The Effects of the COVID-19 Pandemic on Physician Delivery of Virtual and In-person Mental Health Care Services across Reformed Primary Care Payment Models in Ontario, aims to improve access to mental health care in primary care settings using lessons learned during the COVID-19 pandemic; the Ontario Ministry of Health (MOH) approved new physician billing codes for virtual assessments by telephone or video.
These changes in the delivery of care and the payment received through different primary care models may have affected physicians’ behaviour regarding the quantity of virtual and in-person mental health care provided. This research will mobilize knowledge to inform the MOH policymakers on how mental health services can be effectively integrated into primary care settings and delivered to Ontarians given payment models. It will determine the payment model that maximizes virtual and in-person mental health care and how important the temporary virtual visit billing codes introduced are.
The main objectives of this study are to compare physician provision of virtual and in-person mental health care services before and after the COVID-19 pandemic across Ontario’s dominant primary care delivery models: blended fee-for-service, blended capitation, and team-based primary care. The following questions will be investigated:
- How did the COVID-19 pandemic affect the delivery of mental health care services across primary care payment models?
We will compare the quantity of mental health services delivered virtually and in-person across payment models before and after the pandemic.
- Do differences exist by sex and age of physicians in the delivery of virtual and in-person mental health services during the COVID-19 pandemic?
We will compare by sex (women vs men) and age as well as sex and age combinations the quantity of mental health services delivered virtually and in-person to determine which groups of physicians had the largest changes in patterns of service provision during the COVID-19 pandemic.
To achieve the objectives described above, we will use Ontario health administrative data held at ICES containing information on the number and the type of mental health care services (i.e., virtual care, in-person care), physician payment model, and physician characteristics. A population-based, retrospective longitudinal study design will be used, spanning from fiscal years 2010 to 2022, allowing us to compare patterns over time before and during the first two years of the pandemic. We will use a two‐stage estimation strategy to estimate the impact of introducing the new billing codes on physician provision of virtual and in-person mental health care services across payment models. First, we will account for the selection into payment models using a propensity score (PS) weighting model to render physicians comparable regarding their observed characteristics at baseline. Second, we will use an inverse probability weighting (IPW) estimator to adjust the outcomes of physicians in different payment models by weighting them with the inverse of the estimated propensity scores – computed in the first step. Our regression strategy will take advantage of the longitudinal nature of the data to control for unknown or unobservable confounders or fixed effects.
Practicum research student in CAMH practicum program:
The trainee will conduct research activities in parallel to their master’s or PhD’s studies. These research activities will help the trainee gain quantitative analytical skills (mostly in mental health policy evaluation and mental health services research) that will complement his learning. More specifically, the trainee will apply advanced econometrics methods on large administrative datasets. The trainee will be expected to produce quality research in the standard of publishable articles at the end of this practicum.