Abstract
Objective To assess the association between patient sociodemographic characteristics and adoption of and preferences for digital technologies in primary care.
Design Cross-sectional bilingual online survey conducted in the fall of 2022.
Setting Canada.
Participants Adults living in Canada aged 18 and older.
Main outcome measures Descriptive statistics were reviewed and a bivariate analysis was conducted of 8 outcomes by sociodemographic characteristic. Models included the following 8 self-reported characteristics: gender, age, province, level of education, level of income, rurality, whether the participant was born in Canada, and health status. Descriptive responses to a question on why video appointments were not important for some respondents were also examined.
Results Data were analyzed from 9279 completed responses. Compared to those earning more than $150,000, respondents earning less than $30,000 were less likely to have recently used email or secure messaging (adjusted odds ratio [aOR]=0.57, 95% CI 0.37 to 0.87) or video calls (aOR=0.65, 95% CI 0.31 to 1.37) or want to use email or secure messaging (aOR=0.71, 95% CI 0.51 to 0.97) or video calls (aOR=0.50, 95% CI 0.36 to 0.68). Compared to university graduates, respondents with a high school diploma or below were less likely to have used email or secure messaging (aOR=0.67, 95% CI 0.49 to 0.90) or video calls (aOR=0.42, 95% CI 0.24 to 0.76) or want to use email or secure messaging (aOR=0.74, 95% CI 0.60 to 0.91) or video calls (aOR=0.73, 95% CI 0.59 to 0.90). People earning less than $30,000 were less likely to have accessed personal health records (aOR=0.43, 95% CI 0.30 to 0.61) or place importance on accessing them (aOR=0.60, 95% CI 0.41 to 0.88). Similarly, people with a high school diploma or less were less likely to access personal health records (aOR=0.61, 95% CI 0.50 to 0.76) and place importance on accessing them (aOR=0.68, 95% CI 0.54 to 0.86).
Conclusion The results suggest that people living with a lower income or who have less formal education are less likely to have used digital technologies or consider them important. Further research and policy work should help to understand barriers to adoption of digital technologies and develop tailored interventions to enable equitable access to health care services.
Digital technologies such as virtual care or personal health records (PHRs) have the potential to improve access and efficiency in primary care. Virtual care, also known as telemedicine or telehealth, includes synchronous communication tools such as video or telephone calls and asynchronous tools like email or live chat. Personal health records, or patient portal access, are online platforms that allow functions such as viewing test results, immunization records, or medication lists. Canada has historically lagged behind its international peers in technology adoption, but has recently seen a marked increase in the integration of digital technologies in primary care practices sparked by the rapid adoption of such services during the COVID-19 pandemic.1,2 From 2019 to 2022, the proportion of primary care physicians offering online appointments rose from 22% to 38%, while the proportion allowing patient communication through email or secure messaging grew from 23% to 50%.3
However, digital technologies have been described as a double-edged sword. They have the potential to enhance access for underserved communities (including those in rural areas or individuals with disabilities),4 but may also widen existing inequities in health and care, in part due to variation in access to technology, digital fluency, and health literacy.5,6 Studies suggest an increased uptake of virtual care among younger, healthier, more educated individuals with higher socioeconomic means.7-9 Similarly, factors such as age, income, education, and health status greatly influence the access to and usage of PHRs.10-12
Given the expanding influence of digital technologies in primary care practice, it is important to understand their potential to deepen the digital divide and exacerbate health disparities. This study aims to assess the association between socioeconomic factors like income and education on the adoption of and preferences for digital technologies in primary care. To our knowledge, it is the first study to specifically explore how education and income levels impact the perceived importance and actual usage of specific virtual care solutions for primary care in the Canadian context.
METHODS
Study design and context
We analyzed results from a cross-sectional survey of adults living in Canada to understand the use of and interest in digital technologies that enable care and access to information. Medically necessary physician visits are free at the point of care for all residents of Canada through provincial and territorial health insurance plans. Following the onset of the pandemic, family physicians received remuneration from the public system for telephone visits with their patients; remuneration for video and email or secure messaging varied by province and territory.13
Survey design
We analyzed survey data that were collected as part of OurCare, a pan-Canadian initiative to engage the public about the future of primary care in Canada. Survey methods are detailed elsewhere14 and summarized here briefly. The survey was conducted between September 20 and October 25, 2022, with people living in Canada, aged 18 and older, who were eligible to respond. The online questionnaire was available in English and French, hosted on Qualtrics, and distributed using 2 methods. First, we distributed an open link and promoted the survey via our partner networks, the media, social media channels, and the project website. Second, Vox Pop Labs, a national public opinion research company, sent a single closed link to 122,053 individuals from its proprietary panel with 2 personalized reminders. A partner organization supported patients living in an underserved area in Ontario to complete the survey and provided a $10 gift card for participation. No other incentives were offered.
The survey content was developed with more than 50 collaborators, including primary care clinicians, researchers, administrators, policy-makers, patients, survey methodologists, and a patient education expert who provided advice on an accessible literacy level for the questionnaire. The survey was anonymous and no personal health information was collected.
Statistical correction and inclusion criteria
To ensure that our sample closely mirrored the population of Canada, we applied weighting to each response using an iterative proportional fitting method, which was based on marginal distributions derived from the 2021 Statistics Canada census. We used the following attributes for weighting: age, gender, education, income, language, and region. We included surveys where respondents reached the end of the survey, there were no anomalies (eg, a lack of variation in responses within question blocks), and there were usable answers to all the demographic questions required for weighting. We excluded surveys that were completed in less than 550 seconds (the 3.3rd percentile of usable observations for total survey duration).
Data analysis
Analysis for this manuscript was conducted using the weighted data. We examined 8 outcomes related to the use and importance of digital technologies for care and access to information (Table 1). We reviewed descriptive statistics and conducted a bivariate analysis of the 8 outcomes by sociodemographic characteristics. Where bivariate analysis indicated some variation, we used multivariate logistic regression modelling to quantify the association between sociodemographic characteristics and outcomes.
Survey questions on digital technologies included in analysis, response options, and how the variables were dichotomized
Models included the following self-reported characteristics: gender, age, province, level of education, level of income, rurality, whether the participant was born in Canada, and health status. The choice of variables included in the fitted model was based on a literature review. Finally, we examined descriptive responses to a question on why video appointments were not important for some respondents. All statistical analyses were conducted using R, version 4.0.0.
RESULTS
Overall, 14,018 adults responded to the survey and 9279 survey responses were included in the analysis. The effective sample size after weighting was 3199, and demographic characteristics of the respondents are presented in Appendix 1, available from CFPlus.* In total, 77.0% of respondents reported having a family physician or nurse practitioner (ie, a primary care clinician).
Descriptive analysis
Among respondents with a primary care clinician, 70.7% reported communicating by telephone, 5.0% by video, and 17.6% by email or secure messaging in the past 12 months. Among all respondents, when asked about the most important ways to receive care, 92.5% chose in-person appointments booked in advance, 54.4% in-person appointments where you can drop in or walk in, 66.1% telephone communication, 40.7% video consultations, and 42.1% email or secure messaging (Figure 1). Among those who said that telephone appointments were not important, the top 3 reasons were the following: “I like seeing my health care provider in person,” “I do not feel connected to my health care provider when using the phone,” and “I need in-person visits for my health issues.” Among those who said video appointments were not important, the top 3 reasons were the following: “I like seeing my health care provider in person,” “I am satisfied with the other appointment options,” and “I do not feel connected to my health care provider when using video.”
Use and importance of virtual care modalities
Further, 59.4% of respondents reported having used an app or website to access their medical information, and 75.1% of respondents said that accessing their personal health information online was “fairly important” or “very important.”
Bivariate analysis
Use and importance of telephone calls was relatively high among all sociodemographic strata with little variation between sociodemographic groups so no regression modelling was done (Appendix 2, available from CFPlus*). In contrast, there was marked variation by sociodemographic characteristic for the remaining 6 outcome variables.
Regression analysis
Email and secure messaging. After adjusting for other factors, respondents without a university degree and those earning less than $150,000 had lower odds of communicating by email or secure messaging compared to the relevant reference groups. They also had lower odds of considering email or secure messaging as 1 of the most important ways to receive care. Additionally, respondents younger than age 65 had higher odds of selecting email or secure messaging as 1 of the most important methods for care, while men had lower odds than women (Figure 2).
Percentages of respondents who: A) communicated with a family doctor or nurse practitioner via email or secure message during the past 12 mo and corresponding odds ratios by sociodemographic characteristic, and B) would like to use email or secure messaging to receive care from a family doctor or nurse practitioner and corresponding odds ratios by sociodemographic characteristic.
Video calls. After adjustment, few sociodemographic variables showed a statistically significant difference in having used videoconferencing in the past 12 months, except for education level and rurality. Respondents with less than a university degree and those with an income under $70,000 had lower odds of selecting video as 1 of the most important ways to receive care compared to the reference groups. Conversely, respondents younger than 65 had higher odds of considering video as 1 of the most important methods for receiving care (Figure 3).
Percentages of respondents who: A) communicated with a family doctor or nurse practitioner via video call during the past 12 mo and corresponding odds ratios by sociodemographic characteristic, and B) would like to use video appointments to receive care from a family doctor or nurse practitioner and corresponding odds ratios by sociodemographic characteristic.
Digital access to information. After adjustment, respondents with less than a university degree and with an income under $150,000 had substantially lower odds of having used an app or website to view their personal medical information. Respondents with less than a university degree and with an income under $70,000 had substantially lower odds of considering online access to their personal health information important compared to the relevant reference groups. Additionally, men and people living in rural areas had substantially lower odds of having used online access or saying it was important to them compared to women and people living in urban areas (Figure 4).
Percentages of respondents who: A) used an app or website to see personal medical information and corresponding odds ratios by sociodemographic characteristic, and B) said it is fairly or very important to be able to look at personal health information online and corresponding odds ratios by sociodemographic characteristic.
DISCUSSION
The integration of digital technology in primary care has the potential to improve accessibility.1,4 However, our national survey, conducted 30 months after the start of the COVID-19 pandemic, suggests that the transformative potential of digital technology is not uniformly realized or desired. Most respondents had experience using telephone calls and considered them important for receiving care. However, use of and interest in newer technologies such as email or secure messaging, video consultations, and PHRs varied based on socioeconomic characteristics. Those with less than a university degree and those with a lower income had lower odds of communicating or wanting to communicate by email or secure messaging, wanting to use videoconferences, or accessing or wanting to access personal health information online.
Such results reinforce the findings of previous studies that flagged income and education as influential determinants of virtual care adoption.15-18 Our findings align with Yu and Hagens,16 who found that individuals with household incomes below $80,000 had lower odds of using video (odds ratio=0.56) or digital messaging (odds ratio=0.77), and also noted that lower education levels were associated with reduced demand for virtual care modalities. However, contrasting findings were reported by Bhatia et al,19 who observed a substantial increase in virtual care uptake across all income quintiles during the COVID-19 pandemic. Their study, however, included telephone appointments as a form of virtual care, with more than 90% of all virtual care appointments they analyzed being telephone calls, which we excluded from our analysis to focus on newer virtual care modalities, as our preliminary analysis showed minimal variation in the use of and preferences for telephone appointments across different income and education levels. Our findings on PHRs also align with other studies showing lower-income and less-educated individuals are less likely to use them.10-12
Despite its potential to bridge access gaps, strategies to ensure equity for lower-income and less-educated groups must be explored further to understand how virtual care can be made more equitable.20,21 Possible interventions might focus on improving digital literacy, increasing access to affordable technology, ensuring the availability of telephone consultations, and enhancing Internet infrastructure in underserved areas.1,22 Many recently developed virtual care services are not part of the publicly funded health care system, and given the current shortage of health care professionals, these private services can divert human resources away from the public system, exacerbating access issues.23 Members of the public who were engaged through the OurCare priorities panels, conducted in parallel to this study, recommended expanding virtual care with a view to enhance access equity, especially in rural and remote areas, by developing comprehensive models that ensure access 24 hours a day, 7 days a week to services and diverse care modes like video, telephone, and secure messaging tailored to patient preferences and integrated with in-person care. They also emphasized making medical records and PHRs accessible and interoperable across health care platforms to improve efficiency and empower patients.24
Limitations
Our biggest limitation is response bias. The data collection method, an Internet-based survey, introduces potential selection bias. Internet surveys might not capture those without regular Internet access or technology proficiency. In the context of our study on virtual care and technology, this bias is particularly salient. Those less familiar with technology might be underrepresented in our sample, possibly skewing our findings toward a more positive view of virtual care and leading to an underestimation of sociodemographic differences. Additionally, our study did not explore potential differences in the quality of virtual care received by different income groups, which could be an important factor in understanding health disparities. Finally, we did not have any respondents from the Northwest Territories, Nunavut, or Yukon, a region where digital technology plays a potentially even more important role in providing access given the vast geography.
Conclusion
Findings from our large national survey suggest that people living with a lower income or who have less formal education are less likely to have used digital technologies or consider them important, including email or secure messaging, video calls, and online access to PHRs. The integration of digital technology into primary care in Canada is an opportunity to improve access for underserved individuals, particularly those in remote or rural areas, but also risks widening health inequities. Further research and policy work is needed to understand income- and education-related barriers to adopting virtual care and develop tailored interventions that help ensure equitable access to primary care services.
Acknowledgment
We thank our collaborators on our National Health Policy and Health System Governance Group and Primary Care Leaders Circle, members of the Canadian Medical Association’s Patient Voice Advisory Group, and the Improving Primary Care Public Advisors Council at Unity Health Toronto for their help informing the study design and survey questions, interpreting results, and promoting the survey. We also thank Amy Craig-Neil for her support early in the project, Katrina Grieve for help simplifying the survey language, and Paul Krueger for feedback on survey design.
Footnotes
↵* Appendices 1 and 2 are available from https://www.cfp.ca. Go to the full text of the article online and click on the CFPlus tab.
Contributors
All authors contributed to the conception and design of the work. Dr Alexander Beyer and Dr Clifton van der Linden led data collection. Dr Gabrielle Denault, Rick Wang, Dr Beyer, and Maryam Daneshvarfard conducted the analysis. All authors interpreted the data. Dr Benoît Corriveau and Dr Denault jointly drafted the manuscript. All the authors revised it critically for important intellectual content, gave final approval of the version to be published, and agreed to be accountable for all aspects of the work.
Competing interests
Dr Michael E. Green has received grants from the Ontario Ministry of Health and is also a member of the College of Family Physicians of Canada board and executive committee (as Past President). Dr Tara Kiran received a Health Canada grant for the present work, as well as a grant for previous work from the Ontario Ministry of Health and consulting fees from Ontario Health. She has received speaking honoraria from the Canadian Medical Association, the College of Family Physicians of Canada, the Ontario Medical Association, the Association of Family Health Teams of Ontario, Shared Health in Manitoba, Health Workforce Canada, the Alberta College of Family Physicians, and the Ontario College of Family Physicians. The rest of the authors have declared no competing interests.
This article has been peer reviewed.
Cet article a fait l’objet d’une révision par des pairs.
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