Our study aimed to identify a typology of care trajectories following diabetes diagnosis and to explore sociodemographic variables associated with trajectory-type membership. From this analysis, we describe three distinct patterns of all-cause health care utilization in the first 2 years following a diagnosis of diabetes in a cohort of people in Quebec. Forty-three percent of our sample followed a trajectory defined predominantly by regular FP care. Another 41% followed a trajectory comprising mostly specialist care with some involvement of regular FPs as well as “new” (non-regular) FPs. The rest (16%) followed a pattern characterized by few services overall. Those with few services spent an approximately equivalent amount of time in the hospital and emergency care state as those individuals following the Regular FP Trajectory.
Various methods have previously been used to explore and describe different patterns in healthcare utilization. One recent study measured care seeking as irregular provider contact, regular specialized care, and regular generalized care for diabetes based on yearly care patterns . Using group-based trajectory modeling over an 11-year period, they found seven trajectories (persistent irregular use, generalized to irregular, irregular to generalized, persistent generalized, generalized to specialized, specialized to generalized, and persistent specialized); membership to which differed by age, SES, and residential location . Another approach applied a tailored state sequence analysis to study where a service was undertaken, by which specialist, and for which diagnosis among a cohort of patients with chronic obstructive pulmonary disease followed for 1 year . Five trajectory types, corresponding to low healthcare utilization, moderate healthcare utilization, and three high utilization groups with predominantly respiratory diagnoses, cardiovascular diagnoses, and other diagnoses, respectively . Our analysis took a slightly different approach in assigning care states a lasting duration. Nevertheless, our results indicate a low utilization group, a moderate utilization group dominated by regular family physician care, and a higher utilization group dominated by specialist care.
Our results suggest a path dependence in access to care. Individuals in the Specialist Trajectory spent nearly twice as long overall in the hospital and emergency care state. It is conceivable that patients connect with specialists during a hospital encounter, and then potentially bypass the family physician or otherwise have direct follow ups with specialists . Indeed, diagnosis in a physician’s office (i.e., outside of hospital) was associated with lower odds of following the Specialist Trajectory than diagnosis in hospital, as compared to the Regular FP Trajectory. This may reflect differences in the pre-diagnosis trajectory, suggested also by the fact that comorbidities were statistically significantly higher in the Specialist Trajectory than the Regular FP Trajectory. People with the Few Services Trajectory showed no significant differences in comorbidities compared to those with the Regular FP Trajectory.
The second part of our objective was to investigate inequalities in care trajectories. We have argued that a trajectory favouring continuity of care with a regular FP is optimal, as it most closely represents the recommended chronic care management model of PCSCs . While we did observe some socially patterned differences in the odds of following different types of trajectories, we did not find strong evidence of social status privileging access to the Regular FP Trajectory. Immigrants and people with higher education had higher odds of following the Specialist Trajectory as compared to the Regular FP Trajectory. People with higher education also had higher odds of following the Few Services trajectory, which may seem a counterintuitive finding. This result could also be reflective of other dynamics including less frequent visits to a FP due to higher participation in diabetes management programs run outside the family physician’s clinic, or a higher perceived sense of control over condition management recommendations. However, a recent Canadian study has found that people with higher education reported greater difficulties in accessing health care, suggesting that there may be further explanations to explore. After accounting for comorbidities, older people had lower odds of following the Specialist Trajectory, as well as lower odds of following the Few Services Trajectory, likely because they already had access to a family physician.
Men were more likely than women to follow the Few Services Trajectory, as compared to the Regular FP Trajectory, a finding that is supported by studies showing that men are less likely to visit an FP compared to women .
Previous studies have shown a higher rate of specialist visits with higher income and education levels in Canada, even after adjusting for health care need, which suggests the potential influence of these factors on the likelihood of a referral from primary care . In the present study, we found that residents of areas outside of the large urban centre of Montreal were also less likely to follow the Specialist Trajectory. This could be attributable to geographic disparities in access to a family physician – the proportion of people in Montreal with a regular family physician is lower than elsewhere in the province  – or to a supply effect of the higher concentration of specialists in the urban centre of Montreal .
In our analysis, immigrants were more likely to follow the Specialist Trajectory than non-immigrants, as compared to the Regular FP Trajectory. Immigrants may be less likely to have access to a regular family physician , although other studies have not demonstrated this difference . Of note, we found that immigrants were no more likely to follow the Few Services Trajectory than non-immigrants after adjusting for place of residence. This suggests that the concentration of immigrants in a large urban area (Montreal, QC) was not driving the effect. However, grouping all immigrants into one category undoubtedly glosses over nuances.
Strengths and limitations
This study uses a novel cohort in Quebec of survey participants linked to administrative data, which allows richer socio-demographic data than is normally available in administrative data only.
This analysis was not designed to test causal differences in following different trajectory types. However, the socio demographic factors we explored here are all relatively time invariant and would be determined prior to the start of the trajectory. We have not yet assessed outcomes associated with trajectory types membership, which limits our ability to draw conclusions about their effectiveness. This will be the basis of our subsequent work in this area.
We used education instead of income as a proxy measure of SES; as the CCHS interview could occur at varying intervals around the start of the trajectory, we did not have an income measure consistent with the start of the trajectory. We thus opted for measures that would be fixed in time. In support of this decision, we note that in a universal care system with a single government payer, income would be less expected to impact access to or utilization of care. Education level, on the other hand, may influence health literacy and patients’ abilities to navigate the health system. Indeed, previous studies have found education to show stronger associations with health service utilization than income .
We defined a regular FP as the one providing at least half of an individual’s family medicine visits in the past year. While stricter definitions have been used , we still see important differences emerge with our broader approach. Importantly though, we are lacking information on registration with a groupe de médecin de famille (family medicine group, GMF), so we cannot rule out that the “non-regular” FP visits are not with another physician in an individual’s GMF. GMFs were designed to improve continuity of care, even when an individual is not able to see their own regular physician.
Finally, we could not distinguish between type 1 and 2 diabetes with our algorithm; however, given our age criteria of individuals 20 years old and above it is reasonable to assume that our cohort is primarily composed of individuals with type 2. Type 1 diabetes accounts for 5–10% of all diabetes diagnoses, and occurs mostly in children . Our approach to the analysis assessed all-cause health care utilization. It will be important in subsequent work to identify the intensity of diabetes-specific utilization within and among trajectory groups, and to distinguish this from other primary diagnoses associated with healthcare encounters.
Our approach to measure healthcare use maintains daily granularity. Alternatives include measuring use in wider time blocks, such as monthly. However, this would necessitate defining a hierarchy to account for the potential of multiple care states during the time period. As we were equally interested in the presence of each state, we wanted to avoid making hierarchical determinations. However, this daily approach may have been too granular to allow for changing longitudinal trends in care states to be detected (such as shifts from specialist to family physician care, or from new to regular family physician care, over time).
The benefit of sequence analysis is the ability to simultaneously consider the evolution of care interactions over time, without focusing explicitly on transitions between states – the trajectories are analysed as a static object, while allowing for dynamic patterns within . This is a significant benefit in chronic condition health care utilization research, where transitions between care states may be of less interest than the overall pattern of care.
Potential policy implications
The medical home model of health care prioritizes strong connections to a primary care provider or team, with support of specialist consultants as necessary. The Regular FP care trajectory that we used as reference fits well within this model and with that of PCSCs, which stipulates that most treatment, monitoring, and support for diabetes can and should occur in the primary care setting [17, 36]. To note, this care trajectory is not only deemed optimal for the patient, but also for the system, as it prevents unnecessary, more costly, and potentially invasive care .
Our analysis identified a pattern of specialist-predominant services that would generally not conform to the PCSC model. In fact, specialist care is not uniformly associated with better outcomes following a diabetes diagnosis, despite being associated with the use of appropriate diabetes-specific treatments . Efforts could be encouraged to link patients diagnosed in hospital with suitable family physicians willing to take charge of the chronic issue management, if a family physician is not already assigned. In Quebec, this could be implemented through the guichet d’accès à un médecin de famille (GAMF), which is a centralized intake and waitlist system for individuals seeking a family physician .