‘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.

Programmatic outcomes and impact of rapid public sector antiretroviral therapy expansion in adults prior to introduction of the WHO treat‐all approach in rural Eswatini

“…Other studies showed that programmes applying physical defaulter tracing had higher 12‐month retention on ART (80.0% vs . 75.8%) and programmes using phones in combination interventions had reduced loss to care . Sensitivity analysis, however, suggested a temporary increase in risk of attrition in 2008, the year when HIV‐TB care was decentralised through mobile doctor‐led teams.…”

Review of patients perspective’s of m-health adoption factors in the developing world. Development of a framework

“…Research methods used in the 54 reviewed resources were: 25 qualitative papers , 9 surveys [42][43][44][45][46][47][48][49][50], 7 mixed methods [51][52][53][54][55][56][57], 4 experimental [52,[58][59][60], 3 usability assessments [8,61,62], 2 cohort studies [63,64], and 4 cross sectional studies [65][66][67][68]. Collectively they reported the spectrum of factors that affect patient adoption.…”

“…To participate in m-health services, patients need to be literate both in the traditional sense (able to read, write, and speak in their mother language), but also in a broader sense (able to understand the technical needs to effectively use a mobile device, and able to understand their health issues and treatment) [24,46]. In poor rural areas where education levels are often lower [42] people may require the assistance of a family or community member to understand the content of a message sent to them [56]. In general mhealth requires minimum literacy on the part of patients for its adoption [65], particularly when patients are appropriately trained to apply the technology [8, 24-26, 48, 49, 66].…”

A Proposed Framework of Factors Affecting Patient Adoption of mHealth in the Developing World.

“…Research methods used in the 54 reviewed resources were 25 qualitative papers [6,21,22,48,60,37,31,29,43,82,85,87,38,51,14,44,53,54,49,10,32,33,46,34,84], 9 surveys [7,8,45,4,16,13,23,28,18], mixed methods 7 [9,27,47,86,88,89,90], experimental 4 [19,26,36,91], 3 usability assessments [92,15,5], 2 cohort studies [11,41], and 4 were cross sectional [17,<...>…”

“…It was suggested that an appropriate age target for minimally educated women to use mhealth would be 17 to 63 years [15,29,33] but in certain parts of the developing world older women were more likely to own and use a mobile phone for m-health than younger women [47], and in South Africa women are the dominant users [60]. Urban women found evening m-health services more convenient and rural women preferred daytime services [14,38,90].…”