Development and Initial Validation of a Frontline Health Worker mHealth Assessment Platform (MEDSINC) for Children 2-60 Months of Age.

Authors:
Barry A Finette
Barry A Finette
University of Vermont College of Medicine
United States
Megan McLaughlin
Megan McLaughlin
University of Toronto
Canada
Samuel V Scarpino
Samuel V Scarpino
Santa Fe Institute
Santa Fe | United States
Prof John Canning, PhD
Prof John Canning, PhD
The University of Technology Sydney
Professor
Photonics, Physics, Chemistry, materials, nanotechnology
Sydney, NSW | Australia
Michelle Grunauer
Michelle Grunauer
Universidad San Francisco de Quito
Dr. Enrique Teran, MD, PhD
Dr. Enrique Teran, MD, PhD
Universidad San Francisco de Quito
Professor
Quito | Ecuador
Edy Quizhpe
Edy Quizhpe
Instituto de Epidemiología y Salud Comunitaria "Manuel Amunárriz"

Am J Trop Med Hyg 2019 Jun;100(6):1556-1565

THINKMD, Inc., Burlington, Vermont.

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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Source
http://www.ajtmh.org/content/journals/10.4269/ajtmh.18-0869
Publisher Site
http://dx.doi.org/10.4269/ajtmh.18-0869DOI Listing
June 2019
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2.699 Impact Factor

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