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Predicting the risk of developing mental and substance use disorders due to COVID-19: machine learning applied to health service utilization data to facilitate access to effective treatments

COVID-19 Research Area(s): Mental Health & Wellbeing

COVID-19 has caused unprecedented demand on health care systems worldwide. Early indications suggest that the pandemic will lead to a surge in mental health and substance use disorders. This study aims to examine these mental and substance use implications through comparison of patient cohorts in BC, Canada based on their "illness dose" of COVID-19. In partnership with the Health Authorities and the BC Ministry of Health, we will deploy an online survey to assess these patient groups to detect the new onset or worsening of mental and substance use disorders that may be attributed to COVID-19. We will leverage Population Data BC, one of the world's largest collections of health services data containing individual-level, de-identified longitudinal data on BC's 4.7 million residents. We will link our survey results with data available at Population BC data, in order to retrospectively study the sociodemographic, service utilization, prescription drug use, employment, and environmental exposures of patients over the past 10 years. Using machine learning methods (Artificial Intelligence) to compare these different cohorts, each of which represents different "doses" of exposure to COVID-19, we will identify patients that are at increased risk of developing COVID-19-related adverse mental health outcomes. We will follow up with COVID-19 positive patients through a virtual clinic and assess existing treatment options for mental and substance use problems. Ultimately, we will have a system to predict increased risk of neuropsychiatric impact of COVID-19 on patients in BC, and to facilitate access of these patients early on to existing mental health services. This important data will allow Health Authorities to prepare for subsequent waves of COVID-19 with the tools required to rapidly mitigate its adverse effects on mental health and substance use.