Case Study: Primary Access Use Among Urban Older Adults
The Project: Think about this…you’re an older adult who lives in an urban area. There are numerous primary care providers (PCPs) in your neighborhood, so naturally, you visit your doctor for routine care. But do you? What if you perceive your neighborhood to be unsafe, unwalkable, or lacking cohesion in its social capital. This is what Senior Consultant Dr. Miriam Ryvicker was thinking about when she and Dr. Gallo were working together on a larger project—funded by the New York City Department for the Aging—which sought to explore how elements of the neighborhood could influence the well-being of older New Yorkers. Dr. Ryvicker believed that primary care utilization, a critical input to older adults’ well-being, might be explained by more than just access to care. In other words, she reasoned that the number of primary care providers located near to individuals’ residences (we use the term “density” to describe how many PCPs are in the immediate area) would only partly determine how often older individuals visited their PCPs. In fact, Dr. Ryvicker hypothesized that PCP density, personal (what we call socio-demographic), chronic disease, and neighborhood attributes would independently, and in some fashion together, influence PCP utilization.
How We Addressed Key Knowledge Gaps: Our project departed from the assumption that no one category of factors (i.e., environmental, socio-demographic, etc.) could fully explain variation in realized PCP utilization. This assumption was not arbitrarily developed; rather, it arose from consideration of the various scientific literatures that explored why individuals seek primary care. In effect, our contribution was to harmonize, rather than reconcile, the prior research. We achieved three main objectives by analyzing data from a survey of 1260 senior center attendees in New York City (NYC) linked with geographic data on the supply of primary care physicians at the level of the Primary Care Service Area (PCSA). One, we examined whether primary care use among NYC older adults is sensitive to local variations in primary care supply. Two, we examined the differential sorting of individuals into PCSAs with different PCP supply levels by comparing the characteristics of individuals across supply quartiles. Three, we identified combinations of environmental and socio-demographic factors associated with access to primary care both across and within supply quartiles.
What We Did: First, we had to find a way to sort PCP density into reasonable categories, which we could later combine with socio-demographic and neighborhood factors. We accomplished this by creating groupings of participants according to PCP-density quartile, dividing the sample into 4 parts. In this way, the lowest data quartile contained older individuals who had relatively few PCPs in their service areas, with each succeeding quartile’s representing participants with access to more PCPs. Second, we used statistical models to test whether the mere presence of more PCPs in the PCSA predicted more PCP use, independent of participants’ neighborhood and socio-demographic factors. Finally, we applied more advanced analysis to determine whether the interaction of provider density and the other factors explained PCP utilization.
What We Learned: PCP density did not predict whether participants visited a PCP in the last year when we statistically controlled for socio-demographic and neighborhood variables. Rather, such factors as education, insurance type, location of usual source of care, and neighborhood social cohesion explained variation in PCP care seeking. However, within PCP supply quartiles, the results* were more nuanced, with the results’ indicating that the impact of socio-demographic and neighborhood factors (for example, available public transportation) on visiting a PCP differed by how many PCPs were accessible. This all suggests that variation in healthcare supply may be correlated with both individual factors and local variations in neighborhood characteristics, insofar as self-reported perceptions of social cohesion, safety, and the use of public transit may reflect some objective features of a local area’s social capital, built environment, and availability of public transportation.
How Our Findings May Improve Outcomes & Inform Policy: This project advanced our understanding of environmental barriers and facilitators of access to regular primary care that may help to prevent and manage chronic illness and disability among urban elders. Some “takeaway” messages include the following: Different patterns of disadvantage in PCP access exist that may be associated with – but not fully explained by – local primary care supply; elder-friendliness of public transit may facilitate primary care access for elders in areas with low physician supply; racial disparities and inadequate primary care infrastructure hinder access in lower-supply areas; efforts to improve social cohesion and support, may facilitate primary care access for individuals living in low-supply areas; concepts of healthcare access should be multi-faceted and should include neighborhood environmental factors; research on the links between the built environment and healthcare access is crucial for building elder-friendly cities.
The Statistical Findings
* Stratified multivariate models showed that in service areas with the lowest supply levels (Quartile 1), participants who used public transit had a significantly greater likelihood of using primary care (OR=2.40; CI=1.21-4.77). As in the full sample, those with higher social cohesion scores also had a greater likelihood of primary care use (OR=1.14; CI=1.04-1.26). Non-English speakers were more likely to use primary care (OR=2.17; CI=1.30-3.64). In Quartile 2, which had the lowest rate of primary care use overall, non-white participants were significantly less likely to use primary care (OR=0.50; CI=0.29-0.89). Location of the usual source of care was also a strong predictor of primary care use; participants who used a community clinic (OR=0.47; 0.27-0.82), an emergency department (OR=0.18; CI=0.06-0.52), and multiple locations (OR=0.21; CI=0.09-0.47) were less likely than those who used a private doctor’s office to have had a PCP/clinic visit within the past year. In Quartile 3, which had the highest proportion of non-English speakers, participants who did not speak English had a significantly greater likelihood of using primary care (OR=2.72; CI=1.15-6.46). No other factors were significant within this quartile. In Quartile 4, participants with less frequent social contact were less likely to use primary care (OR=0.60; CI=0.41-0.89), a factor which was not significant in any other quartile or in the overall sample.