'M-TRACK' (mobile phone reminders and electronic tracking tool) cuts the risk of pre-treatment loss to follow-up by 80% among people living with HIV under programme settings: a mixed-methods study from Gujarat, India

Abstract

Background: In 2016, the National AIDS Control Programme (NACP) in Gujarat, India implemented an innovative intervention called 'M-TRACK' (mobile phone reminders once every week for four weeks after diagnosis and electronic patient tracking tool) to reduce pre-treatment loss to follow-up (LFU) among people living with HIV (PLHIV) in Vadodara district while other districts received standard of care.

Objectives: To assess the effectiveness of M-TRACK in reducing pre-treatment LFU (proportion of diagnosed PLHIV not registering for HIV care by four weeks after diagnosis) and to explore the implementation enablers and challenges from health care providers' and PLHIV perspective.

Methods: An explanatory mixed-methods study design was used wherein the quantitative phase (cohort study with two groups: Vadodara district exposed to M-TRACK and Rajkot district as unexposed) was followed by a qualitative phase (descriptive study involving group interview with 16 health care providers, personal interviews with two programme managers and telephonic interviews with 16 PLHIV). Data were collected during October 2016 to February 2017.

Results: During the pre-M-TRACK period (July-September 2016), the LFU proportion was similar [13% (25/191) in Vadodara; 15% (21/141) in Rajkot (p = 0.8)]. During the M-TRACK period (October-December 2016), LFU decreased to 4% (9/209) in Vadodara (exposed), whereas it remained similar at 16% (18/113) in Rajkot (unexposed) district (p = 0.02). PLHIV exposed to M-TRACK had an 80% lower risk of LFU (aRR 0.2; 95% CI: 0.1-0.5) compared with standard care, after adjusting for socio-demographics, time and clustering at district level. During interviews, M-TRACK was welcomed by both PLHIV and the counsellors. The latter felt it saved time by obviating the need for home visits and helped in documentation. Inconvenience of using landline phone available at the health facility, lack of budgets for reimbursement of mobile call expenses and internet connectivity problems were the key implementation challenges.

Conclusion: M-TRACK was highly effective in reducing the gap between diagnosis and treatment. It may be considered for scale-up after addressing the challenges noted.

Keywords: SORT IT; initial default; mHealth; operational research; pre-treatment attrition.

Figure 1.

Effect of M-TRACK implementation on ART registration in Vadodara district among PLHIV diagnosed during October 2016 to December 2016 (N = 209). M-TRACK = Mobile phone reminders and electronic tracking tool; PLHIV = people living with the human immunodeficiency virus; ART = antiretroviral therapy.

Figure 2.

Effect of M-TRACK implementation on pre-treatment loss to follow-up among PLHIV diagnosed in Vadodara (exposed) and Rajkot (unexposed) districts of Gujarat, India, during July–December 2016. Pre-M-TRACK χ² = 0.09 (p = 0.75) M-TRACK χ² = 4.75 (p value = 0.02). PLHIV = people living with the human immunodeficiency virus; M-TRACK = mobile phone reminders and electronic tracking tool; LFU = loss to follow-up.