Developing population health surveillance using mHealth in low-resource settings: A formative study focusing on rural Myanmar (Preprint)

BACKGROUND To develop an mHealth-based population health surveillance tool in an extremely rural, low-resource setting with minimal cellular infrastructure in Western Myanmar. OBJECTIVE To develop a mHealth-based tool for conducting population health surveillance in an extremely rural, low-resource setting in Western Myanmar. METHODS We employed an iterative design process to develop an mHealth-based population health surveillance tool for collecting census-related information. We conducted interviews with international consultants (nurse midwives) and local clinicians (nurses and physicians) in Myanmar. Our analytic approach was informed by the Systems Engineering Initiative for Patient Safety (SEIPS), work systems model to capture the multi-level user needs for developing health interventions, which was used to create a prototype data collection tool that was pilot tested in 33 villages to establish initial proof of concept. RESULTS We conducted 7 interviews with 5 participants who provided feedback regarding the core domains of the work system, including: environmental, organizational, sociocultural, technological, informational, task, and people-based considerations for adapting a mHealth data collection application. The mHealth tool was piloted in 33 villages, including census data from 11,945 people, for an initial proof of concept. Key considerations determined from the interviews involved: the need to devise strategies for dealing with the remote, mountainous physical environment; providing security-related features if phones were lost/stolen/confiscated; designing a simple form usable across multiple languages; designing for comprehension in a setting with low literacy levels; conveying the larger purpose of the data collection to community health workers and local people providing the health data to promote buy-in. CONCLUSIONS Findings related to key design considerations using a work systems lens may be informative to others developing technology-based solutions in extremely low resource settings. Future work will involve collecting additional health related data and evaluating the quality of the data collected. Our team established initial proof of concept for using a mHealth tool to collect census-related information in a low resource, extremely rural, low literacy environment. CLINICALTRIAL Not applicable