Highlights
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During the COVID-19 pandemic, virtual physician visits rapidly increased and then declined among older persons living with dementia (PLWD).
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Rural PLWD were less likely to receive virtual family physician visits compared to urban, highlighting geographic disparities.
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Future research should explore and address barriers to virtual care access among rural PLWD.
Introduction
The rapid uptake and implementation of virtual care in Ontario, Canada, has been regarded as a success of the COVID-19 pandemic response.Reference Glazier, Green, Wu, Frymire, Kopp and Kiran1,Reference Bhatia, Chu, Pang, Tadrous, Stamenova and Cram2 Despite this, there are concerns virtual care may exacerbate barriers to healthcare already experienced by vulnerable groups such as rural dwellers, older adults, persons with low income, those with disabilities and racialized persons.Reference Chan-Nguyen, Ritsma, Nguyen, Srivastava, Shukla and Appireddy3,Reference Kronfli4 Such barriers relate to the availability, affordability, access and sustainability of healthcare.Reference Chan-Nguyen, Ritsma, Nguyen, Srivastava, Shukla and Appireddy3 Barriers to the adoption of virtual care include technological challenges such as digital health literacy, vision and hearing impairment and not having access to the required technology for virtual care.
The COVID-19 pandemic posed unique challenges for persons living with dementia (PLWD) and their caregivers. Restrictions and lockdown measures disrupted routines and increased social isolation and loneliness, all of which have been associated with neuropsychiatric symptoms and behavioral disturbances, thus increasing caregiver burden in this population.Reference Manca, De Marco and Venneri5,Reference Talbot and Briggs6 PLWD were more likely to suffer severe outcomes when infected with COVID-19,Reference Numbers and Brodaty7 and some reported a decline in cognitive function.Reference Talbot and Briggs6
In Ontario, access to healthcare services was disrupted at the start of the pandemic, resulting in a decline in the use of several health services including emergency department (ED), physician and home care visits.Reference Bronskill, Maclagan and Maxwell8 During this period, a rapid shift to virtual healthcare services occurred to enable continued care access.Reference Rodin, Lovas and Berlin9 This was facilitated by the Ministry of Health introducing temporary fee codes to the health insurance billing structure to allow virtual physician care via telephone calls and videoconferencing as an alternative to in-person visits.Reference Bhatia, Chu, Pang, Tadrous, Stamenova and Cram2,10,11
Previous research has shown that PLWD in rural/remote areas have lower rates of healthcare utilization including physician visits and home care compared to urban dwellers.Reference Arsenault-Lapierre, Bui, Le Berre, Bergman and Vedel12,Reference Williams, Lee and Kadakia13 We have demonstrated a rapid uptake of virtual care in physician visits among PLWD in Ontario in the first few months of the pandemic;Reference Bronskill, Maclagan and Maxwell8 however, the extent of potential geographic variation has not been explored. We examined the association between rurality and rates of virtual physician care across specialties over time among community-dwelling PLWD in Ontario, Canada.
Methods
Study design, setting and participants
We conducted a population-based repeated cross-sectional study between March 1, 2020, and August 27, 2022, among community-dwelling PLWD aged 66–110 years who were alive and eligible for provincial insurance at the start of each week (index date) in Ontario, Canada. The first COVID-19 case in Ontario was recorded on January 25, 2020; however, community transmission became evident in March 2020. Therefore March 1, 2020, was designated the start of the study period. Ontario is the most populous province in Canada with over 14 million residents, and nearly all residents have universal health coverage for medically necessary services, including ED visits, physician visits and hospitalizations. We identified PLWD using a validated health administrative database algorithm.Reference Jaakkimainen, Bronskill and Tierney14 Individuals with contact with a nursing home in the 3 months prior to each index date were excluded since persons residing in nursing homes experience different patterns of physician visits and access to care, particularly during the pandemic.
Data sources
We obtained sociodemographic information including age, sex and death date (if applicable) from the Ontario Registered Persons Database. We used the Canadian Institute for Health Information (CIHI) Discharge Abstract Database and National Ambulatory Care Reporting System to obtain information on acute care hospitalizations and ED visits, respectively. We used the Ontario Health Insurance Plan (OHIP) for physician billing information and the Ontario Drug Benefit (ODB) database to identify dispensed medications. To identify and exclude those who were admitted to a nursing home, we used the Continuing Care Reporting System Long-Term Care, ODB and OHIP databases. Information on primary care enrollment models based on primary care provider rostering was obtained using the Client Agency Program Enrolment database. These datasets were linked using unique encoded identifiers and analyzed at ICES. ICES is an independent, nonprofit research institute whose legal status under Ontario’s health information privacy law allows it to collect and analyze healthcare and demographic data, without consent, for health system evaluation and improvement. The use of the data in this project is authorized under section 45 of Ontario’s Personal Health Information Protection Act and does not require review by a Research Ethics Board.
Exposure
The primary exposure was urban versus rural location of residence as of the index date. Rurality was obtained from the Postal Code Conversion File Plus, version 2016, and defined using Statistics Canada’s indicator of rural and small-town status based on community size.Reference Du Plessis, Beshiri, Bollman and Clemenson15,16 Rural PLWD were defined as individuals residing in rural communities and small towns (with population size ≤ 10,000) and municipalities outside the commuting zones of larger urban centers. Urban PLWD, in contrast, were those residing within a census metropolitan area or census agglomeration known as “urban core” as well as those in neighboring municipalities where ≥ 50% of the workforce commute to the urban core.Reference Du Plessis, Beshiri, Bollman and Clemenson15
Outcomes
The primary outcomes were visits (total, virtual, in-person) to physicians who regularly provide care for PLWD – family physicians, neurologists and geriatricians/psychiatrists (grouped together for stable estimates due to small counts). Virtual visits were identified using OHIP fee codes for physician visits that indicated telephone or video visits, while in-person visits were identified by fee codes that indicated office or home visits.
Baseline characteristics
Sociodemographic and clinical characteristics such as age, sex, income quintile, Ontario Marginalization Index (ON-Marg) material resources dimension (v2016), medication use and comorbidities were described for community-dwelling PLWD at the start of the study (March 1, 2020). The neighborhood income quintile is an area-based measure of household income obtained by linking an individual’s postal code to census data from Statistics Canada.Reference Sholzberg, Gomes, Juurlink, Yao, Mamdani and Laupacis17 The ON-Marg material resources dimension represents one facet of marginalization and includes indicators on single-parent households, employment and education, social assistance, low-income and housing.Reference Matheson, Dunn, Smith, Moineddin and Glazier18
We identified the history and duration of dementia (time from case ascertainment in administrative databases to the start of the study) and the presence of 17 other chronic conditions using validated health administrative algorithms.Reference Jaakkimainen, Bronskill and Tierney14,Reference Mondor, Maxwell and Hogan19 We identified all medications dispensed where the prescribed duration of use overlapped the start of the study period and categorized them according to subclasses of interest (antipsychotics, antidepressants, benzodiazepines, cholinesterase inhibitors, opioids, angiotensin-converting enzyme inhibitors and angiotensin receptor blockers and total number of medications dispensed (0–4, 5–9 and 10+).
Primary care enrollment models were implemented by the Ontario government in the 2000s to improve primary care delivery.Reference Hutchison, Levesque, Strumpf and Coyle20 We categorized models as capitation (team-based and non-team-based), fee-for-service (FFS) (traditional and enhanced), physicians not in an enrollment model and patients not rostered to a primary care physician. We calculated continuity of primary care using the Usual Provider of Care Index – a ratio of the frequency of visits to a patient’s main provider to the frequency of visits to all providers over a 2-year period.Reference Jee and Cabana21 This index was grouped into low (<0.4), medium (0.4–0.8) and high (>0.8) continuity categories.22 Recent registration for health insurance (<10 years prior to the index date) was used as a proxy for immigration. Health system utilization in the previous year including acute care hospitalizations, ED visits, home care visits, family physician, neurologist and geriatrician/psychiatrist visits was also obtained.
Given changes in the nature of the COVID-19 pandemic over time, we divided the 30-month period into 5 subperiods of 26 weeks (∼6 months). The subperiods were March 1, 2020, to August 29, 2020 (0–<6 months); August 30, 2020, to February 27, 2021 (6–<12 months); February 28, 2021, to August 28, 2021 (12–<18 months); August 29, 2021, to February 26, 2022 (18–<24 months); and February 27, 2022, to August 27, 2022 (24–30 months).
Statistical Analysis
Demographic and clinical characteristics as of March 1, 2020, were summarized and compared between rural and urban groups using standardized differences, with values greater than 0.1 considered meaningful.Reference Mamdani, Sykora and Li23 In each subperiod, we calculated the proportions of PLWD with at least one visit and the average number of visits among those individuals, for each mode of physician visit (virtual and in-person) and specialty. Weekly rates of physician visits (total, virtual, in-person) per 100 persons were calculated for each specialty comparing urban and rural residents. PLWD were censored at each index date on death, admission to a nursing home or loss of OHIP eligibility, whichever occurred first. Poisson regression models with generalized estimating equations were used to calculate rate ratios (RR) and 95% confidence intervals (CI) comparing physician visit rates by rurality. Models were initially adjusted for age, sex and subperiod (to adjust for changes in visits over time). To achieve a parsimonious model and ensure computational efficiency, we further adjusted for income quintile, primary care enrollment model and history of visits to family physicians, neurologists, psychiatrists or geriatricians in the previous year. All analyses were conducted using SAS v9.4 (SAS Institute Inc., Cary, NC).
Results
We identified 122,751 community-dwelling PLWD on March 1, 2020, including 111,447 (90.8%) urban and 11,304 (9.2%) rural individuals (Table 1). Those living in rural locations were younger than urban residents (81.1 vs. 82.3 years, SDiff = 0.16), while sex distribution was similar (female 55.8% vs. 58.5%, SDiff = 0.06). We observed differences in the number of chronic conditions, model of primary care, recent health insurance registration, continuity of primary care and healthcare utilization in the previous year by rurality.
Characteristics of community-dwelling PLWD in Ontario, Canada, as of March 1, 2020, by location of residence
Bolded entries represent standardized difference > 0.10.
* Percentages may not sum to 100% due to missing information. † Angiotensin-converting enzyme (ACE) inhibitors and angiotensin-receptor blockers (ARBs), respectively. ‡ Exact cell sizes cannot be reported due to privacy obligations with ICES. § Patient had no core primary care fee codes for 2 years prior to index.
At the beginning of the study period, we observed an increase in virtual visits and a decline in in-person visits across all physician specialties and both rural and urban PLWD. This increase was more pronounced in visits to primary care providers compared to other specialties (Figure 1). By the end of the third subperiod (12–<18 months), in-person visits began to rise, eventually surpassing virtual visits. However, urban PLWD consistently had higher virtual visit rates than rural PLWD across specialties (Supplementary Table 2).
Weekly rates of physician visits among older adults living with dementia in Ontario, Canada, by location of residence and physician specialty (2020–2022).
Compared to urban PLWD, rural PLWD had significantly lower rates of virtual visits to primary care physicians (RR = 0.71, 95% CI: 0.69–0.73), neurologists (RR = 0.79, 95% CI: 0.75–0.83) and psychiatrists/geriatricians (RR = 0.72, 95% CI: 0.68–0.76) (Table 2). Compared to the first 6 months, virtual visit rates to primary care providers were highest at 6–<12 months (RR = 1.05; 95% CI: 1.03–1.07) and lowest at 24–30 months (RR = 0.70; 95% CI: 0.69–0.71). Similar trends were observed for virtual visits to neurologists (RR = 1.14; 95% CI: 1.11–1.17 at 6–<12 months; RR = 0.73; 95% CI: 0.68–0.78 at 24–30 months) and psychiatrists/geriatricians (RR = 1.14; 95% CI: 1.11–1.17 at 6–<12 months; RR = 0.71; 95% CI: 0.66–0.76 at 24–30 months).
Rate ratios for virtual physician visits associated with sociodemographic and clinical characteristics among community-dwelling persons living with dementia in Ontario, Canada, by specialty (2020–2022)
Bolded entries represent standardized difference > 0.10.
§ Patient had no core primary care fee codes for 2 years prior to index.
Rates of virtual visits to neurologists and psychiatrists/geriatricians were significantly lower for PLWD aged 75–84 years (RR = 0.92, 95% CI: 0.90–0.94 and RR = 0.72, 95% CI: 0.68–0.76) and even lower for those aged 85+ years (RR = 0.68, 95% CI: 0.64–0.72 and RR = 0.57, 95% CI: 0.54–0.61) compared to those aged 66–74 years (Table 2). There were no significant differences across age for family physician visits (75–84 years (RR = 1.02, 95% CI: 0.95–1.10 and 85+ years RR = 1.05, 95% CI: 0.97–1.14).
Female PLWD had higher rates of virtual visits with psychiatrists/geriatricians than males (RR = 1.12, 95% CI: 1.07–1.16) but lower rates of virtual visits with neurologists (RR = 0.89, 95% CI: 0.88–0.91). For family physicians, rates were not significantly different in females compared to males (RR = 1.03, 95% CI: 0.98–1.08). PLWD in the highest income quintile had higher rates of virtual visits to family physicians and neurologists compared to those in the lowest quintile (RR = 1.06, 95% CI: 1.01–1.11 and RR = 1.15, 95% CI: 1.09–1.21, respectively), but rates were not significantly different for psychiatrist/geriatrician visits (RR = 0.99, 95% CI: 0.95–1.04). Patients enrolled in a capitation-based primary care model had lower rates of virtual visits to family physicians compared to those who were not (RR = 0.60, 95% CI: 0.58–0.62). PLWD who had at least one primary care visit in the past year had significantly higher rates of virtual visits to family physicians (RR = 8.97, 95% CI: 8.67–9.27), neurologists (RR = 29.00, 95% CI: 23.15–36.32) and psychiatrists/geriatricians (RR = 19.49, 95% CI: 17.37–21.88) compared to those who did not.
Discussion
In this population-based study of community-dwelling PLWD in Ontario, Canada, we observed lower rates of virtual visits to family physicians, neurologists and geriatrician/psychiatrist physicians among individuals in rural compared to urban areas. During the first few months of the COVID-19 pandemic, rates of virtual visits increased but then declined across all specialties over time. We observed significantly lower rates of virtual care visits to all specialists with increasing age. Female PLWD had higher rates of virtual visits to psychiatrists/geriatricians and lower rates to neurologists compared to men. Those in higher income quintiles had higher rates of virtual visits to family physicians and neurologists, while those in capitation-based primary care models had lower virtual visit rates to family physicians.
Our study highlighted significantly lower rates of virtual visits among PLWD in rural areas. Few studies have compared rates of virtual visits between rural and urban PLWD. However, a study among US veterans that compared the use of telemedicine between urban and rural residents before and during the COVID-19 pandemic observed 36% lower rates of primary care visits and 50% lower rates of mental health integration visits in rural compared to urban residents.Reference Leung, Yoo and Chu24 Similar trends were observed in the general population in Ontario,Reference Glazier, Green, Wu, Frymire, Kopp and Kiran1,Reference Bhatia, Chu, Pang, Tadrous, Stamenova and Cram2,Reference Chu, Cram, Pang, Stamenova, Tadrous and Bhatia25 where rural residents had the lowest rate of virtual primary care visits during the pandemic compared to their urban counterparts. According to Canada Health Infoway, Canadians in rural and remote areas had decreased access to virtual care during the pandemic compared to urban residents.26 Healthcare providers in rural communities have also cited limited internet connectivity, unreliable Wi-Fi and patients’ limited access to and knowledge of technology as barriers to providing virtual care.Reference Mohammed, Hyseni and Bui27
For PLWD in Canada, family physicians are usually the first point of contact and play a crucial role in management. In unusual, complex or rapidly progressing cases, family physicians may refer patients to specialists such as neurologists, psychiatrists and geriatricians, who are sparsely distributed across geographic regions and concentrated in urban areas.Reference Bacsu, Mateen, Johnson, Viger and Hackett28,Reference Moore, Frank and Chambers29 Virtual care, therefore, provides an opportunity for convenient and accessible dementia care across geographic locations.Reference Sekhon, Sekhon and Launay30 Additionally, it offers several advantages over in-person visits such as ensuring continuity of care; increasing access to timely, convenient medical care; and addressing distance and travel barriers.Reference Wong, Bhyat, Srivastava, Lomax and Appireddy31
Despite these benefits, virtual care may widen existing disparities in access to care. Often, patients who are most likely to benefit from virtual care – such as PLWD – may be the least able to access it.Reference Voisin and Cascadden32 Access to virtual care is multifactorial and not only includes the availability of services but also the ability to use services. Therefore, it may depend on individual characteristics like age, income, education level and cognitive status; digital or systemic factors such as local policies and technology access; or previously existing inequities like decreased access to primary and specialist care in remote areas.Reference Chan-Nguyen, Ritsma, Nguyen, Srivastava, Shukla and Appireddy3,Reference Voisin and Cascadden32 In older adults, comfort with technology and digital health literacy remains a concern.Reference Chan-Nguyen, Ritsma, Nguyen, Srivastava, Shukla and Appireddy3,Reference Elbaz, Cinalioglu and Sekhon33 Older adults with dementia and cognitive impairment may also require caregiver assistance to access virtual care.Reference Elbaz, Cinalioglu and Sekhon33 Those without caregivers, lacking access to computers for videoconferencing or who are frail are more likely to choose phone visits over video visits and therefore have disproportionate access to forms of virtual care.Reference Liu, Goodarzi, Jones, Posno, Straus and Watt34,Reference Pang, Zhao, Kithulegoda, Agarwal and Ivers35 Additional systemic factors, especially in rural areas, further complicate access to virtual care. These communities may face unique challenges such as a limited healthcare workforce, a lack of necessary infrastructure and inadequate funding and resources, all of which can further contribute to lower rates of virtual care utilization among rural PLWD.Reference Rahimipour Anaraki, Mukhopadhyay, Wilson, Karaivanov and Asghari36 In particular, the shortage of physicians in rural areas and the high physician turnover lead to low continuity of care for rural PLWD,Reference Chauhan and Michael Jong37 which may lead to difficulties accessing virtual care with a patient’s own physician. Previous research has demonstrated that virtual visits with a physician outside a patient’s enrolling group lead to increased risks of subsequent ED visits.Reference Lapointe-Shaw, Salahub and Austin38 Rural family physicians have also highlighted difficulties communicating with new patients virtually (e.g., difficulty building relationships, accessing health records, understanding and evaluating the health literacy of patients), reinforcing that virtual care is most effective when supported in an existing physician–patient relationship.Reference Rahimipour Anaraki, Mukhopadhyay, Wilson, Karaivanov and Asghari36
Few studies have noted the gradual decline in virtual visits after its rapid uptake in the early months of the pandemic.Reference Falk39 Canada Health Infoway reports that the proportion of virtual visits for non-COVID-related reasons decreased from 54% in April 2020 to 30% in March 2022 across Canada.40 In Ontario, a gradual return to in-person visits has been observed; as of December 1, 2022, the virtual primary care fee codes introduced in March 2020 are no longer billable,41–43 and remaining billing codes for virtual care are limited, further reducing the provision of virtual care services. Given the importance of virtual care in improving healthcare access, consideration for reinstating these virtual primary care fee codes would ensure that it remains a viable option for rural PLWD.
In our study, older females living with dementia were more likely to virtually visit psychiatrists or geriatricians and less likely to visit neurologists compared to men. Virtual visits to family physicians did not show significant differences. Other studies in Ontario observed that rates of virtual visits to family physicians were significantly higher in women compared to men both before and during the pandemic.Reference Glazier, Green, Wu, Frymire, Kopp and Kiran1 This is expected as women are more likely to seek primary care.Reference Thompson, Anisimowicz, Miedema, Hogg, Wodchis and Aubrey-Bassler44 Older age was also associated with significantly lower rates of virtual visits to specialists in our study. The consensus on the association between age and virtual care visits in the literature is mixed.Reference Bhatia, Chu, Pang, Tadrous, Stamenova and Cram2,45 Bhatia et al. found that older adults had higher overall virtual physician visits during the pandemic in Ontario compared to younger adults.Reference Bhatia, Chu, Pang, Tadrous, Stamenova and Cram2 However, a CIHI report found that older adults had the fewest virtual visits.45 These varying results may be due to the different time periods in which these studies were conducted during the COVID-19 pandemic and the unique circumstances of PLWD.
PLWD residing in the highest income neighborhoods were more likely to receive virtual care from family physicians and neurologists. Similarly, a study in Ontario noted an increase in the proportion of virtual visits to primary care providers with increasing income quintiles during the pandemic.Reference Glazier, Green, Wu, Frymire, Kopp and Kiran1 CIHI also reported a slight increase in virtual visits with increasing income quintiles.45 Disparities may be related to the ability to afford devices such as smartphones and laptop computers or high-speed internet connections for virtual care access.Reference Voisin and Cascadden32,45
Rates of virtual visits to family physicians were significantly lower for patients in capitation-based enrollment models compared to those who were not. A study in Ontario found that between February and October 2021, family physicians who provided the most virtual visits practiced outside a patient enrollment model, particularly FFS models, compared to those in enrollment models (capitation, family health teams and family health groups).Reference Kiran, Green and Strauss46
Limitations
To our knowledge, this study is one of few capturing the geographic variations in virtual visits by physician specialties among community-dwelling PLWD over time in Ontario. We used a population-based approach with health administrative datasets to observe virtual physician visits across different physician specialties. Despite these strengths, there are limitations. The definition and ascertainment of dementia used in this study, although validated in a primary care sample, are not a clinical diagnosis, and there is the potential for misclassification. Further, the case ascertainment algorithm for physician visits requires multiple encounters, which may be more difficult for rural PLWD to achieve, particularly during the pandemic, possibly influencing the incidence rates of dementia during the study period. We could not distinguish between modalities of virtual care such as telephone calls and videoconferencing or adjust for individual levels of education. As is a common limitation of administrative data, we also could not examine reasons for the geographic variation in visit rates or the extent, appropriateness or quality of care provided during these visits.
Conclusions and implications
The pandemic highlighted challenges faced by older PLWD in accessing virtual care, particularly in rural areas. Our findings demonstrate that although virtual physician visits for both rural and urban PLWD increased at the start of the pandemic, quickly surpassing in-person visits, rural PLWD received lower rates of virtual care from family physicians, neurologists and geriatricians/psychiatrists.Reference Voisin and Cascadden32 While virtual care can be a convenient and efficient method to deliver timely care,Reference Kronfli4,Reference Shaver47 considerations of equitable access to care and its role in building a sustainable healthcare ecosystem are crucial. Sustainable systems and services are needed to reduce barriers to virtual care for underserved groups. Policymakers, healthcare providers and other stakeholders should consider policies and interventions to close the gap in access to virtual care between rural and urban residents while improving its long-term sustainability. Such policies might include support for rural healthcare providers, enhanced virtual care infrastructure in rural areas, incentivizing reimbursements for virtual services and promoting the retention of physicians practicing in rural settings. Future research should further explore the barriers to accessing virtual care particularly for rural PLWD, evaluate the quality of virtual visits compared to in-person visits and examine outcomes for PLWD in rural and urban areas.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/cjn.2025.43.
Acknowledgments
This document used data adapted from the Statistics Canada Postal CodeOM Conversion File, which is based on data licensed from Canada Post Corporation, and/or data adapted from the Ontario Ministry of Health Postal Code Conversion File, which contains data copied under license from ©Canada Post Corporation and Statistics Canada. Parts of this material are based on data and/or information compiled and provided by CIHI, Ontario Health and the Ontario Ministry of Health. The analyses, conclusions, opinions and statements expressed herein are solely those of the authors and do not reflect those of the funding or data sources; no endorsement is intended or should be inferred. We thank IQVIA Solutions Canada Inc. for the use of their Drug Information File. We thank the Toronto Community Health Profile Partnership for providing access to the Ontario Marginalization Index.
Author contributions
TO: Contributed to the study design, provided input on results, drafted and formatted the manuscript.
LM: Contributed to the study design, result interpretation, manuscript drafting, editing and reviewing.
ZL: Conducted statistical and data analysis and manuscript review.
JG: Supervised statistical and data analysis, determined appropriate techniques for data analysis, interpreted results.
RS: Contributed to the study design, provided input on results, reviewed the manuscript.
CM: Contributed to the study design, provided input on results, reviewed the manuscript.
LJ: Contributed to the study design, provided input on results, reviewed the manuscript.
SB: Conceptualized the research idea and study design, contributed to manuscript drafting editing and reviewing, supervised the entire research project, ensured all aspects were conducted properly.
Funding statement
This study received funding from the Ontario Neurodegenerative Disease Research Initiative (ONDRI) through the Ontario Brain Institute, an independent nonprofit corporation, funded partially by the Ontario government. This study was also supported by ICES, which is funded by an annual grant from the Ontario Ministry of Health (MOH) and the Ministry of Long-Term Care. This work was also supported by the Ontario Health Data Platform, a Province of Ontario initiative to support Ontario’s ongoing response to COVID-19 and its related impacts.
Competing interests
The remaining authors declare that there are no conflicts of interest.
Author disclosures
SB reports grants from the Ontario Brain Institute, ICES and the Ontario Health Data Platform. SB receives honoraria from the Public Health Agency of Canada and the Canadian Agency for Drugs and Technologies in Health.
LJ reports grants from the Public Health Agency of Canada, the Canadian Cancer Society, the Chronic Pain Centre of Excellence for Canadian Veterans, the Canadian Institutes of Health Research and the Ontario Ministry of Health.
RS receives support from the Bastable-Potts Chair in Stroke Research, Sunnybrook Research Institute and University of Toronto. RS reports grants from the Ontario Brain Institute/ONDRI. RS is an advisory board member for Hoffman La Roche and a shareholder in FollowMD Inc.
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