Socioeconomic Factors Associated With the Use of Telehealth in Primary Care Services During the COVID-19 Pandemic

Abstract

Introduction:

The main objective of this study was to assess whether socioeconomic factors were associated with the use of telehealth in primary care services in Portugal during the COVID-19.

Methods:

A questionnaire was administered to patients in primary healthcare units during the pandemic. The set of variables used in this study was part of a larger patient satisfaction questionnaire. A descriptive statistical analysis was performed, and a multiple logistic regression analysis was estimated to assess factors associated with using remote consultation.

Results

The use of a remote consultation was reported by 38.2% of respondents (N = 7008), and the main reason for telehealth use was prescription renewal. Among non-users of telehealth, 40% did not know they could contact their family doctor by email. Factors positively associated with telehealth use were: older age, women, married, filled questionnaire without help, consumption of OTC and prescribed drugs, unmet healthcare needs, and registered with family doctor. The evidence suggests a negative association between education and telehealth use.

Conclusions:

No clear pattern emerged regarding the digital divide. The evidence shows a relevant lack of awareness regarding the possibility of using telehealth. If more complex forms of telehealth are adopted in primary care services, the digital divide might come to the surface.

Keywords

telehealth primary care socioeconomic factors COVID-19 health economics

Introduction

The World Health Organization (WHO) defines telehealth as the “delivery of health care services, where patients and providers are separated by distance. Telehealth uses information and communications technology (ICT) for the exchange of information for the diagnosis and treatment of diseases and injuries, research and evaluation, and for the continuing education of health professionals.”¹ The interaction between providers and patients might assume diverse forms, ranging from synchronous interactions, such as telephone or video consultations, to asynchronous forms, like email.

Although telehealth has a long history, the COVID-19 pandemic has undoubtedly brought it to the forefront, with many health systems rapidly introducing in-home telehealth to maintain access to care.^2,3

Before the pandemic, telehealth’s potential for timely disasters response was acknowledged. Professionals in unaffected areas could meet increased healthcare demands, reduce imbalances in certain specialties, enable current physicians to work longer from home, and involve semi-retired doctors to address specific needs. However, this potential remained underutilized.⁴ During the COVID-19 pandemic, telehealth not only helped to maintain access to care but it also contributed to decreasing the transmission of the SARS-CoV-2, by replacing in-person ambulatory visits with telehealth visits.^3,5,6

The telehealth’s main benefit is to improve healthcare access^1,5,7 and several motives may be advanced to explain it: it reduces transportation difficulties, either distance or cost^8,9; it overcomes shortages in underserved and often remote areas^7,10; and it reduces waiting times.¹¹

While telehealth’s contribution to reducing geographical barriers to care is unequivocal, its role in addressing social barriers to care is more uncertain. The digital divide, that is, disparities in communication technology literacy and access, has been pointed out as the most challenging hurdle faced by telehealth in improving access to healthcare.⁶ One study using a representative sample of California adults found that a 1-U increase in digital competence (a 4-point Likert scale was used, ranging from “very comfortable” performing a given digital task to “not comfortable at all”) is associated with 72.8% greater odds of using telehealth.² The digital divide threatens to become the new face of inequality,¹² where age and level of education stand out as 2 important obstacles to the use of telehealth.^13,14 Older people tend to lack digital literacy, and their physical limitations, sight or hearing, reinforce the difficulties of adopting telehealth.¹⁵ Educational level of attainment has been identified as the most important contributor to information and strategic Internet skills.^14,16

Income is another relevant socio-economic driver. Although telehealth can bring lower cost and productivity gains for people,⁹ lower income was associated with telemedicine unreadiness due to difficulties in using communications technology and affording internet-enabled devices.^8,17,18

Previous evidence shows that among American households earning less than $25 000 yearly, only 71% own a computer, tablet, or smartphone, and only 58% have broadband subscriptions.¹⁹ Similarly, across European countries, low income is associated with lower levels of internet access.^12,16

Finally, health status itself seems to be a relevant factor when it comes to the use of ICT. Existing evidence suggests that telemedicine unreadiness is more prevalent among individuals with poorer self-rated health (SRH)¹⁷ and that internet use is positively associated with better health status.²⁰

In Portugal, telehealth initiatives have been in place for more than 2 decades²¹ and, in 2019, the government approved the National Strategic Plan for Telehealth 2019 to 2022, which aimed the development of telehealth in the Portuguese health system. One main goals of this Plan was to guarantee better and more equitable access in healthcare.²² During the COVID-19 pandemic, similar to other countries, Portugal witnessed a substantial increase in teleconsultations, with a rise in remote appointments of about 100%, in 2020,²³ which fostered the interest about the individual socio-economic drivers underlying this increase.

Conceptual Framework

The conceptual framework used to sustain this research was the Andersen model. This model²⁴ provides a theoretical structure to understand health service use, and it has been applied to a broad range of health system service sectors, different populations, and diseases and is the most frequently cited model of healthcare service utilization in health services research. According to this model, healthcare utilization, regarded as actual access, depends on 3 types of factors: (i) predisposing factors, such as demographic characteristics and the individuals’ perceptions of an illness; (ii) enabling factors corresponding to the means available to individuals and communities to use healthcare; and (iii) needs, usually associated with health status. An extended version of this model²⁵ further includes environmental factors, such as features of healthcare systems and economic climate, while assuming feedback loops, that is, individual characteristics may influence utilization and vice versa. Importantly, access to healthcare is a multidimensional concept, depending on demand and supply side factors. Utilization relies on the interaction between (i) services features such as availability, appropriateness, and affordability, and (ii) the persons’ abilities to perceive need for healthcare, to seek and reach health services, and to pay for it.²⁶

Compared to the traditional mode of delivery, with in-person consultations, telehealth contributes to lessening barriers related to usual enabling factors, such as the availability of health services or means of transport. However, it also brings new challenges, with new enabling factors coming into play, such as having access to internet broadband and devices, the first level of digital divide.² However, enabling factors are necessary, but not sufficient, conditions to use healthcare.²⁴ So, the second level of the digital divide arises by emphasizing the differences between groups of people in terms of the skills necessary to effectively use the internet and devices.² Now the predisposing factors that might transform potential into realized access are at stake.²⁴ In the case of the use of telehealth, some of the traditional predisposing factors, like age and education, might become even more crucial. Thus, from a theoretical point of view, barriers to access to telehealth are still foreseen, especially affecting those already most penalized by the digital divide. Whether telehealth represents an opportunity to decrease inequality in healthcare use is, in fact, a matter for empirical evidence.

Aim and Contribution

In the aftermath of the COVID-19 pandemic, with a widespread environment favoring the adoption of telehealth, and given the potential threat of the digital divide, the main objective of this study was to assess whether socioeconomic factors were significantly associated with telehealth use in primary care services. Our study contributes to the relatively scarce empirical literature on access to telehealth in primary healthcare services and to the best of our knowledge, this is the first empirical study about individual socioeconomic factors associated with the use of telehealth in Portugal.

The findings of this study contribute to improve policy design by providing well-supported evidence on the effectiveness and limitations of the integration of telehealth in primary care, on people’s preferences, on potential measures to optimize healthcare delivery, and finally to prepare for future crises.

Methods

Population and Sample

Data come from a questionnaire administered between the last trimester of 2021 and the first trimester of 2022 to users of the 147 primary healthcare units located in the Centre Region of Portugal. Users, aged 18 years or over, self-completed a satisfaction questionnaire, with or without help, in desktop computers available at the facilities. When preferred by users, the questionnaire was administered by interview, carried out by staff from the citizen’s office without any interference with the answers. The Directive Board and the Ethics Committee of the Ministry of Health’s Regional Health Authority approved its implementation (23.09.2021).

Measurement Instrument

The set of questions used in this paper about the use and knowledge of telehealth was part of a larger questionnaire from a continuous quality improvement program aimed to monitor people’s satisfaction toward the services provided by primary healthcare units.²⁶ This program encompassed some steps including data collection, data analysis, the production of a global and by health unit reports, and a subsequent discussion to design corrective actions to better patient satisfaction in each unit. All this process forced us to wait some months before writing and submitting this paper.

Variables

The dependent variable, identified as “telehealth,” is binary and equals 1 if the respondent answered “Yes” to the question “In the last 12 months did you have any remote consultation with a health professional from your health unit?”. The questionnaire also asked about whose initiative the appointment was (own, family doctor’s, or family health nurse’s). If the respondent answered “No” about having a remote consultation, the following question was asked “Do you know that you can contact your family doctor by email?”. The possible answers were: (i) “Yes and I have the address”; (ii) “Yes but I do not have the address”; and (iii) “No.” In the creation of the questionnaire, we followed the National Health Regulatory Authority’s guidelines about telehealth,²⁷ and we included deferred teleconsultation, real-time consultation, and medical consultation without the presence of the patient (eg, for advice, prescription renewal, or referral to another service) as remote consultations. Regarding telehealth, 3 modalities were possible: telephone-, email-, or video-consultations.

In terms of covariates, grouped according to Andersen’s model as described in previous section, predisposing factors comprise age, sex, education (“primary” corresponds to level 1 of IESCD 2011, “lower_secondary” corresponds to level 2 of IESCD 2011; “upper_secondary” corresponds to levels 3 or 4 of IESCD 2011, and “tertiary” to levels 5 or 6 or 7 or 8 of IESCD 2011), and marital status. The group of enabling factors comprises job status and the binary variable “filled_no_help,” which was used as a proxy for digital literacy/telehealth readiness. Needs are proxied by self-rated health. Regarding healthcare utilization, our analysis includes 3 covariates: “prescribed_drugs” (consumption of prescribed drugs in last 2 weeks), “OTC” (consumption of over-the-counter drugs in last 2 weeks), and “unmet_needs” (self-reported unmet need for medical consultation in last year). Finally, reflecting a feature of the healthcare system, the list of covariates includes information on whether the respondent is registered with a family doctor.

Statistical Analysis

We started with a descriptive analysis of the data, with emphasis put on knowledge about and the reasons for using telehealth, the modalities used and initiative regarding appointments. A chi-square test was performed to assess differences in the use of telehealth between the various sample groups. To assess factors associated with the use of telehealth, multiple logistic regression analysis was adopted.²⁸ Results were reported in the form of Odds-Ratio (OR); 95% confidence intervals and P-values are also provided. All the analyses were performed using SPSS 28.0.

Results

The sample used in this study comprises 7008 observations. Table 1 presents the mean scores for each variable, as well as, its distribution based on the use of telehealth.

Table 1.

Sample Composition and Bivariate Analysis Between the Use of Telehealth and Sample Characteristics.

	Mean (%)	Telehealth		χ²	P-value
Factors	Mean (%)	Yes (%)	No (%)	χ²	P-value
Predisposing factors
Age: 18-34	17.5	32.3	67.7	52.7	<.001
35-44	17.7	37.9	62.1
45-54	21.4	40.8	59.2
55-64	21.2	42.2	57.8
65-74	13.6	38.9	61.1
75+	8.5	38.6	61.4
Sex: Female	64.1	39.4	60.6	7.08	.008
Male	35.9	36.2	63.8	7.08	.008
Education: primary	20.2	40.2	59.8	3.64	.303
lower_secondary	24.2	36.9	63.1
upper_secondary	32.1	38.0	62.0
Tertiary	23.5	38.2	61.8
Marital status: single	17.4	30.0	70.0	43.87	<.001
married_partner	66.4	40.3	59.7
Divorced	9.2	39.1	60.9
Widowed	7.0	37.8	62.2
Enabling factors
Job status: Employed	62.5	39.0	60.0	20.22	.001
Unemployed	7.0	34.2	65.8
Retired	22.1	38.3	61.7
Student	2.6	28.9	71.1
domestic_work	3.2	32.1	67.9
disabled_inactive	2.6	46.9	53.1
Filled:no_help	73.5	39.3	60.7	9.65	.002
help_interviewed	24.5	35.2	64.8	9.65	.002
Needs
SRH: fair/good/very good	93.0	37.9	62.1	3.43	.064
poor/very poor	7.0	42.1	57.9
Healthcare utilization
prescribed_drugs: Use	60.0	42.1	57.9	65.4	<.001
No use	40.0	32.5	67.5	65.4	<.001
OTC: Use	20.1	42.8	57.2	15.68	<.001
No use	79.9	37.1	62.9	15.68	<.001
unmet_needs: Yes	45.6	40.2	59.8	9.53	.002
No	54.4	36.6	63.4	9.53	.002
Healthcare system
Family_doctor: Yes	93.8	38.7	61.3	10.83	<.001
No	6.2	30.8	69.2

As shown in the flowchart of Figure 1, 38.2% of respondents reported at least 1 remote consultation in the previous 12 months, mostly via telephone. Each respondent could select more than 1 modality of telehealth, and the vast majority (90.3%) contacted health professionals by phone and only 16.3% used video calls.

Figure 1.

Flowchart for the use of telehealth and correspondent percentage of respondents.

The most frequent reason for remote consultations was prescription renewal (62.3%), though more than half of respondents (58.2%) also used this form of care delivery to carry out a consultation with their family doctor. In more than half of the situations (54.1%), respondents themselves took the initiative to make remote appointments, while the role of family health nurses is quite residual in this aspect. Among those respondents who did not use any form of telehealth, 40.0% did not know they could contact their family doctor by email and, even among those who knew this, more than one-third (37.2%) did not know the email address.

Regarding factors associated with the use of telehealth, the results of the bivariate analysis also shown in Table 1 suggest that, among all the covariates, only educational level and self-rated health are not significantly associated with telehealth. However, for a more robust assessment, Table 2 presents the results of the multiple regression analysis.

Table 2.

Factors Associated With the Use of Telehealth.

	OR	P-value	95% CI
Factors	OR	P-value	Lower	Upper
Predisposing factors
Age^a: 35-44	1.279	.009	1.063	1.540
45-54	1.393	<.001	1.157	1.677
55-64	1.531	<.001	1.259	1.862
65-74	1.479	.006	1.121	1.951
75+	1.528	.011	1.101	2.121
Female	1.172	.003	1.054	1.303
Education^b: lower_secondary	0.791	.008	0.665	0.940
Upper_secondary	0.849	.079	0.707	1.019
Tertiary	0.816	.042	0.671	0.993
Marital status^c: Married_partner	1.306	.001	1.110	1.536
Divorced	1.184	.139	0.947	1.482
Widowed	1.121	.394	0.862	1.457
Enabling factors
Job status^d: unemployed	0.833	.081	0.679	1.023
Retired	0.809	.059	0.649	1.008
Student	1.048	.798	0.734	1.495
domestic_work	0.616	.002	0.455	0.835
disabled_inactive	1.230	.201	0.896	1.690
Filled: no_help	1.421	<.001	1.245	1.623
Needs
Good SRH^e	0.909	.346	0.744	1.109
Healthcare utilization
prescribed_drugs	1.451	<.001	1.304	1.615
OTC	1.196	.004	1.059	1.351
unmet_needs	1.148	.007	1.039	1.268
Healthcare system
family_doctor	1.359	.005	1.096	1.684

Abbreviations: CI, confidence interval; OR, odds ratio.

Goodness-of-fit tests: Omnibus—P < .001; Hosmer-Lemeshow—P = .438; Nagelkerke R = .039.

Reference categories: ^a: 18 to 34 years; ^b: educ_primary; ^c: employed; ^d: employed; ^e: SHR poor/very poor.

As displayed in this table, among the predisposing factors included in the analysis, age, female, and being married are positively associated with the use of telehealth, while higher levels of education are negatively associated. Respondents who filled the questionnaire without help were 42% more likely to report the use of telehealth. Self-rated health seems to be irrelevant for the use of telehealth, but the consumption of medicines shows a positive, statistically significant, association. Respondents who reported unmet needs in previous 12 months were more likely to have used telehealth, as well as respondents registered with a family doctor.

Discussion

With this study, we aimed to identify factors related to the use of telehealth in primary care services, with emphasis placed on socioeconomic variables given the threat of the digital divide. But it also contributes to fill a gap in evidence that still exists regarding types of, and reasons to use telehealth.²⁹ Our results provide insights regarding the implementation of future policies aiming at expanding the use of telehealth in primary care services, targeting patients of all ages and levels of education. They also provide some clues regarding the preparedness for future health crises. Although the COVID-19 pandemic represented an opportunity in terms of the expansion of telehealth, it has been noted that, in Portugal, the rapid response during the pandemic, mostly through phone-based services, should have been followed by upgrading to more comprehensive telehealth technologies.³⁰ Our results show that the use of telehealth in primary care services is not that spread across patients, with less than 40% of respondents reporting this use, even in its simplest forms, such as telephone and email. However, this percentage is, for instance, higher than that found in the U.S. of about 32.5%,³¹ though in this latter case, the data was collected in an earlier phase of the pandemic (2020), and the study considered consultations only by video or by phone. In our sample, only 6% of respondents reported to have used video conference. These results might be in part related to the reasons for using telehealth. That is, simpler forms of telehealth are adequate to address needs like prescription renewal, which emerged as the most frequent reason for remote consultations. A study in Australia concluded that telephone services and shorter consultations were the most dominant forms of telehealth.³² This study also found that the proportion of video consultations was higher in the most socioeconomically advantaged areas compared to less socioeconomically advantaged areas. Still, it was not clearly established that health professionals and patients, namely older ones, prefer video calls over less complex forms of telehealth.^33,34 A study aimed at doctors working in the Portuguese National Health Service, carried out during July-September 2020, found that 70.4% of doctors would like to continue doing follow-up teleconsultations, and 53.3% considered that video call technologies should always or often be used during teleconsultations.³⁵

Regarding potential barriers to the use of telehealth, we did not find strong patterns. While older ages and lower levels of education are usually pointed out as obstacles to the adoption of telehealth^13,15 our results show the opposite scenario. Which might be partly explained by different study populations, countries, and time periods. Those 2 reviews of literature^13,15 were published before the COVID-19 pandemic, most studies included are from the U.S. and many considered disease-related, small-sized, samples. In fact, more recent studies, 1 for Canada and another for the U.S., also found the highest rates of telemedicine among adults aged 65 years and older.³⁶ For older individuals and chronic patients, telehealth might be in fact substituting in-person visits, facilitating access to care, namely for more straightforward services like prescription renewal, or for requesting and showing exams, somehow like what was found for the U.S.³¹ Also, in Portugal, there has been a 24-h health(care) line run by the Ministry of Health since 2017, meaning that patients had time to learn and adjust to this delivery form.

Contrary to what would be expected,¹⁴ our findings showed that people with less education were more likely to use telehealth. We must nonetheless stress that, as noted in this WHO’s review of literature,¹⁴ not many studies analyzed the effect of education on the use of telehealth and some of the studies focused on quite specific’s dimensions of access such as research on patient portals and patient self-scheduling. In a previous study, which analyzed only interactions resorting to audio and video, the authors found that education is insignificant for telehealth use when controlling for digital competence; even among the educated, lower digital competence is negatively associated with telehealth use.² Plus, the need to use telehealth to reduce the risk of infection may have been an incentive for accessing these types of services for the first time, impelling more vulnerable groups to overcome barriers to telehealth use.³¹ Also, during the COVID-19 pandemic, the Portuguese government created special telecommunication/internet packages for lower-income people. This means that future interventions must take into account that people might become more reluctant to use telehealth, given the alternative of in-person visits, and greater barriers might come into play for low-income families if financial support for internet access is not provided. On the positive side, it seems that people are capable of adjusting and overcoming unsureness in times of crisis.

Although we did not find clear evidence of the digital divide, respondents who filled out the questionnaire themselves, without any help, were 44% more likely to have used telehealth. Only this variable from the group of enabling factors is statistically significant. Still, 1-quarter of all respondents did not know they could contact their family doctor by email, which reveals a considerable lack of awareness regarding telehealth possibilities. These results are in line with previous findings, which revealed that the main challenges for patients to adopt telemedicine were low digital literacy, unfamiliarity with technology, and misinformation about telemedicine processes.³⁷ While acknowledging the limitations of our proxy for digital literacy, it showed a significant impact on telehealth use, even when we restricted the analysis to individuals who used telehealth on their initiative (which returned an OR = 1.457, P < .001, for the variable “filled_no_help,” as presented in Supplemental Table). Evidence suggests that experience with specific digital tasks, such as filling in a digital form, can indicate readiness for telehealth.³⁸ Thus, our proxy conveys, to some extent, information about how people might respond to a digital challenge. Given our results and previous findings, universal interventions to improve digital literacy are of utmost relevance to expand and upgrade telehealth use, while avoiding new forms of inequalities in access. Our results further suggest the need for reinforcing information about the possibility of using and how telehealth can be used. Given the potential percentual increase of patients using telehealth, it might be important to reassure patients about the quality of care provided (eg, if exam results are sent by email, patients must trust that their doctors will pay due attention to this matter).

Regarding the variable sex, although men usually report higher internet access and digital skills than women,^12,14,31 according to our results, men seem less keen to use telehealth. A similar result was found in a study using 2020 data from a sample in Nebraska, USA.¹⁹ There is prior evidence that, in high-income countries, although women use digital services less often and less intensively, they tend to use them more frequently than men to seek health-related information and to support their health.¹⁴

Our results suggest a residual role of family health nurses regarding the initiative to make appointments. Plus, consultation with a family health nurse was the least frequent reason for using telehealth. This might mean that in-person visits are preferred and/or more accessible compared to in-person doctor visits. Patients might be using telehealth as a substitute for doctor visits but not for nurse visits as these are more accessible. Or nurse visits might be used for care not amenable to remote consultations such as vaccination and bandage. But our results can also reflect a shortcoming of service organization, with under exploitation of telehealth for services delivered by family health nurses. There is a debate still going on about whether remote care substitutes for or complements in-person care and whether telehealth adds value or is wasteful for health systems.²⁹ Another strand of less clear understanding is about the contribution of nurses during the pandemic.³⁹ One way or another, these results merit further thought on how telehealth might be potentiated regarding nurse visits.

In our study, respondents who reported unmet needs for medical consultation in last 12 months were more likely to report the use of remote consultation. In these cases, telehealth might represent an improvement in access to healthcare, which may be expected.⁵ Even if it is not the preferred option, compared to no care at all, it is an improvement. On the other hand, telehealth does not seem to solve the scarcity of family doctors in some regions, as patients registered with a family doctor are more likely to use telehealth. It may be that most of these patients live with chronic diseases which need permanent medication requiring prescription. Our results show that people who report taking prescribed drugs are more likely to use telehealth, which is aligned with findings that clinical pharmacy services may be provided via telehealth.⁴⁰

As far as we know, this study was the first in Portugal to identify factors associated with the utilization of telehealth in primary care services, focusing on socioeconomic variables due to the potential impact of the digital divide. Our findings offer valuable information for decision-makers and policy-makers to develop policies to increase telehealth utilization in primary care services, focusing on patients of all ages and educational backgrounds. Additionally, they offer indications about the readiness for forthcoming health emergencies and the use of telehealth technologies.

Some limitations apply to our study namely the proxy used for digital literacy and the inclusion of only 1 variable of need. Because we used cross-sectional data, causality cannot be inferred. This study used self-reported data that is susceptible to recall biases. Finally, we have focused on patients’ characteristics. Although it was not relevant in this study, given that the responses were collected during the COVID-19 pandemic, it would be interesting to assess the impact of travel distance and the use of telehealth in future studies. Information about participants’ income and internet use may also be valuable for a more detailed analysis. Besides expanding this analysis to other regions of Portugal, future research should assess the role of education and digital literacy more closely, using more accurate proxies for the latter and considering video consultations. Income and internet access should also be controlled. It is important to understand if our results remain in a non-pandemic context and if telehealth is a complement to or a substitute for in-person visits. Future research might seek to unveil the reasons behind the low use of telehealth for nurse consultations and understand the perceptions that both patients and providers have regarding the use of telehealth. These dimensions affect not only access to healthcare but also service organization and the use of resources. Nonetheless, we must be aware that there are further barriers and risks associated with adopting telehealth such as patient privacy and confidentiality, data accuracy, incorrect diagnoses, provider-patient relationships, medical liability, fraud and abuse, prescription of controlled substances, and reimbursement.¹³ Doctors in the Portuguese National Health Service have also identified a series of obstacles to the expansion of telehealth. A great majority (84.3%) think it is unsuitable for the first consultation. In addition, the lack of ICT, especially in public facilities, the inability to perform a physical exam, the difficulty in understanding the complaints expressed by patients and the need of training for health professionals, are some examples of barriers to telehealth reported.³¹

Conclusions

Notwithstanding the substantial use of telehealth during the COVID-19 pandemic, we found that fewer than 40% of patients had used telehealth in primary care services for a period of 12 months. Moreover, this utilization occurred mainly in the simplest form, with telephone consultations and mostly for prescription renewal, with few patients using telehealth to reach their family health nurse. Thus, the full potential of telehealth in primary healthcare services in Portugal seems to remain largely unexploited.

The main goal of this study was to assess if and which socioeconomic factors were associated with the use of telehealth. The results do not support concerns related to the digital divide. Factors such as low education or older ages do not seem to be acting as barriers to access. However, there is some lack of awareness about alternative channels to contact the family doctor, and respondents who were able to self-complete the (computer-based) questionnaire without help were also more likely to use telehealth.

Telehealth might play a role in improving access to healthcare for those who report unmet healthcare needs. Nonetheless, telehealth should not be adopted as a second-best option. It should be used when both patients and providers are comfortable with this mode of delivery. Hence, many challenges are yet to be overcome in primary care services in Portugal, not only in terms of the digital literacy of patients (especially if we are to move to more complex forms of telehealth) but also in terms of investment in ICT and training of health professionals.

Supplemental Material

sj-docx-1-jpc-10.1177_21501319241312564 – Supplemental material for Socioeconomic Factors Associated With the Use of Telehealth in Primary Care Services During the COVID-19 Pandemic

Supplemental material, sj-docx-1-jpc-10.1177_21501319241312564 for Socioeconomic Factors Associated With the Use of Telehealth in Primary Care Services During the COVID-19 Pandemic by Carlota Quintal, Aida I. Tavares, Inês Ribeiro, Victor Raposo and Pedro L. Ferreira in Journal of Primary Care & Community Health

Footnotes

Acknowledgements

The authors particularly thank due to patients who, in a very willing way, accepted to participate in this study.

Author Contributions

CQ: conceptualization, methodology, formal analysis, and writing of the original draft. PF and VR: main contributor to data collection. All authors—CQ, AIT, IR, PF, and VR—contributed to the interpretation of results, critically revised the manuscript, and approved its final version.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research has not been funded. However, CEISUC/CiBB is funded by national funds through FCT—Foundation for Science and Technology, I.P., under the Multiannual Financing of R&D Units 2020 to 2023. CeBER is funded by national funds through FCT—Foundation for Science and Technology, I.P., under the Project UIDB/05037/2020.

Ethical Approval and Informed Consent Statements

The Directive Board and the Ethics Committee of the Ministry of Health’s Regional Health Authority approved its implementation (23.09.2021). The participants provided their written informed consent to participate in this study.

ORCID iDs

Aida I. Tavares

Victor Raposo

Pedro L. Ferreira

Data Availability Statement

The data that support the findings of this study are available from CEISUC but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of CEISUC.

Supplemental Material

Supplemental material for this article is available online.

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