Accepted for/Published in: JMIR Formative Research
Date Submitted: Jan 28, 2022
Date Accepted: Aug 23, 2022
Developing population health surveillance using mHealth in low-resource settings: A qualitative assessment and pilot evaluation
ABSTRACT
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. Clinical Trial: Not applicable
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.