GLOBAL DIGITAL HEALTH FORUM   WASHINGTON, D.C. - DECEMBER 4-6, 2017

Exploring Methodologies for Digital Tool Evaluation

  • Room: Treasury Room
Monday, December 04, 2017: 3:15 PM - 4:15 PM

Speaker(s)

Panelist
Andrea Fletcher
Lead Data Strategist
Cooper/Smith
Moderator
Dykki Settle
Global Program Leader, Digital Health
PATH
Panelist
Kelsey Alland
Johns Hopkins University
Panelist
Smisha Agarwal
Digital Health Consultant
World Health Organization

Description

Come explore three unique methodologies used to evaluate digital health interventions across the globe. The WHO digital health M&E guide represents collective learning from five years of engagement with development agencies working to introduce digital health projects, develop robust evaluations, and scale-up activities nationally and regionally. Based on this guide, the session will provide an overview of M&E methods and practical considerations for digital health projects at different stages of maturity. In the mCARE-II trial in Bangladesh, researchers at Johns Hopkins University conducted a 14,000 pregnancy randomized controlled trial to evaluate the impact of a digital health intervention on neonatal mortality.  This session will provide an overview of the study, including aims, intervention content, and primary outcomes. Findings will be shared from phase I, which assessed the quality of the government health workforce intervention implementation and was used to develop data monitoring procedures to improve real-time decision making, streamline reporting and facilitate a culture of data use amongst target workforces. Finally, Cooper Smith conducted a Discrete Choice Experiment in Malawi, in order to better understand data use incentives and how to prioritize investments in incentive programs for healthcare workers. This approach allows researchers to quantitatively measure perceived value and trade-offs between options provided to participants in simple survey form, which in turn allows policy makers to choose those factors that will most affect the desired outcome.


Track(s)