Utilizing mobile health and community informants to collect real-time health care data in extremely low resource environments

BACKGROUND: Mobile health provides promising opportunities to perform population surveillance in rural, impoverished, or unstable communities. The objective of this study was to test the efficacy and accuracy of data collected by community informants in extreme low-resource environments using electronic surveys and mobile phones. METHODS: We carried out a population-based, cross-sectional survey between October and November 2017 measuring access to health care and prenatal services for pregnant women in the Northern Region of Malawi. The survey was conducted by members of the community who received one day of training and volunteered to conduct a survey for each live birth that occurred within their predetermined catchment area. A study member audited less than 2% of survey responses, where community informant responses were compared to community member self-reports. RESULTS: A total of 915 survey responses were recorded by 21 community informants. These surveys recorded 621 live births and 4 cases of maternal mortality. This represents a maternal mortality rate of 0.64% (95% confidence interval (CI) = 0.2% to 1.6%), roughly equal to the United Nations Children's Fund (UNICEF) estimate from 2015 of 634 per 100 000 live births, or 0.63%. This survey captured 120 births by adolescent mothers aged 15-19 out of 673 responses about maternal age. This represents 17.8% (95% CI = 15.1% to 20.9%) of all births, slightly higher than the UNICEF estimate of 143 per 1000 live births (14.3%). Finally, 51.7% of women were recorded as attending 4 antenatal care visits (95% CI = 47.8% to 55.7%), consistent with the 2015-2016 Demographic and Health Survey (DHS) value of 51%. CONCLUSIONS: The use of cellular phones and electronic surveys by community informants allowed for the real-time capture of data in an area where access is limited by seasonally impassable roads and unreliable cell reception. The data recorded by the surveys is comparable to accepted statistics in several measures. Community reporting of health care data can provide an efficient method of monitoring extremely rural or hard to reach communities

Community health · Confidence interval · Environmental health · Health care · Live birth · Population · Postnatal Care · Pregnancy · Public health · Demography · Global Maternal and Child Health · ICT in Developing Communities · Medicine · Mobile Health and mHealth Applications · Nursing

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  Open Access•Sabera Turkmani, Rachel Smith et al.•PLOS Global Public Health•2023

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