Primary care payment models and avoidable hospitalizations in Ontario, Canada: A multivalued treatment effects analysis.

Improving access to primary care physicians' services may help reduce hospitalizations due to Ambulatory Care Sensitive Conditions (ACSCs). Ontario, Canada's most populous province, introduced blended payment models for primary care physicians in the early- to mid-2000s to increase access to primary care, preventive care, and better chronic disease management. We study the impact of payment models on avoidable hospitalizations due to two incentivized ACSCs (diabetes and congestive heart failure) and two non-incentivized ACSCs (angina and asthma).

Self-reported mental health during the COVID-19 pandemic and its association with alcohol and cannabis use: a latent class analysis.

Background: Mental health problems and substance use co-morbidities during and after the COVID-19 pandemic are a public health priority. Identifying individuals at high-risk of developing mental health problems and potential sequela can inform mitigating strategies. We aimed to identify distinct groups of individuals (i.

Machine Learning-Based Predictive Modeling of Anxiety and Depressive Symptoms During 8 Months of the COVID-19 Global Pandemic: Repeated Cross-sectional Survey Study.

Background: The COVID-19 global pandemic has increased the burden of mental illness on Canadian adults. However, the complex combination of demographic, economic, and lifestyle factors and perceived health risks contributing to patterns of anxiety and depression has not been explored.

Objective: The aim of this study is to harness flexible machine learning methods to identify constellations of factors related to symptoms of mental illness and to understand their changes over time during the COVID-19 pandemic.