Development and Initial Validation of a Frontline Health Worker mHealth Assessment Platform (MEDSINC®) for Children
Barry A Finette1,2, Megan McLaughlin1, Samuel V Scarpino3
1THINKMD, Inc., Burlington, Vermont.
Insights
A mobile health platform, MEDSINC, helps frontline health workers in low- and middle-income countries accurately assess and triage children, potentially preventing millions of deaths from treatable conditions.
Area of Science:
- Digital Health
- Pediatric Health
- Global Health
Background:
- Millions of young children in low- and middle-income countries (LMICs) die annually from preventable conditions.
- Early clinical assessment and intervention are crucial for reducing child mortality in LMICs.
Purpose of the Study:
- To develop and validate a mobile health (mHealth) platform, MEDSINC, for frontline health workers (FLWs) in LMICs.
- To assess the accuracy, usability, and acceptability of MEDSINC for pediatric clinical risk assessment and triage.
Main Methods:
- MEDSINC, a web-based platform using Bayesian logic, was developed for FLWs to assess children aged 2-60 months.
- Validation involved 861 children and 49 FLWs across Burkina Faso, Ecuador, and Bangladesh.
- FLW assessments using MEDSINC were blindly compared to local health professional (LHP) assessments.
Main Results:
- MEDSINC-based assessments by FLWs showed high specificity correlation (84%-99%) with LHPs.
- Triage recommendations from MEDSINC were highly correlated with LHP recommendations.
- Usability and feasibility testing yielded positive feedback from both FLWs and LHPs.
Conclusions:
- The MEDSINC platform demonstrates potential to enhance pediatric healthcare capacity in LMICs.
- Improved FLW accuracy in assessing and triaging children can facilitate timely, life-saving interventions.
- mHealth solutions like MEDSINC are vital for improving child survival rates in resource-limited settings.
Abstract:
Approximately 3 million children younger than 5 years living in low- and middle-income countries (LMICs) die each year from treatable clinical conditions such as pneumonia, dehydration secondary to diarrhea, and malaria. A majority of these deaths could be prevented with early clinical assessments and appropriate therapeutic intervention. In this study, we describe the development and initial validation testing of a mobile health (mHealth) platform, MEDSINC®, designed for frontline health workers (FLWs) to perform clinical risk assessments of children aged 2-60 months. MEDSINC is a web browser-based clinical severity assessment, triage, treatment, and follow-up recommendation platform developed with physician-based Bayesian pattern recognition logic. Initial validation, usability, and acceptability testing were performed on 861 children aged between 2 and 60 months by 49 FLWs in Burkina Faso, Ecuador, and Bangladesh. MEDSINC-based clinical assessments by FLWs were independently and blindly correlated with clinical assessments by 22 local health-care professionals (LHPs). Results demonstrate that clinical assessments by FLWs using MEDSINC had a specificity correlation between 84% and 99% to LHPs, except for two outlier assessments (63% and 75%) at one study site, in which local survey prevalence data indicated that MEDSINC outperformed LHPs. In addition, MEDSINC triage recommendation distributions were highly correlated with those of LHPs, whereas usability and feasibility responses from LHP/FLW were collectively positive for ease of use, learning, and job performance. These results indicate that the MEDSINC platform could significantly increase pediatric health-care capacity in LMICs by improving FLWs' ability to accurately assess health status and triage of children, facilitating early life-saving therapeutic interventions.
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