Prescription opioid misuse and opioid use disorder (OUD) are significant health problems in the US and impact stakeholders across the healthcare sector[1]. The Center for Medicare and Medicaid Services’(CMS’s) paper summarizes these issues and outlines strategies to handle the crisis and reduce impacts of this epidemic[2]. Although there are several initiatives at the federal, state, and local level to combat this problem, proactively identifying fraudulent and risky behaviors of various healthcare entities can help with preventive measures. This thesis propose a framework for healthcare data analytics platform using Cloud, Artificial Intelligence (AI) and Machine Learning (ML) technologies to enable real time/predictive analytics and gather deep insights into collecting preliminary data to investigate opioid crisis.

Author: Jones Yeboah

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