Applying Open Data to Tackle the Pandemic (Covid-19): Leveling the Barriers using Interpretive Structural Modeling (ISM)
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Abstract
Coronavirus Pandemic (Covid-19) has put many healthcare systems in severe crisis. One way to deal with these uncertainties is to use open data systems. This study aims to analyze the development barriers of an open data network in Iran’s health system to create a more effective solution to the crisis. In this research, utilizing interpretive structural modeling (ISM), the opinions of eight experts in the field of health have been used. The strategic wisdom of the present study in two separate phases is to identify and level 1- barriers to establishing an open data network and 2- barriers to using an open data network. This research shows the severe gap among specialists in infrastructure and human resources of the Iran’s healthcare system.
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