TB	17 (11.0)	10 (6.5)
Extrapulmonary TB	79 (51.0)	88 (56.8)
Category of treatment
New (Category 1)	143 (92.3)	135 (87.1)	0.14
Previously treated (Category 2)	12 (7.7)	20 (12.9)
Comorbidity
No comorbidity	125 (80.6)	119 (76.8)
Diabetes mellitus	15 (9.7)	23 (14.8)	0.24
Hypertension	4 (2.6)	11 (7.1)
Renal disorders	6 (3.9)	5 (3.2)
Others^	6 (3.9)	4 (2.6)

$ - history of tobacco use in the past 1 year. @ - history of alcohol use in the past 1 year. ^ - Others included bronchial asthma, hepatic dysfunction, coronary vascular disease, and psychiatric disorder

Failure to initiate treatment

The intention-to-treat analysis showed that 14 (9.0%) and 28 (18.1%) of the 155 participants randomized into intervention and control arms, respectively, did not initiate TB treatment by the end of 14 days, and hence were lost to follow-up prior to treatment initiation. The absolute risk difference was 9.0% (95% CI [1.5, 16.5], P = 0.01). Mobile voice call interventions to 11 patients would prevent one PTLFU. The perprotocol analysis revealed similar results where participants in the control arm were at a significantly greater risk of loss to follow-up prior to treatment initiation than patients in the intervention arm (13.0% vs. 4.7%). The absolute risk difference was 8.3%, (95% CI [1.8, 14.7], P = 0.01) [Table 3]. Multivariable analysis showed that participants in the intervention arm had 0.5 (95% CI [0.3, 0.9]) times lower risk of being lost-to follow-up before treatment (P value = 0.03) after adjusting for other factors [Suppl Table 1].

Table 3

Comparison of outcomes between the intervention and the control group for initiation of treatment and time delays using intention-to-treat analysis

Outcomes	Intervention group n (%)	Control group n (%)	P
Proportion Loss to follow-up before treatment
Perprotocol analysis	7/148 (4.7%)	19/146 (13.0%)	0.01
Intention-to-treat analysis	14/155 (9.0%)	28/155 (18.1%)	0.01
Duration between diagnosis and treatment initiation (in days)	11 (9-13)	13 (10-15)	0.23
Duration between referral and treatment initiation (in days)	2 (2-3)	4 (2-5)	<0.001

Supplementary Table 1

Multivariable regression for determinants of pretreatment loss to follow-up among TB patients diagnosed in tertiary care hospital, Puducherry (n = 310)

Characteristics	Treatment not initiatedn (%)	Treatment initiatedn (%)	Unadjusted risk ratio (95% CI)	P	Adjusted risk ratio* (95% CI)	P
Age-group (in years)
0-14	2 (15.4)	11 (54.6)	1.6 [0.4, 7.5]	0.53	2.1 [0.5, 8.9]	0.32
15-24	5 (9.4)	48 (90.6)	Ref		1
25-34	6 (11.1)	48 (88.9)	1.2 [0.4, 3.6]	0.78	0.8 [0.3, 2.0]	0.68
35-44	11 (17.7)	51 (82.3)	1.9 [0.7, 5.1]	0.21	1.0 [0.4, 2.8]	0.94
45-54	7 (10.0)	63 (90.0)	1.1 [0.4, 3.1]	0.92	0.6 [0.2, 2.0]	0.42
55-64	9 (20.9)	34 (79.1)	2.2 [0.8, 6.1]	0.12	1.3 [0.4, 3.7]	0.68
65 and above	2 (13.3)	13 (86.7)	1.4 [0.3, 6.6]	0.66	0.7 [0.2, 2.7]	0.59
Group
Intervention arm	14 (9.0)	141 (91.0)	0.5 [0.3, 0.9]	0.02	0.5 [0.3, 0.9]	0.03
Control arm	28 (18.1)	127 (81.9)	Ref		Ref
Gender
Male	36 (16.8)	179 (83.3)	2.7 [1.2, 6.1]	0.02	2.4 [1.0, 6.0]	0.05
Female	6 (6.3)	89 (93.7)	Ref		1
Education#
Primary or less	26 (22.4)	90 (77.6)	2.7 [0.9, 7.3]	0.05
Secondary	12 (8.2)	134 (91.8)	1.0 [0.3, 2.9]	0.98
Tertiary	4 (8.3)	44 (91.7)	Ref
Occupation
Employed	24 (15.7)	129 (84.3)	1.6 (0.7, 3.8]	0.26
Unemployed	8 (14.8)	46 (85.2)	1.5 [0.6, 4.1]	0.40
Student	6 (9.7)	56 (90.3)	Ref
Housewife	4 (9.8)	37 (90.2)	1.0 [0.3, 3.4]	0.99
Marital status
Ever married	35 (14.5)	206 (85.5)	1.4 [0.7, 3.1]	0.36	1
Never married	7 (10.1)	62 (89.9)	Ref		0.7 [0.3, 1.8]	0.44
Residence
Within the state	5 (9.8)	46 (90.2)	Ref		1
Neighboring districts	16 (9.9)	146 (90.1)	1.0 [0.4, 2.6]	0.99	0.9 [0.3, 2.3]	0.77
Others*	21 (21.7)	76 (78.3)	2.2 [0.9, 5.5]	0.09	1.9 [0.7, 5.1]	0.17
Current tobacco user
Yes	15 (22.7)	51 (77.3)	2.1 [1.2, 3.6]	0.01	2.4 [1.2, 4.8]	0.02
No	27 (11.1)	217 (88.9)	Ref		1
Current alcohol user
Yes	13 (15.3)	72 (84.7)	1.2 [0.6, 2.2]	0.58	0.6 [0.3, 1.3]	0.21
No	29 (12.9)	196 (87.1)	Ref		1
HIV status
Positive	4 (22.2)	14 (77.8)	1.7 [0.7, 4.3]	0.25	1.4 [0.5, 3.6]	0.54
Negative	38 (13.0)	254 (87.0)	Ref		1
Type of tuberculosis (TB)
Smear-positive TB	14 (12.1)	102 (8.9)	1.6 [0.4, 6.7]	0.50	1.2 [0.2, 5.6]	0.84
Smear-negative TB	2 (7.4)	25 (92.6)	Ref		1
Extrapulmonary TB	26 (15.6)	141 (84.4)	2.1 [0.5, 8.4]	0.29	1.7 [0.4, 7.2]	0.48
Category of treatment
New (Category 1)	27 (11.8)	201 (88.2)	Ref		1
Previously treated (Category 2)	15 (18.3)	67 (81.7)	1.5 [0.9, 2.7]	0.14	1.4 [0.8, 2.4]	0.30

* Adjusted analysis conducted with modified Poisson regression

The reasons for noninitiation were documented for 7 and 16 patients in the intervention and control groups, respectively. In the intervention arm, the reasons were hospitalization elsewhere, nonavailability of PC-13 box (weight-based treatment box for children with TB), nonavailability of alternate drugs for a patient with hepatotoxicity, loss of referral slip, unable to travel, and visiting different PHIs for treatment. Among the control group, 10 out of 19 PTLFU participants primarily were not aware of the disease condition or the necessity of starting the treatment. Other reasons in the control arm were hospitalization (n = 3), inability to travel (n = 2), seeking care from private practitioner (n = 3), and the perception that no further treatment is required (n = 1).

Delay in treatment initiation

The overall time delay between diagnosis and treatment initiation was lower in the intervention group (11 days) than in the control arm (13 days), but the difference was not statistically significant (P = 0.23). However, the median time gap between referral from tertiary care institute and treatment initiation at PHI was significantly lesser (P < 0.001) in the intervention arm (2 days) compared with the control arm (4 days) as shown in Table 3.

Discussion

To our knowledge, this is the first study from India to have assessed the effectiveness of mobile voice call on reducing PTLFU among TB patients referred for anti-TB treatment from a tertiary care center. This study found that mobile voice call reminders reduced the PTLFU by 50% compared with the conventional referral system. The mobile voice call reminders were also beneficial in reducing delays in initiation of TB treatment.

The results of this study are consistent with the findings of the study from Cambodia where the introduction of mobile voice call reminders improved the retention of referred TB patients compared with previous cohorts.[20] Other than the study from Cambodia, no other study has assessed the effectiveness of mobile call reminders on PTLFU among TB patients. A study from South Africa reported that tracking of referred TB patients by community health workers (CHWs) through patient house visits improves TB treatment initiation rate.[24] Hence, both mobile voice call reminders and tracking through CHWs are potential interventions to reduce PTLFU. In India, about one fourth of pulmonary TB patients and nearly half of the extrapulmonary TB patients are diagnosed in tertiary care teaching hospitals. It is known that referral of TB patients for treatment initiation across the districts results in considerable PTLFU.[19] In 2018, the NTP addressed the issues with tracking of TB patients by strengthening NIKSHAY, an online TB patient notification platform. The patient diagnosed at any facility is notified on the NIKSHAY, and the portal alerts the STS of the PHI based on the address provided by the patient. Thus, it helps the health care providers to reach out to the patient and initiate TB treatment. However, because of deficiencies in recording the address, such tracking systems are not functioning to its potential. Also, the system does not provide any alert to TB patients for initiating the treatment. The mHealth (mobile health) interventions such as mobile phone reminders to patients and electronic tracking tool (M-TRACK) tried in program setting to reduce LTFU from care among HIV patients showed 80% reduction in PTLFU.[25] Thus, mobile voice call reminder seems to be a simple, feasible, and low-cost intervention to adopt by the RNTCP because about 80% of TB patients possess mobile phone and the call rates in India are very less.

A previous study done in the same setting had shown that only two thirds of the diagnosed TB patients are referred for treatment initiation, and there was a substantial delay between the diagnosis and the referral.[26] Although the mobile call reminders reduced the delay between the patient referral and the treatment initiation, there was no significant reduction in the overall delay between diagnosis and treatment initiation. This is rightly so, as the mobile voice call reminders were given only after referring the patient for treatment initiation. As the delay between diagnosis and referral is relatively longer and did not differ between the study groups, the intervention did not have a positive effect on overall delay between the diagnosis and the treatment initiation. This long delay is expected because the patient needs to visit the tertiary teaching hospital for collecting the referral for treatment initiation. However, programmatically it is important to reduce the overall delay, and similar mHealth interventions can be tried to expedite the process of referral once the patient is diagnosed with TB.

The study has several strengths. First, this randomized control trial was embedded within the routine program setting conducted using the existing resources, and thus reflects the ground reality in the control group. Hence, the low rates of PTLFU in the intervention group compared with control group can be attributed to the mobile voice call reminders. Second, there was no selection bias because about 98% of the eligible participants consented to take part in the study. Third, the dropout rates were minimal and similar between the two groups and hence there was less chance of attrition bias. Fourth, both intention-to-treat and perprotocol analyses were conducted, which reflect the effectiveness of mobile voice call reminders in programmatic and controlled conditions, respectively.

The study has a few limitations. First, the status of treatment initiation among referred patients was self-reported by the TB patient and was not validated with the information in the TB treatment registers. Hence, we failed to account for potential social desirability bias in reporting the status of treatment initiation. However, this might not have affected the estimated difference between the groups as the same methodology was used for ascertainment in both the study groups. Second, the duration of follow-up was limited to 14 days after the referral. It is possible that some patients in either group could have enrolled for treatment beyond 14 days. Third, only those patients who came to collect their referral letters from the hospital were included in the study. Those patients who might have been lost to follow-up prior to receipt of the referral letter were not included. This needs further study. Fourth, we did not record the process of intervention such as the number of calls made per each participant prior to successful receipt of the call, the cost of each call, and the duration of the call. Last, the investigator was not blinded about the allocation. Because the same researcher provided the intervention and ascertained the outcomes, the possibility of ascertainment bias could not be eliminated.

The study has important implications. First, with about 80% of the TB patients having access to mobile phones and 98% of them being ready to register for mHealth interventions, RNTCP should seriously consider implementing such interventions for improved patient tracking and follow-up. Second, the study showed mobile call reminders to be beneficial in reducing the PTLFU and also the duration between receipt of referral and initiation of treatment. However, in the current study, the study investigator who is not an RNTCP staff was delivering the intervention. Thus, the feasibility and effectiveness of the mobile call reminders through the use of existing RNTCP staff in the tertiary care hospitals need to be explored. Third, there is high LTFU between the patients diagnosed and receiving the referral letters for treatment initiation in the teaching hospitals. Thus, similar mobile call reminder interventions can be explored as a potential strategy to reduce the dropout between diagnosis and receipt of referral.

Conclusion

The mobile call reminders to TB patients reduced the PTLFU and delays in treatment initiation. The national program needs to explore the feasibility and effectiveness of delivering mobile call reminders with the existing manpower.

The study was approved by the Institute Ethics Committee of the Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry (reference number: JIP/IEC/SC/2014/8/633)

Trial registration

This trial was provisionally submitted to the Clinical Trials Registry - India (ICMR-NIMS) vide reference number REF/2015/03/008586.

Data availability statement

The data that support the findings of this study are available in the following link: https://tinyurl.com/h3vyewxx

Financial support and sponsorship

This study was supported by the Operational Research grant from the Puducherry State TB Operational Research Committee for the conduct of the study.

Conflicts of interest

There are no conflicts of interest.