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Bangladesh's Digital Health Journey: Reflections on a Decade of Quiet Revolution

Overview
Specialty Public Health
Date 2019 Aug 24
PMID 31441440
Citations 27
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Abstract

Bangladesh has made remarkable progress in digital health in recent years. Through one of the world’s largest deployments to date of the open-source District Health Information Software 2 (DHIS2), the country now has a national public sector health data warehouse. Information from previously fragmented data systems is now unified in a common data repository, enabling data exchange for health information systems and decision-making. Work is ongoing to create lifetime electronic health records for all citizens that can be transferred between health facilities. Extensive customization of open-source software has laid the foundations for a national digital networking system. Initiatives have focused on producing digital solutions to aid priorities such as strengthening the health system as a whole as well as supporting specific technical interventions, for example improving the civil registration and vital statistics system. Digital solutions have also supported the Bangladesh health workforce strategy through a set of registries that electronically captures and maintains human resource information for the entire public health sector, including monitoring staff attendance through the use of low-cost biometric fingerprint time-attendance machines. Citizens are encouraged to engage in shaping health services via a web-based complaints and suggestions system, and a new system to raise health awareness via public digital displays has started in Dhaka. Strong support at the highest political level has been critical to the success of efforts to introduce these innovations. The endeavour has also generated a cadre of enthusiastic eHealth proponents, who are focused on further strengthening and expanding the existing systems and on harnessing the vast amount of information amassed at the central data repository through big data analysis, artificial intelligence and machine learning.

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