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Profiling patterns of patient experiences of access and continuity at team-based primary healthcare clinics (Canada): a latent class analysis

International Journal for Equity in Health volume 23, Article number: 213 (2024) Cite this article

Abstract

Background

Access to primary healthcare services is a core lever for reducing health inequalities. Population groups living with certain individual social characteristics are disproportionately more likely to experience barriers accessing care. This study identified profiles of access and continuity experiences of patients registered with a family physician working in team-based primary healthcare clinics and explored the associations of these profiles with individual and organizational characteristics.

Methods

A cross-sectional e-survey was conducted between September 2022 and April 2023. All registered adult patients with an email address at 104 team-based primary healthcare clinics in Quebec were invited to participate. Latent class analysis was used to identify patient profiles based on nine components of access to care and continuity experiences. Multinomial logistic regression models were fit to analyze each profile’s association with ten characteristics related to individual sociodemographics, perceived heath status, chronic conditions and two related to clinic area and size.

Results

Based on 87,155 patients who reported on their experience, four profiles were identified. “Easy access and continuity” (42% of respondents) was characterized by ease in almost all access and continuity components. Three profiles were characterized by diverging access and/or continuity difficulties. “Challenging booking” (32%) was characterized by patients having to try several times to obtain an appointment at their clinic. “Challenging continuity” (9%) was characterized by patients having to repeat information that should have been in their file. “Access and continuity barriers” (16%) was characterized by difficulties with all access and continuity components. Female gender and poor perceived health significantly increased the risk of belonging to the three profiles associated with difficulties by 1.5. Being a recently arrived immigrant (p = 0.036), having less than a high school education (p = 0.002) and being registered at a large clinic (p < 0.001) were associated with experiencing booking difficulties. Having at least one chronic condition (p = 0.004) or poor perceived mental health (p = 0.048) were associated with experiencing continuity difficulties.

Conclusions

These results highlight individual social and health characteristics associated with increased risk of experiencing healthcare access difficulties, such as immigration status and education level and/or continuity difficulties when having a chronic condition and poor perceived mental health. Facilitating appointment booking for recently arrived immigrants and patients with low education, integrating interprofessional collaboration practices for patients with chronic conditions and improving care coordination and communication for patients with mental health needs are recommended.

Background

Access to primary healthcare services is one of the core levers for reducing health inequalities [1,2,3,4]. To compare healthcare systems’ access efficiency, the organizational characteristic related to timely access is the most frequently measured [5]. However, access to care also involves responding to health needs of patients with a diverse combination of individual and social characteristics [4]. Patients’ experience of access to care is defined as a process with steps such as perceiving the need for care, seeking and obtaining healthcare services [4, 6]. Inequitable healthcare occurs when access varies by social characteristics rather than need [4, 7,8,9]. The presence of one or more social characteristics such as poverty, isolation, age and discrimination has been associated with greater negative impacts on the experience of accessing and receiving healthcare [4, 7,8,9,10,11]. Population groups living with certain individual social characteristics are disproportionately more likely to experience barriers to accessing care, such as foregone care due to cost, inability to attend appointments during limited opening hours at their clinic and an overall lack of timely access to care [4, 12].

Low income contributes to barriers to accessing primary healthcare prior to and after obtaining care [4, 12,13,14,15,16]. Additionally, being an immigrant increases the likelihood of experiencing multiple barriers after accessing primary healthcare [12] and is associated with lower rates of affiliation with a provider and greater unmet health needs [17] as well as higher emergency room use, especially among those who immigrated in the last 10 years [4]. Indigenous/Aboriginal individuals and people with low education levels and low social support also experience frequent issues with access [4]. Although the elderly (65 + years of age) are less likely to report barriers to accessing primary healthcare, having multiple chronic conditions leads to greater difficulties accessing care in relation to hours available for appointments [18]. Also, patients with mental health conditions experience more access difficulties due to higher out-of-pocket healthcare costs [18]. Finally, comparisons of access in Organisation for Economic Co-operation and Development countries showed that women were more likely to experience multiple barriers prior to obtaining care in New Zealand and after obtaining care in France and Sweden but not in Canada [12]. When individual social characteristics resulting in barriers to accessing care accumulate and interact, the use of urgent care for general access and primary healthcare increases, as do unmet care needs, inappropriate treatment and deteriorated health status [4, 19].

Another main dimension of primary healthcare is the continuity of care that encompasses three types of continuity known as informational continuity, based on “the use of information on past events and personal circumstances to make current care appropriate for each individual,” management continuity as “a consistent and coherent approach to the management of a health condition that is responsive to a patient's changing needs,” and relational continuity as “an ongoing therapeutic relationship between a patient and one or more providers.” [20]. From a patients’ perspective, barriers are also perceived after accessing care related to continuity, such as care providers not listening carefully, not knowing the patient’s medical history, not coordinating care, and not spending enough time with patients [4, 12]. Our previous pilot study to this research among patients experiencing multiple barriers to accessing care resulted in an increase in urgent care use for general access [4, 21], however, we found that continuity with their family physician was a key-element in reducing their ER use [22].

Given the many possible configurations of individual social characteristics, individual perceptions for care needs and actions related to seeking and reaching care [4, 6, 23], it is relevant to profile subgroups with similar patterns of access and continuity difficulties. There is still limited research based on patient experiences investigating the characteristics that result in multiple barriers to access to primary healthcare [4, 12]. The objective of this study is to identify different profiles of access and continuity experiences of patients registered with a family physician in team-based primary healthcare clinics and explore how these profiles are associated with individual and organizational characteristics.

Methods

Study design and setting

This study is based on a cross-sectional e-survey hosted on a web platform conducted between September 2022 and April 2023 among registered patients of team-based primary healthcare clinics in Quebec, Canada. This study is part of a cluster-controlled trial on the impact of an externally facilitated continued quality improvement cohort on advanced access. As part of the recruitment for the trial, all clinics located in the province of Quebec were invited to participate to the benchmark part on access and continuity [24].Those not meeting the inclusion/exclusion criteria were offered to be part of a benchmarking database which include the data collection process presented in this paper.

Recruited team-based primary healthcare clinics included family physicians, nurse practitioners, nurses, social workers and pharmacists. In 2021 in Quebec, 87% of patients are registered to a family physician or a nurse practitioner [25, 26]. This constitutes a formal patient-provider agreement confirming the therapeutic relationship [25, 26]. Patients registered with a family physician do not have quite the same characteristics as the general population. They are more likely to be women, seniors and patients with chronic illnesses [26].

Content of the patient survey

The e-survey questionnaire consisted of 34 items including 5 items related to patient profile and 29 items related to access and continuity of care based on four main dimensions: 1) pre-booking (actions taken before booking an appointment), 2) the appointment booking process, 3) access to the clinic (reaching the clinic, obtaining healthcare or advice, opening hours, reasons to consult elsewhere) and 4) care continuity (communication with team members, interprofessional collaboration). Among the 29 items on access and continuity of care, 4 items had a QI-oriented purpose and were designed based on clinics perspective aiming to improve their performance and services and 25 items reflected the patient-centered process definition chosen for this study [4, 6].

The e-survey also included sociodemographic characteristics comprised of three variables related to health perception, mental health perception and having at least one chronic condition [24]. The questionnaire was developed based on existing validated questionnaires to document the four dimensions of access and combined by a research steering committee that included a patient-partner committee (n = 5) and an expert committee (n = 5). Pre-booking and booking experience were assessed by mapping questions from the GP [general practitioner] patient survey [27], the Primary Care Assessment Survey (PCAS) [28] and the Patients' Insights and Views of Teamwork (PIVOT) [29]. We used a shortened version of the organizational accommodation questionnaire [30] and the generic measure of continuity of care questionnaire [31] to assess access to the clinic and care continuity (Appendix 1).

The questionnaire was pilot tested in the fall of 2021 with 1562 patients from four team-based primary healthcare clinics in Quebec to assess its face validity [22]. Following that pilot project, the expert committee (n = 5, including experts on access to care inequity, interprofessional collaboration, and integrated multidisciplinary primary care models) in collaboration with the patient-partner committee (n = 5) qualitatively assessed the content validity. Experts and patients were asked to rate each item based on their relevance to the evaluation of access to care and the continuity experience. They were also prompted to comment on the formulation of the items. The final version of the questionnaire was pre-tested with 20 patients with low literacy levels using cognitive testing. Three questions were reformulated and two were shortened to increase their readability and understanding. The order of answers was changed for one question so the most common answers were the first choices [32].

Data collection

The questionnaire was distributed electronically by an administrative assistant at each clinic to all registered patients with an email address in their electronic medical record. Only adult respondents were asked to complete the anonymous questionnaire on a voluntary basis. However, respondents could answer for another person (e.g., child). The research team prepared an email message for the administrative assistant inviting patients to participate in the e-survey. The self-administered questionnaire took approximately 20 min to complete.

Analysis

In this study, respondents were grouped into profiles according to similarities based on a clustering classification algorithm namely latent class analysis (LCA). LCA is centred on individual experiences and examines how variables combine across individuals, as opposed to analyses that investigate how variables relate to each other (e.g., regression models) [33]. LCA seeks to identify homogeneous groups within a heterogeneous population [34]. Individuals in the same class share a common joint probability distribution among the observed variables (e.g., the same access difficulties profile) and are clustered in distinct latent classes, each of which represents a similar experience.

Among the 25 items covering patients access and continuity experience, the expert committee selected 13 components for LCA based on the literature on access, and the factors known to influence or not access to care from a patient perspective [6, 12]. The 9 items that had a concept similar to another item selected to represent better this concept were excluded, as well as the 2 items that implied multiple embedded socio-economic factors and the 1 filter question. The LCA was initially based on 13 components. Nine components were based on access: 1) needing to try several times to obtain an appointment at the clinic; 2) actions taken to obtain information or advice before booking an appointment; 3) perception of the appointment booking experience; 4) ease of reaching the clinic for booking; 5) ease of getting to the clinic; 6) difficulty obtaining care due to lack of physician availability; 7) perception of opening hours for appointments; 8) consultation at another clinic for minor emergencies; and 9) consultation at a hospital ER to obtain health care. Four components were based on continuity: 10) having the impression that no one was in charge of their file; 11) receiving contradictory information; 12) team members not being aware of decisions made by another professional on the team; and 13) having to repeat information that should have been in their file (Appendix 1).

The LCA technique automatically excludes respondents who have missing data on one of the components included in the model. The recommended threshold of missing data allowed to avoid bias in survey-based research is 20% [35]. This required removing 9 items, resulting in a 4-item model, which was not acceptable given the recommendation of 12–16 items for a model with 3–4 classes [36]. In order to maximise the balance between the concept representativity and ensure as many respondents as possible were included in the model, the expert committee decided to increase the threshold for missing data by 5%, which meant excluding four components: actions taken to obtain information or advice before booking an appointment (26%); perception of the appointment booking experience (34%); difficulty obtaining care due to lack of physician availability (34%); and having the impression that no one was in charge of their file (34%) (Appendix 2). We also compared the sample of LCA with the respondents to the survey with missing data. There were differences in the socio-demographic characteristics such as age, gender, social support, chronic disease, education, physical health, mental health and urban/rural living area.

The data analysis was conducted in four steps.

  • Step 1. Descriptive analyses were used to describe the response frequencies (% valid) of the nine components included in the LCA (Appendix 2), the seven respondent sociodemographic characteristics (gender, age, indigenous origin, immigration status, financial situation, education, social support) and three variables related to health perception (chronic condition, perception of health and mental health status). Due to differences in access due to organizational settings, two characteristics related to clinic geographic area and size (using a threshold of 15,000 registered patients) were also explored. We also included some descriptive analyses of explanatory variables that could not be included in the model because of the loss of respondents’ effect due to the LCA technique but remain relevant to understand the access and continuity experiences.

  • Step 2. LCA was used to identify latent classes with different patterns of access to the clinic and care continuity difficulties. The determination of the optimal number of classes in the model was made by the expert committee following commonly used criteria [37]: the model chosen is an acceptable fit representing the responses to the items included in the LCA informed by the Akaike information criterion (AIC), [38] the Bayesian information criterion (BIC) [37, 39], lowest values indicate a better-fitting model; the model chosen is able to accurately classify respondents into groups [37] and entropy, is a classification quality measure we used to assess the precision with which respondents can be assigned to classes based on their probabilities (e.g. the closest to 1 is the best) with 95% confidence intervals (CIs) [40]; The final model is ultimately chosen for its interpretability, meaning that it allows for meaningful labels to be assigned to each class based on their ability to be qualitatively distinguished from the other classes. [37].

  • Step 3. Three meetings with the expert committee were held to characterize and name the classes according to their distinguishing characteristics [39].

  • Step 4. Associations between individual and organizational characteristics and latent class membership were assessed using multivariate analysis to investigate how each sociodemographic, health and organizational characteristic predicted class membership using a multinomial logistic regression model including gender, age, perceived financial situation, education, social support, indigenous origin, immigration status, chronic conditions, perceived health and mental health status and clinic geographic location and size. Associations were evaluated using odds ratios (ORs) with 95% confidence intervals (CIs). Each odds ratio was adjusted for the remaining characteristics in the model. Analyses were conducted using SAS 9.4 (SAS Institute, Cary, NC, USA), MPlus software for LCA and IBM SPSS, version 26 for statistical analyses (IBM Corp., Armonk, NY, USA).

Results

Sample description

Of the 560,465 registered patients who had an email address in their electronic medical record and were contacted in the 104 participating clinics across the province, a total of 120,075 completed the e-survey, for an overall response rate of 21%. The size of the clinics varied from 1000 to 25,000 registered patients for 2 to 20 family physicians. The LCA technique automatically excludes respondents who have missing data on one of the 9 components included in the model, meaning that of the 120,075 participants, 87,155 respondents answered the all components selected for LCA. Table 1 presents the descriptive results of individual and organizational characteristics of the sample included in the LCA.

Table 1. Descriptive results of individual and organizational characteristics of the study sample included in the LCA, n (%)
Full size table

LCA results: Patient experiences of access and continuity profiles

The four-class model appeared to have the best interpretation potential. Among the 8 models, the 4-class model had the best classification quality entropy (closest to 1) combined with the adjustment indices (AIC/BIC), which have to be the lowest possible. It also has a sufficient variety of profiles’ experiences without having too much similarity with each other. This model was chosen based on its balance between statistics and meaningful labelling richness. The LCA results are summarized in Table 2.

Table 2. Statistics for latent class analysis
Full size table

Four profiles were identified, including one profile characterized by ease of access and continuity for all components that represented 42% of the sample. The three other profiles were characterized by diverging access and continuity difficulties. Table 3 presents the four profiles and probabilities of experiencing difficulties for each component of access to the clinic and continuity of care experience.

Table 3. Class proportions and class-specific probabilities for four-profile latent-class model of difficulties related to access to the clinic and continuity experiences
Full size table

The profile "Easy access and continuity" was the most common profile, representing 42% of the sample (n = 36,694). This class was characterized by a low probability of experiencing access difficulties related to booking an appointment, the lowest probability of receiving contradictory information and a low probability of experiencing continuity difficulties (e.g., team members not being aware of other professional’s decisions, having to repeat information that should have been in their file). This profile was also characterized by the lowest probability of patients consulting at another clinic for minor emergencies and/or at a hospital ER to obtain health care.

The profile "Challenging booking" represented one-third of respondents (n = 27,874, 32%) and was characterized by high probabilities of experiencing access difficulties related to reaching the clinic to book an appointment (e.g., having to try several times to obtain an appointment at their clinic and experiencing difficulties reaching the clinic to book an appointment). This profile had the second highest probability of consulting at another clinic for a minor emergency (0.14 [0.04, 0.31]). However, this profile was composed of patients with a low probability of experiencing continuity difficulties. Among the 15% of these respondents who reported having consulted at another clinic in the past 12 months, the main reasons reported were that no appointments were available at their clinic (52%) and that their family physician was not available (51%).

The profile "Challenging continuity" was composed of nearly one-tenth of the sample (9%, n = 8379). This profile was characterized by a low probability of experiencing access difficulties related to booking an appointment but a high probability of experiencing continuity difficulties, such as receiving contradictory information, team members not being aware of other professional’s decisions and having to repeat information that should have been in their file. This profile was also characterized by a low probability of patients consulting at another clinic for a minor emergency but had the second highest probability of patients consulting at the ER to obtain care (0.26 [0.16, 0.38]). Of the 30% of these respondents who reported having consulted at a hospital ER in the past 12 months, the main reasons reported were that the clinic was closed at the time they needed healthcare (18.6%) and that their family physician was not available (12%).

The profile "Access and continuity barriers" represented 16% of the respondents (n = 14,208) and was characterized by the highest probability of experiencing difficulties with all access and continuity components. This profile also had the highest probability of consulting at another clinic for a minor emergency (30%) and at a hospital ER to obtain health care (38%). Unavailability of their family physician was the main reason these respondents consulted at another clinic (61%) or at the ER (59%).

Individual and organizational characteristic analysis

The results of how each individual (sociodemographic and health) and organizational characteristic predicted profile membership are presented in Table 4.

Table 4. Characteristics and multinomial logistic regression results for covariates by latent access and continuity difficulties class
Full size table

The "Easy access and continuity" profile was used as a reference for the multinomial logistic regression model with ten individual characteristics and two organizational characteristics (clinic area and size). Each OR presented in Table 3 was adjusted for the remaining characteristics in the model.

Female gender and poor perceived health significantly increased the risk of belonging to the three difficulties profiles by at least 1.5. Furthermore, poor perceived health was almost three times more likely to be associated with belonging to "Access and continuity barriers," the profile with the highest probability of experiencing difficulties with all access and continuity components (adjusted OR = 2.8 [2.3, 3.0]; p = 0.001).

Some characteristics such as being a recently arrived immigrant increased the risk of belonging to the profile "Challenging booking" (adjusted OR = 1.2 [1.0, 1.4]; p = 0.036). Having less than a high school education and being registered at a large clinic also increased the risk of belonging to the profiles "Challenging booking" (adjusted OR = 1.9 [1.4, 2.6]; p = 0.002 and adjusted OR = 1.4 [1.3, 1.6]; p < 0.001, respectively) and "Access and continuity barriers" (adjusted OR = 2.4 [1.7, 3.5]; p = 0.001 and adjusted OR = 1.4 [1.3, 1.6]; p < 0.001, respectively).

Some individual health characteristics such as having at least one chronic condition or poor perceived mental health, which increased the risk of belonging to the two continuity difficulties profiles "Challenging continuity" (adjusted OR = 1.4 [1.1, 1.7]; p = 0.004 and adjusted OR = 1.5 [1.1, 1.9]; p = 0.048, respectively) and "Access and continuity barriers" (adjusted OR = 1.3 [1.1, 1.5]; p = 0.001 and adjusted OR = 1.8 [1.4, 2.1]; p < 0.001, respectively).

Finally, low social support (adjusted OR = 1.4 [1.1, 1.7]; p = 0.001), having a poor to very tight financial situation (adjusted OR = 1.5 [1.2, 1.9]; p = 0.019) and being 55–69 years of age (adjusted OR = 1.2 [0.9, 1.5]; p < 0.001) increased the risk of belonging to the profile with the highest probability of experiencing difficulties with all access and continuity components, “Access and continuity barriers". The age of 18–34 increased the risk of belonging to this profile by almost threefold (adjusted OR = 2.6 [2.0, 3.4]; p < 0.001).

Discussion

We aimed to identify different profiles of access and continuity experiences of patients registered with a family physician in a team-based primary healthcare clinics and to explore how these profiles are associated with individual and organizational characteristics. Our results revealed four profiles, one with easy access in almost all access and continuity components and three profiles with access and/or continuity difficulties. Along with other studies, our results show inequitable access and continuity related to multiple and interacting social characteristics [4, 6,7,8,9]. This study adds to the literature by clarifying how specific individual social characteristics based on patients’ experience are associated with an increased risk of experiencing particular access and/or continuity difficulties.

Our results showing that poor to very tight perceived financial situation increases the risk of belonging to the profile characterized by the highest probability of experiencing difficulties related to access and continuity are in line with other studies that underscored how social vulnerability leads to barriers to obtaining care [4, 12, 13, 15]. Also, as utilization of the ER is frequently used as a proxy to measure difficulties in accessing care, our results concur with other studies related to combined social vulnerabilities and inequity in access to healthcare [4, 41]. However, our results add social characteristics associated with an increased risk of experiencing access and continuity difficulties.

First, female gender increased the likelihood of belonging to the three profiles of access and continuity difficulties by almost 1.5. However, this result differs from those of the access study comparing Organisation for Economic Co-operation and Development countries, which found that women in Canada were less likely to experience multiple barriers prior to and after reaching care [12]. Another study on the association between individual and social characteristics and ability to access healthcare conducted in Australia and Canada, which included some cases from Quebec, came to the same conclusion [4]. The fact that our results showed that the likelihood of belonging to the three access and continuity profiles was also associated with poor perceived health may explain this difference. It may be interesting, in future research and/or interventions aimed to improve access in primary healthcare settings, to analyse these two social characteristics in combination.

Being a recent immigrant and/or having a level of education less than high school were associated with an increased risk of booking difficulties. Our results align with another study showing that low educational level combined with immigrant status were predictive of problematic access [4]. In our results, access difficulties related to booking an appointment were also associated with the clinic having more than 15,000 registered patients. Navigation healthcare service initiatives can contribute to alleviating barriers to obtaining adequate health care [42] and can be adapted to the specific context of clinics with more than 15,000 registered patients. Other studies on navigation needs among socially vulnerable patients and immigrants reported that they expected to be provided with pragmatic information on available resources (types and location), including team-based primary healthcare clinics tailored to their realities and needs, and information on processes to follow to access and use these resources, such as how to schedule appointments and where to go for specific medical services [43].

Having a chronic condition and mental health care needs were associated with an increased risk of experiencing continuity difficulties related to communication (between patients and professionals and among the clinical team) and unavailability of family physicians. Integrating interprofessional practices and information transfer strategies for care coordination combined with navigation interventions may help tailor care experiences to the needs of these patients [43,44,45,46]. For patients with chronic conditions, studies have shown that integrating interprofessional practices, such as strategies that lead to a shared practice between family physicians and registered nurses and assigning nurse practitioners to leadership roles in managing the care of patients with chronic conditions, helps to reduce physician visits [45] and improve timely access in primary healthcare [47]. Also, sharing information about health conditions, self-management and treatment with patients, particularly those living with chronic conditions, enables and empowers them to play an active role in their own care, such as by implementing monitoring and self-care [44].

However, not all patients are in a position to assume an active role in their care monitoring and management, and some may need a single trusted clinician to help them navigate the system [44]. Also, regarding mental health needs, including psychologists on medical teams and having physicians inform their patients about psychological services have been shown to improve patient experiences of care (satisfaction, symptom reduction, quality of life) [48]. Navigation interventions led by a trained person with or without clinical expertise (e.g., patients and volunteers, medical professionals, social workers, health educators, etc.) [42] have been shown to facilitate care coordination in primary healthcare teams by improving communication between clinicians and patients [46] and by providing needed emotional support [42]. These roles may replace the family physician as the trusted person when they are not available when needed and contribute to reduced ER use for primary healthcare needs [46].

Study strengths and limitations

We followed the STROBE reporting guidelines for cross sectional online surveys [49]. The strength of this study is the size of the sample. To our knowledge, no other study has been conducted with more than 100,000 patients in Quebec. The sample allowed us to examine associations for several individual vulnerability characteristics with high power. Nevertheless, certain aspects of this study may limit the generalizability of the findings. First, it was conducted in team-based primary healthcare clinics in Quebec, which have particular characteristics, notably their various remuneration modalities (i.e., physicians are mainly remunerated on a fee-for-service basis, whereas nurse practitioners and nurses are employed by public organizations and remunerated by salary) [50]. Second, we sent the questionnaire only to patients with an email address in their electronic medical record. Although this data collection method is low cost, it may have introduced a response bias, with patients with the highest vulnerability scores being underrepresented [51]. To reduce these biases, future research should include recruitment strategies such as adapting the communication modalities for recruitment and data collection to occur close to where people are and when it is convenient for them (e.g., partnering with community organizations) and offering meaningful incentives [51]. Our differing conclusions from other studies [4, 12] related to women experiencing increased access and continuity difficulties may be interesting to investigate in combination with health status perceptions in further research. Using a listwise deletion technique combined with our goal to capture the experience of as many of our respondents, reduced the components of the access and continuity of care experience to 9 of 26 items, which was offset by our large sample size.

Conclusions

Based on patient experiences of access to care and continuity, four profiles were identified. One profile was characterized by ease in almost all access and continuity components and three profiles were characterized by diverging access and/or continuity difficulties. These results highlight difficulties related to access and continuity of care for patients with specific individual characteristics, such as female gender and poor perceived health. Difficulties booking an appointment at their clinic were experienced by patients that were recently arrived immigrants, had less than a high school education and were registered at a large clinic. Difficulties related to continuity of care were experienced by patients who have at least one chronic condition or poor perceived mental health. These results indicate that a one-size-fits-all model is not recommended. Personalized strategies need to be considered when socially vulnerable populations are concerned, such as implementing strategies to facilitate appointment booking for recently-arrived immigrants or patients with low education levels and integrating and adapting models of interprofessional collaboration that work for other groups (e.g., patients with chronic diseases or mental health needs) to help decrease and better coordinate the use of services. Lastly, enhanced information transfer and communication are needed between clinical teams and patients with chronic conditions and mental health care needs. Female patients with poor perceived health and patients with poor to very tight financial perceived situation may benefit from a combination of these strategies.

Availability of data and materials

The data are available on request for research purposes at acces.adapte@usherbrooke.ca.

Abbreviations

AIC:

Akaike information criterion

BIC:

Bayesian information criterion

CIs:

Confidence intervals

ER:

Emergency room

LCA:

Latent class analysis

ORs:

Odds ratios

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Acknowledgements

The authors are grateful to Elisabeth Martin, Christine Beaulieu, Sarah Descôteaux and François Bordeleau for contributing to the design of the protocol and questionnaire and data collection.

Funding

This study was supported by a grant from the Canadian Institutes of Health Research, the Fonds de recherche du Québec and the Ministère de la santé et des services sociaux du Québec.

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Authors and Affiliations

  1. Department of Community Health, Université de Sherbrooke, 150 Place Charles-Le Moyne, Room 200, Longueuil CampusLongueuil, QC, J4K 0A8, Canada

    Nadia Deville-Stoetzel, Djamal Berbiche & Mylaine Breton

  2. Department of Family Medicine and Emergency Medicine, Université de Sherbrooke, Longueuil, QC, Canada

    Isabelle Gaboury

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  1. Nadia Deville-Stoetzel
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Contributions

NDS, MB, and IG have made substantial contributions to the conception or design of the work; and the acquisition, analysis, and interpretation of data. DB has made substantial contributions to the analysis and interpretation of data.  NDS has drafted the work and all authors have substantively revised it and have approved the submitted version (and any substantially modified version that involves the author's contribution to the study) and have agreed both to be personally accountable for the author's own contributions and to ensure that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature.

Corresponding author

Correspondence to Nadia Deville-Stoetzel.

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Ethics and consent to participate

This study was approved by the Research Ethics Committee of the Centre de recherche – Hôpital Charles-Le Moyne of the CISSS de la Montérégie-Centre (MP-04–2022-696). In an invitation email, participants were provided with information on the study and a link to the online information and consent form approved by the Research Ethics Committee. Once they consented to participate, they could access to the survey to be completed.

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The authors consent for this research to be published.

Competing interests

The authors declare no competing interests.

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Appendix

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Deville-Stoetzel, N., Gaboury, I., Berbiche, D. et al. Profiling patterns of patient experiences of access and continuity at team-based primary healthcare clinics (Canada): a latent class analysis. Int J Equity Health 23, 213 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12939-024-02300-6

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International Journal for Equity in Health

ISSN: 1475-9276

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