Peer Group Focused eHealth Strategies to Promote HIV Prevention, Testing, and Care Engagement.

PURPOSE OF REVIEW: Electronic communication platforms are increasingly used to support all steps of the HIV care cascade (an approach defined as eHealth). Most studies have employed individual-level approaches in which participants are connected with information, reminders, or a healthcare worker. Recent growth in use of social media platforms, which create digital communities, has created an opportunity to leverage virtual peer-to-peer connection to improve HIV prevention and care. In this article, we describe the current landscape of peer group eHealth interventions in the HIV field, based on a review of published literature, an online survey of unpublished ongoing work, and discussions with practitioners in the field in an in-person workshop. RECENT FINDINGS: We identified 45 published articles and 12 ongoing projects meeting our inclusion criteria. Most reports were formative or observational; only three randomized evaluations of two interventions were reported. Studies indicated that use of peer group eHealth interventions is acceptable and has unique potential to influence health behaviors, but participants reported privacy concerns. Evaluations of health outcomes of peer group eHealth interventions show promising data, but more rigorous evaluations are needed. Development of group eHealth interventions presents unique technological, practical, and ethical challenges. Intervention design must consider privacy and data sovereignty concerns, and respond to rapid changes in platform use. Innovative development of open-source tools with high privacy standards is needed.

Optimising mHealth helpdesk responsiveness in South Africa: towards automated message triage.

In South Africa, a national-level helpdesk was established in August 2014 as a social accountability mechanism for improving governance, allowing recipients of public sector services to send complaints, compliments and questions directly to a team of National Department of Health (NDoH) staff members via text message. As demand increases, mechanisms to streamline and improve the helpdesk must be explored. This work aims to evaluate the need for and feasibility of automated message triage to improve helpdesk responsiveness to high-priority messages. Drawing from 65 768 messages submitted between October 2016 and July 2017, the quality of helpdesk message handling was evaluated via detailed inspection of (1) a random sample of 481 messages and (2) messages reporting mistreatment of women, as identified using expert-curated keywords. Automated triage was explored by training a naïve Bayes classifier to replicate message labels assigned by NDoH staff. Classifier performance was evaluated on 12 526 messages withheld from the training set. 90 of 481 (18.7%) NDoH responses were scored as suboptimal or incorrect, with median response time of 4.0 hours. 32 reports of facility-based mistreatment and 39 of partner and family violence were identified; NDoH response time and appropriateness for these messages were not superior to the random sample (P>0.05). The naïve Bayes classifier had average accuracy of 85.4%, with ≥98% specificity for infrequently appearing (<50%) labels. These results show that helpdesk handling of mistreatment of women could be improved. Keyword matching and naïve Bayes effectively identified uncommon messages of interest and could support automated triage to improve handling of high-priority messages.

Unpacking the performance of a mobile health information messaging program for mothers (MomConnect) in South Africa: evidence on program reach and messaging exposure.

Despite calls to address broader evidence gaps in linking digital technologies to outcome and impact level health indicators, limited attention has been paid to measuring processes pertaining to the performance of programs. In this paper, we assess the program reach and message exposure of a mobile health information messaging program for mothers (MomConnect) in South Africa. In this descriptive study, we draw from system generated data to measure exposure to the program through registration attempts and conversions, message delivery, opt-outs and drop-outs. Using a logit model, we additionally explore determinants for early registration, opt-outs and drop-outs. From August 2014 to April 2017, 1 159 431 women were registered to MomConnect; corresponding to half of women attending antenatal care 1 (ANC1) and nearly 60% of those attending ANC1 estimated to own a mobile phone. In 2016, 26% of registrations started to get women onto MomConnect did not succeed. If registration attempts were converted to successful registrations, coverage of ANC1 attendees would have been 74% in 2016 and 86% in 2017. When considered as percentage of ANC1 attendees with access to a mobile phone, addressing conversion challenges bring registration coverage to an estimated 83%-89% in 2016 and 97%-100% in 2017. Among women registered, nearly 80% of expected short messaging service messages were received. While registration coverage and message delivery success rates exceed those observed for mobile messaging programs elsewhere, study findings highlight opportunities for program improvement and reinforce the need for rigorous and continuous monitoring of delivery systems.