Research ArticleResearch

Age equity in different models of primary care practice in Ontario

Simone Dahrouge, William Hogg, Meltem Tuna, Grant Russell, Rose Ann Devlin, Peter Tugwell and Elizabeth Kristjansson
Canadian Family Physician November 2011; 57 (11) 1300-1309;

Abstract

Objective To assess whether the model of service delivery affects the equity of the care provided across age groups.

Design Cross-sectional study.

Setting Ontario.

Participants One hundred thirty-seven practices, including traditional fee-for-service practices, salaried community health centres (CHCs), and capitation-based family health networks and health service organizations.

Main outcome measures To compare the quality of care across age groups using multilevel linear or logistic regressions. Health service delivery measures and health promotion were assessed through patient surveys (N = 5111), which were based on the Primary Care Assessment Tool, and prevention and chronic disease management were assessed, based on Canadian recommendations for care, through chart abstraction (N = 4 108).

Results Older individuals reported better health service delivery in all models. This age effect ranged from 1.9% to 5.7%, and was larger in the 2 capitation-based models. Individuals aged younger than 30 years attending CHCs had more features of disadvantage (ie, living below the poverty line and without high school education) and were more likely than older individuals to report discussing at least 1 health promotion subject at the index visit. These differences were deemed an appropriate response to greater needs in these younger individuals. The prevention score showed an age-sex interaction in all models, with adherence to recommended care dropping with age for women. These results are largely attributable to the fact that maneuvers recommended for younger women are considerably more likely to be performed than other maneuvers. Chronic disease management scores showed an inverted U relationship with age in fee-for-service practices, family health networks, and health service organizations but not in CHCs.

Conclusion The salaried model might have an organizational structure that is more conducive to providing appropriate care across age groups. The thrust toward adopting capitation-based payment is unlikely to have an effect on age disparities.

Equity in health care concerns “fair arrangements that allow equal geographic, economical, and cultural access to available health care for all in equal need of care.”1 According to Culyer and Wagstaff, the main focus of equity in health care should, insofar as possible, be achieving equal health for all.2 Two main forms of health care equity exist: vertical equity, in which preferential treatment is given to those with greater health needs, and horizontal equity, in which equal treatment is provided for equivalent needs.3 Equity in access to health care is a key goal of health care systems in many countries.4

In the 1960s, Canada introduced a publicly financed health care system, which included free access to medical services provided by hospitals and physicians. More than half of all physician visits are made to family doctors5; and investments in primary care have been advocated as a means to strengthen health care systems and mitigate health inequities.4,6–10

For many years, primary care delivery in Ontario, Canada’s most populous province, has relied on fee-for-service (FFS) practice, in which compensation is directly related to the types and number of services rendered. Beginning in the 1970s, the province introduced community health centres (CHCs)—a community-oriented, multidisciplinary primary care model that focused on social justice and equity and had salaried providers. Today, CHCs serve approximately 3% of the Ontario population.11–13 In the same decade, the province introduced a capitation-based model for delivering primary care services, health service organizations (HSOs), in which family physician compensation was based on the number and age-sex profiles of patients registered to them.14 It was believed that the dissociation between patient visit and physician payment would result in a more equitable delivery of care, in which there was a greater focus on patient need rather than output. In the past decade, Ontario has continued its investments in models of care in which providers derive the largest proportion of their compensation from capitation payments. Family health networks (FHNs) are an example of this. Today, FHNs and other capitation models serve approximately 40% of the Ontario population. As a result of these reform initiatives, Ontario now has various primary care payment models, providing a unique opportunity to evaluate the impact of these structures, unconfounded by time or contextual factors. Some studies have focused on evaluating the effect of these different models on the quality of care,15–17 but only one has sought to assess whether these models have had an effect on the equity of the care delivered to men and women across a broad spectrum of needs.18

This study is part of a larger evaluation exploring the effect of these 4 primary care models (FFS, CHC, HSO, and FHN) on equity.18 This study aimed to describe the profile of patients across age groups in order to understand their health care needs; determine the extent to which disparities in the quality of care delivered across age groups in family practices exist; and assess whether the extent of these disparities varies between primary care models.

METHODS

Design

This analysis used a data set collected for a study conducted in 2005 to 2006: the Comparison of Models of Primary Care.19 The study was approved by the Ottawa Hospital Research Ethics Board.

Sample

The Comparison of Models of Primary Care was a cross-sectional study evaluating care in FFS (including family health groups), CHC, HSO, and FHN practices. The study approached all known and eligible FHN (N = 94), CHC (N = 51), and HSO (N = 65) practices. We also approached a random sample of 155 FFS practices from a list of 1884 practices. Recruitment efforts were discontinued when 35 practices of each primary care model of service delivery agreed to participate or when time constraints required us to cease recruiting. We recruited 35 CHC, FFS, and FHN practices, as well as 32 HSO practices. Details of the study methodology and key features of the model are reported elsewhere.19

Data collection

In each practice we surveyed patients (30 to 50 per practice) and conducted chart reviews (30 per practice). Surveyed patients were required to be under the care of one of the participating providers; aged 18 years or older; not severely ill or cognitively impaired; able to communicate in English or French either directly or through a translator; and attending the practice on the day of survey administration. Charts reviewed were limited to patients aged 17 years and older who had been with the practice for at least 2 years.

Instruments

Patient surveys were adapted from the Primary Care Assessment Tool–Adult edition20,21 and supplemented with 2 scales.22,23 The largest portion of the survey was completed before the encounter with the provider and measured the quality of health service delivery and elicited patient sociodemographic and economic information. The second portion, a single page, was completed after the visit and captured information relating to that “index visit,” including a measure of health promotion activity. The survey tool was available in English and French.24

We measured preventive care and chronic disease management by comparing documented activities (intent, recommendations, or actions relating to a maneuver) in the chart against indicators from recommended guidelines.

Performance measures

We assessed performance across 7 dimensions of health service delivery and 3 dimensions of technical quality of care (Table 1).20,21,23,25–33 In each case, the score was normalized to be represented as a percentage.

View this table:
Table 1

Scales for the measurement of performance; range of overall PCAT* scores was 86% to 88% (N = 5073): A) Dimensions of quality of health care service delivery; B) Technical quality of clinical care delivery.

Analysis

Description of patient profile

To understand the health needs of the various age groups, we compared the profile of patients in each group using Pearson χ2 statistics and ANOVA (analysis of variance), as appropriate.

Age disparities in measures of performance

Because this is an exploratory study, age was grouped into categories based on its relationship with the outcome of interest. To demonstrate the effect of age on performance, we compared the scores of older individuals to those of individuals in the youngest category. For all analyses, except chronic disease management, we performed multilevel linear or logistic regressions using the Glimmix procedure in SAS (Statistical Analysis System, version 9.1), as appropriate, to account for the clustering effect of patients within practices. Because of the small number of eligible charts per practice, chronic disease management was evaluated using standard linear regression.

Analyses in which we adjusted for health assessed horizontal equity (For health needs made equal, is care similar?), while those analyses in which we did not adjust for health assessed vertical equity (If greater health needs could be demonstrated for a group, is care greater?). Based on the different health profiles of patients from various age groups, we determined that older individuals would require more health services. For that reason, our primary analysis for health service delivery included adjustments for patient socioeconomic characteristics but not for health to assess vertical equity (more services for more need). In a second analysis, we added measures of health to assess whether the observed differences were in fact due to the differing health status. Because health lifestyle advice is believed to be equally important across all age groups, our primary analysis for health promotion included adjustments for socioeconomic characteristics and health status and assessed horizontal equity (same care for same need). In a secondary analysis, we excluded health variables to determine the effect of health on differences observed. Prevention and chronic disease management analyses were based on chart abstraction data and could be adjusted for sex, rurality, and insurance status only. In all analyses, age-sex interactions were evaluated and used where appropriate. All analyses were stratified by model.

Model comparison

To determine whether the age disparities within each model were different across the primary care models, we compared the effect size (absolute β values) of the age variable derived from the regression models described above across models using t statistics. Where meaningful differences (larger than 5%) in the age disparities for the overall score of a dimension were observed between models, we used regression analysis to provide an estimate of the performance level for the “typical” patient in each age group by model. This allowed the performance level of the age reference group to be represented along the disparity measures.

RESULTS

Characteristics of the study population

Patient surveys were completed by 5361 individuals (response rate of 79%), 5111 of whom indicated their age. Age was known for all 4108 charts reviewed. We observed significant differences in the sociodemographic and health profile of patients across age groups (P < .05) (Table 2).34

View this table:
Table 2

Profile of patients by age groups: A) Survey patient profile; B) Chart audit patient profile.

There were more women overall, less so in the older age groups. Older individuals were more likely to have chronic conditions and less likely to state that their health was “good” to “excellent” (P < .001). However, older individuals reported significantly fewer days with poor mental health than younger people did (P < .001). There were some differences in the sociodemographic profiles of patients across models (results not shown in tables): Individuals younger than 30 years of age were considerably more likely to be living below the poverty line than older individuals in CHCs only (40%, 34%, and 21% for ages < 30, 30 to 64, and ≥ 65, respectively). Community health centres also had the highest proportion of individuals younger than 30 years without a high school education (19% vs 7% to 10%).

Age disparities

The duration of the index visit (overall average of 17 minutes) did not differ among age groups in any model. Individuals 30 years of age or older reported more yearly visits than younger individuals did in FFS practices only (1.3 visits, 95% confidence interval [CI] 0.3 to 2.6, adjusted for socioeconomic factors). In other models, the difference was smaller than 1 visit yearly.

Health service delivery scales

Older individuals reported better health service delivery across many dimensions in all models (Table 3), with the largest differences observed in patients attending FHNs and HSOs (adjusting for socioeconomic factors). Adjusting for health status (Table 3 legend) attenuates the age effect only slightly. Including the duration of the relationship with the practice in the analysis had no additional effect. The age effect on the overall Primary Care Assessment Tool score for patients aged 65 and older compared with those younger than 30 was larger in FHNs (5.6, 95% CI 3.7 to 7.6) and in HSOs (5.7, 95% CI 3.8 to 7.6) than in CHCs (1.9, 95% CI −0.4 to 4.2) or FFS practices (2.6, 95% CI 0.5 to 4.7).

View this table:
Table 3

Dimensions of health service delivery in the various models of primary care among age groups: Statistically significant results (P < .05) are boldface.

Technical quality-of-care scales

Health promotion

Table 4 shows the odds ratio (OR) of having discussed at least 1 (and each) healthy lifestyle subject assessed at the index visit in each age group across models. Patients 30 to 64 years of age were significantly less likely than younger patients were to have discussed at least 1 lifestyle subject in the CHC model only (OR 0.65, 95% CI 0.45 to 0.94, P < .05). The size of the age effect was larger for CHC than FFS and FHN practices. To represent age effect on actual quality of care delivered, the estimated likelihood of discussing at least 1 subject is provided. Analyses in which the health variables are excluded from the equation show no statistically significant effect of age.

View this table:
Table 4

Health promotion across age groups among primary care models: A) ORs of having discussed lifestyle topics at the index visit; B) Estimated likelihood of discussing at least 1 topic.

Preventive care

The overall preventive score showed a significant age-sex relationship (Table 5). There was no significant difference in the preventive score across age groups in men. However, women 50 years of age and older were less likely to have been up to date on their preventive care in all models. The age effect for those 50 to 64 years of age was significantly larger (P < .05) in HSOs (−22%, 95% CI −15% to −30%) than FHNs (−12%, 95% CI −6% to −18%). To represent age effect on actual quality of care delivered, the estimated prevention score is provided for men and women of different age groups.

View this table:
Table 5

Preventive care* among age groups in the various models of primary care: A) Age effect for overall prevention score and ORs for screening; B) Estimated overall prevention score by age groups and sex.

Colorectal cancer screening (for which there is no upper age limit) and cervical cancer screening were less likely to be performed in older individuals in most models. In contrast, influenza immunization, which, at the time, was indicated for individuals of any age considered at high risk of contracting influenza or experiencing complications from it as well as all individuals 65 years of age or older, was most likely to have been performed in the older age groups in all models.

Chronic disease management

Provider adherence to recommended guidelines for chronic disease management showed an inverted U-shaped relationship with age in FFS, FHN, and HSO practices. The pattern was similar for the individual chronic conditions included in the chronic disease management score (Table 6). Scores were significantly higher (P < .05) in patients 60 to 69 years of age compared with those younger than age 60, then appeared to drop in individuals 70 years of age and older. The age effect size for those 60 to 69 was significantly larger in HSOs (24.4, 95% CI 11.6 to 37.2) compared with CHCs (5.7, 95% CI −9.1 to 20.5). To represent this age effect on actual quality of care delivered, Table 6 provides the estimated chronic disease management score.

View this table:
Table 6

Chronic disease management among age groups across models of primary care: A) Percentage of age effect between age groups; B) Estimated chronic disease management score.

DISCUSSION

This study is the first to assess disparities among age groups across several dimensions of primary care performance in primary care models. We observed disparities across age groups for health service delivery, preventive care, and chronic disease management, but found that the model of care had little meaningful effect on these disparities. In health promotion, we found the focus on younger individuals attending CHCs justifiable and therefore appropriate.

Individual findings

Health service delivery

Relative to their younger counterparts, older individuals reported significantly better health service delivery (P < .05). This relationship persisted after adjusting for health status, indicating that the effect was not related to the lower health status or greater needs of the elderly. These results are consistent with findings from other groups,35–37 one of which attributed its results to differences in expectations, suggesting that the older generations value the services more.36 Although the age effect was larger in both capitation-based models compared with CHCs and FFS practices, the small difference in effect size suggests that any effect these models might have is negligible.

Health promotion

The likelihood of discussing a healthy lifestyle subject was considerably higher in individuals younger than age 30 compared with those who were older in CHCs only. Because individuals attending CHCs in the younger-than-30 age group are more likely to be living under the poverty line and less likely to have completed high school than other groups, and because these sociodemographic factors are associated with higher risk of unhealthy behaviour, including smoking38,39 and drinking,40 this higher likelihood of receiving healthy lifestyle counseling in younger individuals attending CHCs is likely an appropriate response to greater needs. It is noteworthy that, despite a large effect in CHCs, older individuals attending CHCs do not receive less healthy lifestyle counseling than those receiving care in other models.

Preventive care

Preventive care was more likely to be experienced by younger women. The main reason for this is that the maneuvers for which younger women are eligible are more likely to be performed (breast [70%] and cervical cancer screening [78%]), whereas those for which older individuals are eligible are the least likely to have been documented as performed (vision [32%] and hearing [16%] screening). The drop in the prevention score from those aged 17 to 49 years to those aged 50 to 64 years was significantly larger in one capitation-based model (HSO) than in the other (FHN), suggesting that this effect is not driven by the remuneration structure (P < .05).

There was some indication that an age effect was present within maneuvers. At the time of the study, influenza immunization was recommended for all individuals 65 years of age and older, as well as for younger individuals with chronic conditions.41 Adherence to the guidelines for the latter group is significantly lower than that for seniors (P < .05). Because individuals with the types of chronic conditions for which vaccination is indicated are expected to visit the practice at least as often as those aged 65 and older, this finding is unlikely to represent less-frequent opportunity to offer that care for younger individuals. Instead, this either represents a lack of adoption of this maneuver by the medical community in that population or, because a substantial proportion of influenza vaccination is given in immunization clinics, it might point to the fact that sensitization campaigns aimed at the target public are not as successful at reaching these individuals.

Older individuals were less likely to have had colorectal and cervical cancer screening. This might reflect competing medical priorities leaving less time for this preventive maneuver to be performed or the perception that these interventions are less beneficial for those in the older age groups.

Chronic disease management

In our study, adherence to the recommended guidelines for care of diabetes, coronary artery disease, and congestive heart failure was somewhat greater among patients aged 60 to 69 compared with those aged 70 to 79 in all models of care except CHCs, where evidence-based care was equivalent across age groups. Several studies have documented that the elderly are less likely to receive recommended drug management for chronic disease.42–45 Our study evaluated the family physician’s intent by measuring prescriptions or recommendations. The results therefore cannot reflect patient compliance. The commonly postulated reasons why physicians adhere less closely to guidelines in older patients include the lack of evidence for efficacy in that population because seniors were often excluded from clinical trials; patient medical complexity that would result in inappropriate polypharmacy; and lower life expectancy rendering aggressive treatment undesirable.46,47 The fact that we did not observe an age effect in CHCs, where visits are longer and nurse practitioners are more available, suggests that competing demands in older patients and limited time might be responsible for lower adherence to recommended guidelines in older patients. This study also demonstrated that younger individuals are less likely to receive care according to recommended guidelines. Few studies have documented lower use of drug therapy in younger individuals with chronic diseases.42 These results warrant further investigation.

Conclusion

This study evaluated whether disparities across age groups exist within models of primary care, and assessed whether the type of primary care model affects the disparity. We observed considerable age effect across a number of dimensions studied. We found 2 differences in the age effect across models. First, the likelihood of discussing a healthy lifestyle subject was higher in younger individuals attending CHCs, a finding determined to likely be an appropriate response to differing patient need. Second, quality of chronic disease management varied considerably with age in FFS and capitation models but not in CHCs. We conclude that the salaried model might have an organizational structure that is more conducive to providing appropriate care across age groups, and that the thrust toward adopting capitation-based payment is unlikely to have an effect on age disparities.

Acknowledgments

Funding for the original study on which this research is based was provided by the Ontario Ministry of Health and Long-Term Care Primary Health Care Transition Fund. Opinions do not necessarily reflect the views of the Ontario Ministry of Health and Long-Term Care.

Notes

EDITOR’S KEY POINTS

  • Canada has restructured its primary care models of service delivery, shifting from traditional fee-for-service models to salaried community health centres, and to models in which remuneration is largely based on capitation (ie, health service organizations and family health networks). This is the first study to assess disparities among age groups across several dimensions of primary care performance in primary care models.

  • Older individuals reported substantially better health service delivery in all models and this was not explained by their poorer health status or greater needs.

  • Age was a significant determinant (P < .05) of the likelihood of receiving chronic disease management according to recommended guidelines in all models of care except community health centres.

POINTS DE REPÈRE DU RÉDACTEUR

  • Les modèles de prestation des services de soins primaires ont été restructurés au Canada, passant de modèles de rémunération à l’acte à des centres de santé communautaires salariés et à ceux dans lesquels la rémunération repose en grande partie sur la capitation (p ex. organisations de services de santé et réseaux de santé familiale). Cette étude est la première qui cherche à évaluer des disparités éventuelles entre les différents groupes d’âge, et ce, pour divers aspects de la dispensation des soins primaires dans différents modèles de soins primaires.

  • Les sujets plus âgés ont rapporté une prestation de services de santé considérablement meilleure dans tous les modèles, ce qui ne s’expliquait pas par leur moins bonne santé ou leurs besoins plus importants.

  • L’âge était un déterminant significatif (P < ,05) de la probabilité de recevoir un traitement pour maladie chronique qui soit conforme aux directives de pratique, et ce, dans tous les modèles de soins, à l’exception des centres de santé communautaires.

Footnotes

  • This article has been peer reviewed.

  • Cet article a fait l’objet d’une révision par des pairs.

  • Contributors

    Dr Dahrouge conceptualized the current study, consulted on the statistical analysis, and wrote the initial draft of the manuscript. Dr Tuna contributed to methodological and statistical analysis and critically reviewed the manuscript. Dr Hogg conceptualized the original study, provided consultation on the analytical approach, and critically reviewed and edited the manuscript. Drs Russell, Devlin, Tugwell, and Kristjansson contributed to the concept and design of the study and interpretation of the results, and critically reviewed and edited the manuscript. All authors have read and approved the final manuscript.

  • Competing interests

    None declared

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Age equity in different models of primary care practice in Ontario
Simone Dahrouge, William Hogg, Meltem Tuna, Grant Russell, Rose Ann Devlin, Peter Tugwell, Elizabeth Kristjansson
Canadian Family Physician Nov 2011, 57 (11) 1300-1309;
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