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ORIGINAL ARTICLE
Year : 2021  |  Volume : 65  |  Issue : 1  |  Page : 34-38  

The effect of a mhealth intervention on anti-tuberculosis medication adherence in Delhi, India: A quasi-experimental study


1 Junior Resident, Department of Community Medicine, Maulana Azad Medical College, New Delhi, India
2 Director Professor, Department of Community Medicine, Maulana Azad Medical College, New Delhi, India
3 Senior Resident, Department of Community Medicine, Maulana Azad Medical College, New Delhi, India
4 State Programme Officer, Chest Clinic (TB), Lok Nayak Hospital, New Delhi, India

Date of Submission14-Jul-2020
Date of Decision18-Dec-2020
Date of Acceptance21-Jan-2021
Date of Web Publication20-Mar-2021

Correspondence Address:
Saurav Basu
Department of Community Medicine, Maulana Azad Medical College, New Delhi
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijph.IJPH_879_20

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   Abstract 


Background: Suboptimal adherence to anti-tuberculosis medication in patients is associated with adverse treatment outcomes including treatment failure, relapse, and emergence of drug resistance. Objectives: We conducted the present study with the objectives of evaluating the effectiveness of a mHealth package on the medication adherence of patients with tuberculosis (TB) on antitubercular (directly observed treatment short-course [DOTS]) treatment. Methods: We conducted Quasi-experimental study at six DOTS centers of Delhi among 220 newly diagnosed TB patients. We included adult TB patients (18 years and above) who were on DOTS therapy ≥30 days, had access to a mobile phone and were able to read messages and receive calls. We excluded patients with impaired hearing, blindness and those on non-DOTS therapy or having multidrug-resistant/extensively drug-resistant TB. Participants in the intervention group received amHealth package for 90 days. The medication adherence of the study participants was measured using Morisky, Green, and Levine Adherence Scale. Results: A total of 130 men and 90 women were recruited for the study. Occupational interference and forgetfulness were the most common reasons for medication nonadherence in the patients. In the intervention group, the medication adherence to antitubercular medication (daily DOTS regimen) was 85.5% at baseline which increased to 96.4% at endline (postintervention) (P = 0.004). No significant change was observed in the control group (P = 0.328). The increase in adherence was observed across the following subgroups: age, gender, education, and Socioeconomic status. Conclusions: The mHealth intervention in TB patients was effective in improving the adherence to DOTS therapy.

Keywords: Directly observed treatment short-course, India, medication adherence, mHealth, tuberculosis


How to cite this article:
Santra S, Garg S, Basu S, Sharma N, Singh MM, Khanna A. The effect of a mhealth intervention on anti-tuberculosis medication adherence in Delhi, India: A quasi-experimental study. Indian J Public Health 2021;65:34-8

How to cite this URL:
Santra S, Garg S, Basu S, Sharma N, Singh MM, Khanna A. The effect of a mhealth intervention on anti-tuberculosis medication adherence in Delhi, India: A quasi-experimental study. Indian J Public Health [serial online] 2021 [cited 2021 Apr 16];65:34-8. Available from: https://www.ijph.in/text.asp?2021/65/1/34/311528




   Introduction Top


Tuberculosis (TB) is an air-borne infection caused by Mycobacterium tuberculosis which causes 1.4 million deaths a year representing one of the top ten causes of death worldwide.[1] India accounts for almost a quarter (~23%) of the global burden of TB with an estimated 10 million incident cases.[2] The failure to adequately treat TB increases the risk of treatment failure and premature death, that accounts for 80% of the disability-adjusted life years lost on account of the disease.[3]

Adherence to anti-tubercular medication for 6 months or until treatment completion is essential for achieving complete cure in drug-sensitive tuberculosis cases.[4] However, suboptimal adherence to anti-tubercular treatment (ATT) significantly accentuates the risk of treatment failure and drug resistance.[5] Moreover, it is well-established that factors like the long duration of treatment, potential side-effects of ATT, discontinuation of therapy by patients on perceived well-being, and out-of-pocket expenses associated with inhibition of timely drug refill can undermine medication adherence.[6],[7],[8]

Under the Revised National Tuberculosis Control Program (RNTCP) (now National Tuberculosis Elimination Program [NTEP]), India is the second-largest provider of the Directly observed treatment short-course (DOTS) in the world.[2] Adherence support via direct observation was the hallmark of the RNTCP until 2018 with the patient taking the DOTS medication in the presence of the DOTS provider during the intensive phase for 2 months in new and 3 months in previously treated cases. The RNTCP (now NTEP) since 2018 has transitioned to a daily medication regimen from a thrice-weekly regimen with a variable refill duration.[9] The daily regimen has the advantage of higher effectiveness and enhanced patient convenience when coupled with a longer refill duration, but it may lack daily direct observation of drug intake during the intensive phase, reflecting a need for deploying alternative adherence monitoring and support mechanisms.

mHealth refers to the application of the mobile telephonic platform enabling support for public health and clinical practice with scope for low-cost, ubiquitous, and universal access. The use of text messages and voice calls to improve adherence behavior has proven efficacy in chronic conditions, but the evidence in TB patients,[10],[11] especially in the Indian context is limited.

We conducted the present study with the objectives of evaluating the effectiveness of a mHealth package on the medication adherence of patients with TB on antitubercular (DOTS) treatment.


   Materials and Methods Top


Design and participants

We conducted a quasi-experimental study during an 8-month study period during 2018–19 at six DOTS centers under the jurisdiction of a major hospital in Central Delhi. The intervention and the control sites included three DOTS centers each that were selected purposively, being separated from each other by a distance of at least three kilometers each. The study design precluded any chances of contamination from the sharing of the intervention contents and was also necessary for administrative reasons.

We enrolled consenting adult TB that were: (a) on DOTS therapy for a minimum period of 30 days and a maximum of 90 days, (b) had access to a mobile phone (c) were able to read messages and receive calls on their mobile phones. We excluded patients with impaired hearing, blindness and those on non-DOTS therapy or diagnosed with multidrug-resistant/extensively drug-resistant-TB.

Study outcomes

The primary outcome of this study was adherence to TB treatment assessed with the 4-item Morisky-Green-Levene adherence scale (MGLS).[12]

Outcome measurement

Nonadherence to anti-tuberculosis medications was defined as a score <4 as per the MGLS, i.e., if the response to at least one of the four questions was answered as “yes” by the participant. The recall period was the previous 15 days. The outcomes were ascertained at baseline during the study enrolment and subsequently, after 90 days of intervention.

Sample size and sampling method

We enrolled a total of 110 patients with TB in both the intervention and control groups. Based on a previous study, the expected adherence to DOTS therapy in drug-sensitive TB cases is 84%.[13] The sample size was adequate at 80% power to detect a postintervention enhancement in medication adherence ≥10% compared to the preintervention levels, while also accounting for up to 10% attrition. The participants were selected by the consecutive sampling method from each of the DOTS centers that were visited on a rotation basis.

Standard care

TB patients (without HIV infection) under the daily regimen are instructed to take their anti-tubercular medications regularly at the time of refill collection by the DOTS providers.

Intervention

We developed a mHealth package comprising of 30 unique text-messages in the local language, Hindi and a weekly real-time two-way phone call that lasted for approximately 10 min. The mHealth package duration was 90 days comprising once-daily text message (90 text-messages sent in total) and once a week voice call (12 voice calls in total). The messages and calls motivated patients to persist with their anti-tubercular medications, provided reminders for adherence to medications and also addressed patient concerns regarding potential drug-related adverse effects. The package contents were pretested among 25 TB patients at a DOTS center in a secondary care hospital in Delhi to assess message readability and comprehension. Participants of the control group did not receive the mHealth package and instead continued to receive standard care.

Statistical analysis

The data were analyzed using IBM SPSS Version 25 replace with IBM SPSS Statistics for Windows, Version 25.0 (Armonk, NY: IBM Corp). Categorical variables were expressed in frequency and proportion and continuous variables as mean and standard deviation. Association between categorical variables was assessed using the Chi-square test of independence. We further compared the parameters to assess: (1). Pre-intervention or baseline differences in the intervention and control group, (2). Postintervention difference between the intervention and control group (between-group differences), (3) Pre- and post-intervention differences within both the intervention and control group (within-group differences). The McNemar's test was applied to test for within-group (paired) differences for categorical outcomes, and the Chi-square difference in proportion test for between-group (unpaired) differences for categorical outcomes. A value of P ≤ 0.05 was considered statistically significant.

Ethics: We obtained ethical approval from the Institutional Ethics Committee. All the participations provided written and informed consent. The study was prospectively registered with the clinical trial registry of India (CTRI/2018/08/015306).


   Results Top


Participant characteristics

A total of 130 men and 90 women were recruited for the study [Figure 1]. Patients excluded on not meeting selection criteria were 10 patients that were illiterate and another seven patients who did not own a mobile phone. Furthermore, 68 patients also refused to participate citing either lack of time, perceived lack of benefit, and nondisclosure of mobile phone numbers due to concerns over privacy.
Figure 1: Flow-diagram of the quasi-experimental study (n = 220)

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The mean age of the study participants was 45.7 (±9.6) years. One hundred ten patients in each group were enrolled from the six DOTS center constituting the control and intervention groups, respectively. Majority (45%) of the participants belonged to the lower middle class.

At baseline, the intervention group had a significantly higher proportion of participants who were male, belonging to the Hindu religion, vegetarian by diet, and residing in their current residence for >10 years compared to the control group that had more female patients, Muslims by religion and meat containing diet. The sociodemographic and clinical characteristics of the participants in both the groups were comparable in terms of age, SES, BMI, and educational status [Table 1].
Table 1: Characteristics of participants at baseline (n=220)

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Medical adherence in patients with tuberculosis at baseline: High adherence, medium, and low adherence to the anti-tubercular DOTS regimen were observed in 188 (85.45%), 9 (8.63%), and 13 (5.9%), respectively, with similar adherence rates observed in both the intervention and control groups. On dichotomizing adherence status, high medication adherence was present in 188 (85.45%) and low in 32 (14.5%) participants [Table 2].
Table 2: Medical adherence to anti-tubercular treatment regimen at baseline

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Reasons for medication nonadherence

Among the participants reporting low medication adherence (n = 32), the male gender was the only sociodemographic characteristic that was significantly associated with medication nonadherence (P < 0.001). The most common reasons attributed to nonadherent behavior were occupational interference (31.2%), forgetfulness (25%), lack of knowledge of DOTS (12.5%), feeling better (9.3%), and nondisclosure to the family (6.2%) (n = 32).

Effectiveness of the intervention

The mHealth package phone call attendance was regular in 100 (91%) subjects while 102 (92.7%) reported regularly reading the text messages. The proportion of participants' adherent to DOTS in the intervention group increased from 85.5% at baseline to 96.4% at endline, postintervention. We found an increase in adherence across the following subgroups: age, gender, education, and SES [Table 3].
Table 3: Medication adherence of TB patients after mHealth intervention (n=218)

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   Discussion Top


The present study conducted in six DOTS centers located in Delhi, India found a comprehensive health package was effective in enhancing medication adherence among patients with TB on DOTS therapy, compared to standard care. The improvement in adherence was observed across different subgroups including patients with a limited educational background.

A study from a Deccan state in India by Narreddy et al. reported 95% of TB patients receiving text-message and Interactive Voice Response packages were completely adherent to their prescribed medication.[14] In South Africa, Wagstaff et al. demonstrated SMS text-reminders promoted the TB testers to return to clinics.[15] Other African studies have also reported small gains in DOTS adherence, treatment cure rates and clinic attendance attained through text-message interventions.[16]

There are several limitations to the study. First, the sociodemographic characteristics of the intervention and control group differed significantly due to the divergent demographic composition of the respective catchment areas of the selected DOTS centers. Some of these factors could be associated with medication adherence behaviors, although, the educational status of the participants in both groups was comparable. Moreover, more than two-thirds of the participants were educated up-to middle school only, suggesting the utility and relevance of the intervention in real-world health settings of the developing world. Nevertheless, in this study, participants lacking basic or digital literacy were excluded, limiting the generalizability of the study findings in probably the most vulnerable patient subgroups. However, the evidence generated in this study provides proof of the concept of the deployment and acceptability of a comprehensive mHealth package among patients with TB in India.

Second, we did not prospectively follow-up the participants to determine their treatment outcomes. Third, the possibility of overestimation of the adherence rates due to an element of socialdesirability bias cannot be ruled out. Fourth, replicating the mHealth model applied in the present study can be a challenge for developing world TB control programs due to issues of feasibility and cost. The real-time audio call component of the present study that enabled two-way communication between the patient and a highly qualified provider may not be viable in resource-constrained settings. Finally, adherence is a dynamic process that varies with the time elapsed since diagnosis, especially in chronic diseases requiring long-term drug intake, indicating the need for more frequent monitoring.[17]


   Conclusions Top


A mHealth intervention is a useful mechanism for the provision of adherence support to TB patients, especially in a daily regimen scenario, in the absence of direct observation of treatment. Future studies should explore the role of divergent mHealth packages that also factor the intervention feasibility and cost-effectiveness.

Financial support and sponsorship

Funding source is National Tuberculosis Elimination Program, Government of National Capital Territory, Delhi.

Conflict of interest

There are no conflicts of interest.



 
   References Top

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WHO. Global tuberculosis report. Geneva: World Health Organization; 2018.  Back to cited text no. 1
    
2.
Central TB Division. India TB Report 2018. New Delhi: RNTCP, Central TB Division; Directorate General of Health Services, Ministry of Health and Family Welfare, Government of India; 2018.  Back to cited text no. 2
    
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Central TB Division, MOHFW, GOI. TB India 2012 Status Report. New Delhi: Central TB Division, MOHFW, GOI; 2012. p. 185.  Back to cited text no. 3
    
4.
Houben RM, Menzies NA, Sumner T, Huynh GH, Arinaminpathy N, Goldhaber-Fiebert JD, et al. Feasibility of achieving the 2025 WHO global tuberculosis targets in South Africa, China, and India: A combined analysis of 11 mathematical models. Lancet Glob Heal 2016;4:e806-15.  Back to cited text no. 4
    
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Ali AO, Prins MH. Disease and treatment-related factors associated with tuberculosis treatment default in Khartoum State, Sudan: A case-control study. East Mediterr Health J 2017;23:408-14.  Back to cited text no. 5
    
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Sabatâe E. Adherence to long-term therapies: Evidence for action. 1st ed. Geneva: World Health Organization; 2003.  Back to cited text no. 6
    
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Herrero MB, Ramos S, Arrossi S. Determinants of non adherence to tuberculosis treatment in Argentina: Barriers related to access to treatment. Rev Bras Epidemiol 2015;18:287-98.  Back to cited text no. 7
    
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Woimo TT, Yimer WK, Bati T, Gesesew HA. The prevalence and factors associated for anti-tuberculosis treatment non-adherence among pulmonary tuberculosis patients in public health care facilities in South Ethiopia: A cross-sectional study. BMC Public Health 2017;17:269.  Back to cited text no. 8
    
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Chaudhuri AD. Recent changes in technical and operational guidelines for tuberculosis control programme in India-2016: A paradigm shift in tuberculosis control. J Assoc Chest Physicians 2017;5:1-9.  Back to cited text no. 9
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Hall SC, Fottrell E, Wilkinson S, Byass P. Assessing the impact of mHealth interventions in-and middle-income countries _ what has been shown to work? Glob Health Action 2014;7:25606.  Back to cited text no. 10
    
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Barclay E. Text messages could hasten tuberculosis drug compliance. Lancet 2009;373:15-6.  Back to cited text no. 11
    
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Morisky DE, Green LW, Levine DM. Concurrent and predictive validity of a self-reported measure of medication adherence. Med Care 1986;24:67-74.  Back to cited text no. 12
    
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Bagchi S, Ambe G, Sathiakumar N. Determinants of poor adherence to anti-tuberculosis treatment in mumbai, India. Int J Prev Med 2010;1:223-32.  Back to cited text no. 13
    
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Narreddy S, Trivedi A, Farheen A, Chadha S. Digitalization leverages notification and treatment adherence of tuberculosis patients in private sector: Pilot study from India. Open Forum Infect Dis 2016;1:S1-68.  Back to cited text no. 14
    
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Wagstaff A, van Doorslaer E, Burger R. SMS nudges as a tool to reduce tuberculosis treatment delay and pretreatment loss to follow-up. A randomized controlled trial. PLoS One 2019;14:e0218527.  Back to cited text no. 15
    
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Nglazi MD, Bekker LG, Wood R, Hussey GD, Wiysonge CS. Mobile phone text messaging for promoting adherence to anti-tuberculosis treatment: A systematic review. BMC Infect Dis 2013;13:566.  Back to cited text no. 16
    
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Basu S, Garg S, Sharma N, Singh MM. Improving the assessment of medication adherence: Challenges and considerations with a focus on low-resource settings. Ci Ji Yi Xue Za Zhi 2019;31:73-80.  Back to cited text no. 17
    


    Figures

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    Tables

  [Table 1], [Table 2], [Table 3]



 

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