Waiting times for primary care appointments among older adults: a scoping review

Abstract

Background

Healthcare service waiting times have worsened due to the COVID-19 pandemic, particularly impacting older adults who need timely access to primary care to manage chronic conditions and prevent hospitalizations. This scoping review aims to fill a research gap by examining whether delays in primary care appointments for older adults occurred and, if so, how these delays have affected their access to primary care, with a focus on the role of social determinants of health.

Methods

Following PRISMA guidelines, a systematic search was conducted across three health databases—MEDLINE (Ovid), CINAHL, and EMBASE—as well as one AI platform (typeset.io). To be included, articles needed to discuss waiting times for primary care appointments, include older adults in their target population, and be published in English since 2014. Non-English articles were excluded due to language proficiency constraints among the review team. The review also examined the impact of social determinants of health on equity in access to care.

Results

This review identified a significant lack of research on primary care waiting times for older adults, with only twelve studies addressing the issue. Findings indicate that prolonged wait times act as a major barrier to accessing timely care, resulting in patient frustration, delayed treatment, and increased reliance on emergency services. The COVID-19 pandemic has exacerbated these challenges, particularly through care interruptions and the shift to virtual care, which is understudied regarding its impact on waiting times.

Conclusions

Prolonged waiting times for primary care disproportionately affect older adults, exacerbated by age-related health conditions and intersecting social determinants. Healthcare systems must address these barriers and prioritize research into tailored interventions to ensure equitable access to care for older adults.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s12889-026-28406-w.

Background

Waiting times for healthcare services pose a significant challenge across all sectors of the healthcare system worldwide, and these challenges have only been exacerbated by the COVID-19 pandemic. The strain on healthcare systems has intensified, leading to longer delays in accessing medical care. While waiting times for specialized services have been studied and shown to contribute to adverse mental health and stresses [1], there is a notable lack of evidence focusing on primary care, particularly for older adults – a demographic with greater healthcare needs and higher susceptibility to complications from delays [2]. Timely access to primary care is crucial for this demographic to manage chronic conditions, prevent health deterioration, and avoid unnecessary hospitalizations [3]. Social and physical factors, such as limited mobility and a higher prevalence of chronic diseases, further hinder their ability to access care [4]. The lack of focused research on this issue highlights a critical gap in understanding how older adults navigate these delays within healthcare systems worldwide.

This scoping review seeks to address this current gap by synthesizing evidence on waiting times for primary care appointments among older adults. Through a systematic examination of studies conducted across various healthcare contexts, this review aims to clarify how waiting times affect access to care for older adults and explore the influence of social determinants of health on these delays. In doing so, this review will provide critical insights to inform healthcare policy, and the development of targeted interventions aimed at improving equity in healthcare access for this vulnerable population.

Methods

This scoping review was conducted using the methodological framework proposed by Arksey and O’Malley [5] with recommendations by Levac et al. [6], which consists of five stages: (1) identifying the research question; (2) identifying relevant studies; (3) study selection; (4) charting the data; and (5) collating, summarizing, and reporting the results. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guideline was used to guide transparent reporting of the review process [7] and is included in Supplementary 1 (Appendix A).

Eligibility criteria

This scoping review includes qualitative and quantitative peer-reviewed articles from 2014 onward that discuss waiting times for primary care appointments among adults aged 60 and over. At both the abstract screening and full-text review stages, each item was independently reviewed by two reviewers, AP and IA, with discrepancies resolved by consensus. Articles were included if they addressed (1) waiting times (2), primary care settings, and (3) older adults population (age group 60 + or 65+). All steps of screening, full-text review, and data extraction were conducted using Covidence [8].

Information sources and search

Following the Peer Review of Electronic Search Strategies (PRESS) Guideline [9], one author (AP) worked with a librarian at the Simon Fraser University to develop search strategies, which were then revised and refined by all team members. We searched MEDLINE (Ovid), CINAHL, and EMBASE for eligible articles from 2014 to May 2024. The same search strategies were also applied to search using an artificial intelligent platform – typeset.io [10]. The final search strategies of these three databases are provided in Supplementary 1 (Appendix B).

Data charting process and items

Data extraction contains characteristics of included articles (i.e., first author, title, year of publication, and country), aims of the study, study design(s), sample size and target population, participants inclusion and exclusion criteria, method of recruitment of participants, mean age and sex distribution of the cohort, characteristics of comparison group, whether waiting time was measured and how it was measured, social determinants of health that impact waiting time (i.e., age, sex at birth, gender, ethnic, income, education, occupation, religious and beliefs, employment status, immigrant status, health conditions or diseases), and whether waiting time was measured in regarding to COVID-19. Two reviewers (AP and IA) extracted data independently and met afterward for mutual agreement.

Results

Selection of sources of evidence

Figure 1 presents a flowchart of the search and selection of sources of evidence. We identified 2656 abstracts from Embase, MEDLINE, and CINAHL; we also included the first 50 titles from a search on typeset.io [10]. A total of 79 studies were eligible for full-text review and 12 studies were included in this analysis.

Fig. 1.

Selection of sources for this scoping review

The final review included 12 papers, with 5 cross-sectional articles, 2 cohort articles, and 5 qualitative articles. These were characterized based on their study design, country, and sample population. The focus of the studies was either solely on waiting time or on waiting time among other aspects of access to healthcare in primary settings.

Characteristics of sources of evidence

The characteristics of the included studies are summarized in Table 1. The sample populations primarily comprised all ages, with three exceptions - one study focused on adults aged 75 to 93 years, and two on those aged 60 and above. The studies were conducted across diverse geographical locations. The quantitative studies relied on survey methods, while the qualitative studies utilized either individual interviews or focus group discussions.

Table 1.

Characteristics of included articles

No.	References	Study Design	Country
1	Wetmore et al. (2014) [11]	Quantitative; Cross-sectional study	Canada
2	Hung et al. (2016) [12]	Quantitative; Cross-sectional study	US
3	Martin et al. (2020) [13]	Quantitative; Cross sectional study	UK, Canada, Australia, France, Germany, the Netherlands, New Zealand, Norway, Sweden, Switzerland
4	Tolvanen et al. (2018) [14]	Quantitative; Cohort study	Finland
5	Neville et al. (2020) [15]	Qualitative; Semi-structured interviews	New Zealand
6	Das et al. (2020) [16]	Qualitative; Interviews and focus groups	US
7	Turin et al. (2020) [17]	Qualitative; Focus group discussions	Canada
8	Naidoo et al. 2019 [18]	Qualitative; Focus group discussions	South Africa
9	Steyl et al. (2020) [19]	Quantitative; Cross-sectional study	South Africa
10	Smithman 2018 [20]	Quantitative; Cross sectional study	Canada
11	Melchiorre et al. (2022) [21]	Qualitative; Interviews	Italy
12	Xu et al. (2021) [22]	Quantitative; retrospective observational cohort study	China

The aggregated data of included studies is presented in Table 2.

Table 2.

Aggregated description of included articles

	Sources	Counting number of Studies
Location of data	UK	1
	US	2
	Canada	3
	Australia	1
	New Zealand	2
	EU	3
	Non-EU	1
	China	1
	South Africa	1
Study design	Cross-sectional	4
	Cohort	2
	Qualitative (Interviews and focus groups)	4
Population	Older adults only	2
	Older adults as a group among others	8
	Patients with a health condition	1
	Men	1
Focus	Waiting time only	2
	Waiting time among other access to care aspects	8
	Waiting time to attachment to general practitioners (GPs)	1
Primary Objective 1	Report waiting time	10
Primary Objective 2	Determinants of health	4
	Age	2
	Sex	1
	Gender	1
	Income	1
	Education	1
	Employment status	1
	Other	3
Secondary Objective	Relevant to COVID	1

Waiting time for primary care appointments

Most of the studies reported long wait times which also posed a significant barrier to access healthcare services. Indeed, seven studies reported the estimated length of the wait time for primary care appointments (Table 3).

Table 3.

Length of waiting time reported in quantitative studies

References	Length of waiting time	Country
Wetmore et al. (2014) [11]	2–3 days	Canada
Hung et al. (2016) [12]	1 week (6.9 days)	US
Martin et al. (2020) [13]	< 2 days	UK, Canada, Australia, France, Germany, the Netherlands, New Zealand, Norway, Sweden, Switzerland
Tolvanen et al. (2018) [14]	≤ 2–7 days	Finland

Martin et al. [13] reported the ratio of participants who waited for less than 2 days for primary care appointments across 10 OECD countries in 2010, 2013, and 2016. The highest ratio of participants who waited less than 2 days was in New Zealand (76%), followed by the same ratio in the Netherlands and Switzerland (73%). The smallest 45% and 48% ratios were found in Canada and Norway, respectively. The time trend also showed that the waiting time for primary care appointments increased in Switzerland, decreased in Australia, and plateaued in France, New Zealand, Norway, and Sweden from 2010 to 2016; no pattern was observed for the other countries, i.e., Canada, Germany, and the UK. While the Victoria Family Medical Centre (VFMC) Patient Survey conducted by Wetmore et al. [11] in Ontario, Canada reported that the median waiting time for booking an appointment for any doctor was 2 days, increased by 1 day for booking specific doctors. Another study in the USA by Hung et al. [12] revealed the average waiting time for an appointment with a primary care physician was 1 week (6.9 days).

From qualitative studies, Neville et al. [15] reported that there were issues with the local health services and most of the participants reported long waiting times to access these services. Patricia stated, “Our doctors have quite long waiting lists. If you want to get a normal check-up, I think it’s usually 2–3 weeks and that is a bit annoying”. (Patricia, 81 years). While Das et al. [16] reported most of the patients were not able to get an appointment for the first time or when needed to follow up (same day, next day, or in upcoming weeks) and waited several months. If the disease relapsed after the clinic hours, they were forced to visit the emergency department (ED). A patient mentioned “When you get out of here [the emergency room] go see your gastroenterologist. But that’s not the way it works… The last time I called to get in the next day, they told me he had 17 patients and couldn’t see me. In three months, you don’t know what could happen. So, the next thing is [back to] the ED”.

A study of focus group discussions by Turin et al. [17] stated that Bangladeshi immigrant male patients who lived in Calgary had negative experiences with booking an appointment to visit family physicians (FP). Most of the participants reported they were unable to make an appointment when required immediately and needed to visit an emergency room or walk-in clinic. However, some accepted that FP were only for accessing healthcare services that are not acute and regular such as follow-ups and yearly checkups. A participant reported “It took 2–3 months to find a family doctor. Now, the problem is when I need him, I don’t find him and his service. Once my son had a fever and he needed to see the doctor. I called the office, and they told me to come later after 10 days. I can wait 2 days, but 10 days? What would I do after 10 days if I am sick now? Why do I need a family doctor if he is not available when I need him? Right? I need his access now”. (FGD-5, participant-5)

A qualitative study by Naidoo & Wyk [18] reported that the most important concern raised by the participants when visiting public health primary care facilities was the long waiting times. Participants expressed feelings of frustration for prolonged wait times. A participant mentioned “The biggest worry is the queue… Sometimes you spend the whole day here”. (Participant 4, Group 1, 66-year-old female)

A cross-sectional study conducted by Steyl et al. [19] reported that more than half of patients with type 2 diabetes mellitus (52.5%) were satisfied with the waiting time for primary care appointments on the same day while a substantial number (47.5%) were dissatisfied. When participants were asked for suggestions, 46% suggested a shorter waiting time for primary care appointments.

Time to be assigned to a FP

One cross-sectional study of five local health networks in Quebec by Smithman et al. [20] reported that from June 2013 to May 2015, a total of 24,958 patients were assigned to 468 FPs with an average waiting time of 284 days (SD: 350 days). While 49,901 patients were on the 5 central waiting lists and the average waiting time for patients waiting to be assigned was 458 (SD: 359 days).

Waiting time variation

A study by Tolvanen et al. [14] revealed that 51.9% of patients with advance appointments reported a waiting time of 1 week or less and 44.6% of patients who made an appointment with illness as a reason for a contact reported a waiting time of 2 days or less. In fact, patients who reported an illness as a reason for contact with a GP were able to get their appointments much faster compared to the patients with other reasons (OR 4.5 for non-urgent check-up group, 95% CI 3.2–6.5). Older adults had longer wait times compared to the younger ones even if the reason for contact was an illness (OR 1.02, 95% CI 1.003–1.03). Additionally, working patients have shorter wait times in case of illness (OR 2.4 for retired patients, 95% CI 1.2–4.7).

Only one study, Xu et al. [22], focused on impacts of the COVID-19 pandemic on wait times for older adults. It reported that the average wait time was positively associated with the number of patients visit each month. The average wait time was reduced by 35%, 69%, 54%, 44%, 37%, and 25% from January to June 2020 each month in comparison to the corresponding periods in 2019.

Determinants of health

Martin et al. [13] reported that male patients are associated with shorter waiting times in Canada. In 4 countries (Canada, Germany, Norway, and Sweden), household income was negatively associated with waiting times for primary care appointments. There was a negative correlation between education level and waiting times in Australia and France, but this relationship is only statistically significant at the 10% level. Patients with post-secondary and tertiary education experience 0.3 and 0.9 fewer days of waiting respectively, compared to those with primary and lower secondary education. The study did not find any significant association between chronic conditions and wait time except a positive association with depression and arthritis in Sweden and a negative association with coronary heart disease in Sweden and Switzerland. There was also a negative association between coverage by private health insurance and waiting times in Australia, Germany, and France.

Impacts of prolonging wait time for primary care appointments

Only 2 studies reported the impacts of the long waiting time on patients. A study by Melchiorre et al. [21] identified long waiting lists as one of the greatest challenges to accessing public health services, with long waiting times exacerbating poor health among older adults. A participant stated, “It is so long that I have booked a visit, and I am still waiting to do it. In the meantime, my health has deteriorated”.

Neville et al. [15] revealed that the pressure on local health services in New Zealand increases during summer due to the influx of tourists creating wait times for patients who need immediate appointments. A respondent reported “This summer I had a sort of bad back and rung up to see what they could do for me, and they couldn’t see me until next Friday! What was I meant to do? To be fair the nurse rang me back and talked to me about it, she is a local and was a great help, but the wait time was terrible”. (Colin, 79 years)

Discussion

Our systematic search of major health-related databases revealed a significant gap in evidence on primary care appointment waiting times, with only two studies specifically focused on older adults. The findings consistently highlight prolonged wait times as a substantial barrier to accessing primary care services, suggesting that these delays are not merely an inconvenience but a critical issue affecting patient outcomes – particularly for older populations. Even among high income countries with universal healthcare systems, such as Norway and Canada, waiting times vary considerably, signaling disparities in healthcare system efficiency and accessibility across countries.

Qualitative data deepens this understanding, shedding light on the real-life consequences of long waiting times. Patients frequently voiced frustration and anxiety over the difficulty of securing timely appointments, often resorting to emergency departments or walk-in clinics. These responses underscore how prolonged waiting times can delay essential care, which may force patients toward costlier and less efficient healthcare options, thereby increasing the overall burden on healthcare systems. If timely care is unavailable, patients may be left to endure worsening and prolonged health conditions.

Research that included other determinants of health, as well as age, demonstrate that wait times can differ according to gender, socio-economic status, education and other factors. Such findings must be situated within the context of the study to better understand the structural determinants of wait times among older adults and tailor responses to those most at risk of poor health outcomes and of prolonged wait times.

The COVID-19 pandemic exposed and exacerbated systemic weaknesses in healthcare delivery, particularly for older adults. In Canada, for example, older populations were disproportionately impacted, suffering not only from severe illness and higher mortality rates related to COVID-19 but also from secondary effects of pandemic policies, such as increased isolation, interrupted care, and higher out-of-pocket costs for necessities like transportation. To mitigate the effects of physical distancing policies, virtual care was rapidly scaled up despite limited evidence of its usability among older adults. Administrative data showed that about 60% of care appointments were virtual during the second year of COVID-19 (2021–2022). While in China, during the early months of the pandemic, Xu et al. (2022) observed a significant reduction in waiting times, due the scale up of virtual care. Virtual care continues to be scaled up around the world, yet there appears to be little research on how this trend effects wait times for older adults – a demographic that both often has greater need for primary care and maybe disproportionally impacted by digital divides. More research is needed not only on the effects of wait times on the health of older adults, but on the potential of virtual care to mitigate wait times for older adults.

Recommendations

To better support older adults in aging at home, healthcare systems must evolve and expand services to meet the growing demand for care. Older adults face substantial barriers, including a higher prevalence of comorbid conditions, mobility challenges, and age-related discrimination. These challenges are often magnified by intersecting social factors such as gender, race, ethnicity, and socioeconomic status, resulting in diverse and unequal experiences of healthcare access [23]. To address these complexities, future studies should address impacts of delayed access to primary care and advise policy makers with tailored solutions to ensure equitable access to care for all older adults.

Strengths and limitations

To the best of our knowledge, this is the first scoping review to address waiting times for older adults in primary care. Our study employed a systematic literature search, along with a comprehensive screening and data extraction process, to ensure validity and generalizability. However, by focusing specifically on older adults, we may have overlooked studies that included older adults within their samples but did not explicitly mention them in their titles or abstracts. Additionally, we acknowledge that our focus on waiting times for pre-booked primary care appointments excludes countries where healthcare operates on a first-come, first-served basis.

Conclusions

The evidence reviewed highlights that long waiting times for primary care appointments remain a significant barrier to accessing healthcare, particularly for older adults. However, despite the consensus that aging is a significant factor affecting access to primary care, evidence to show how long older patients wait to see their primary care providers is limited. Additionally, none of the studies examined the determinants of health exclusively within this population, leaving a gap in understanding how these factors uniquely impact older adults’ access to care. Meanwhile, the variability in waiting times across different regions and patient demographics underscores the need for targeted interventions to reduce disparities.

The COVID-19 pandemic has shown that significant reductions in waiting times are possible through virtual care, suggesting that lessons learned during this period could inform future strategies to improve access to primary care. Future studies addressing the underlying determinants of health that contribute to longer waiting times will be essential in ensuring equitable access to care for all patients.

Abbreviations

AI

Artificial intelligence

CI

Confidence interval

ED

Emergency department

FGD

Focus group discussion

FP

Family physician

GP / GPs

General practitioner / General practitioners

JBI

Joanna Briggs Institute

OR

Odds ratio

PRESS

Peer Review of Electronic Search Strategies

PRISMA

Preferred Reporting Items for Systematic reviews and Meta-Analyses

PRISMA-ScR

Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews

SD

Standard deviation

SFU

Simon Fraser University

VFMC

Victoria Family Medical Centre

Authors' contributions

AP developed the methodology and search strategies, screened and reviewed articles, and drafted the manuscript. IA screened and reviewed articles and wrote the results section. JS and MHT contributed to developing the methodology, search strategies, and discussion. All authors approved the final manuscript.

Funding

This study was funded by a Social Sciences and Humanities Research Council (SSHRC) Partnership Engage Grant (Grant number 1015-2023-0018). AP is supported by the Pacific Institute on Pathogen, Pandemic and Society at Simon Fraser University. JS is supported by a Michael Smith Health Research BC Scholar Award. The funders had no role in the design of the study, data collection, analysis, interpretation of data, or writing of the manuscript.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

Not applicable for a scoping review.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.