COVID-19 Variant Supplement - 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.
- Funded by Canadian Institutes of Health Research (CIHR)
- Total publications:0 publications
Grant number: 202102VS1
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Key facts
Disease
COVID-19Start & end year
20212022Known Financial Commitments (USD)
$39,500Funder
Canadian Institutes of Health Research (CIHR)Principal Investigator
N/A
Research Location
CanadaLead Research Institution
University of British ColumbiaResearch Priority Alignment
N/A
Research Category
Clinical characterisation and management
Research Subcategory
Prognostic factors for disease severity
Special Interest Tags
Data Management and Data Sharing
Study Type
Non-Clinical
Clinical Trial Details
Not applicable
Broad Policy Alignment
Pending
Age Group
Adults (18 and older)
Vulnerable Population
Unspecified
Occupations of Interest
Unspecified
Abstract
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.