The most meaningful difference in population characteristics of the PCSAs of the five population-per-physician groups was their size, with PCSAs in the groups with fewer people per physician (greater physician availability) being generally larger (). There were also group-to-group differences in the proportions of non-Hispanic whites but the differences did not vary in a consistent direction with physician densities. PCSAs of the five groups did not differ in their mean population poverty rates or in the household incomes and health status of their respondents.
PCSA Population and Respondent Characteristics (Weighted) within Five Groups of PCSAs Stratified by Population-to-Physician Ratios
There were very few statistically significant access differences in the direction anticipated among the five population-per-physician groups. The only differences related to travel to care () and in the use rate of one preventive health service (). Specifically, incrementally more individuals reported traveling more than 30 minutes for outpatient care in the PCSA groups with increasingly more people per physician, ranging from 18.5 percent of those living in PCSAs with 1,499 or fewer people per physician up to 39.1 percent of those in PCSAs with more than 3,500 people per physician (). Subjects living in PCSAs with 3,500 or more people per physician were also more likely to report difficulty in traveling to care—a subjective measure of the burden of travel—than those living in PCSAs with fewer than 1,500 people per physician (15.5 versus 10.9 percent, respectively). These differences in travel time and perceived difficulty of travel remained statistically significant after adjusting for characteristics of respondents and PCSAs.
Table 2 Subjects Who Experienced Impaired Access to Outpatient Care, Stratified by the Population-per-Physician Ratios of the PCSAs Where People Live: Unadjusted Percentages and Adjusted Odds Ratios† Relative to the Group with Smallest Population per (more ...)
Table 3 Subjects Who Didn't Get Recommended Preventive Health Services, Stratified by the Population-per-Physician Ratios of the PCSAs Where They Live: Unadjusted Percentages and Adjusted Odds Ratios† Relative to the Group with Smallest Population per (more ...)
Subjects living in the five PCSA population-per-physician groups did not differ on any of the indicators of outpatient physician service use over the past year, including the proportions that had not seen a physician, had not had a routine check-up, or had not gotten or delayed care they thought they needed (). Other than travel difficulties the respondents of the five PCSA groups did not differ in their likelihood of reporting any of a variety of perceived barriers to care, including cost barriers, not having a usual source of care, or finding care generally difficult to obtain. Respondents of the five PCSA groups also reported comparable satisfaction with the care they received.
Reported use rates for only one of the seven preventive health services we assessed was lower for a PCSA group where physicians were scarcer (). Influenza immunizations were more often missed by subjects age 65 and older who lived in the PCSA group with most people per physician than in the group with fewest people per physician (42.1 versus 27.7 percent, p=.019). We found no group differences in rates of missed sigmoidoscopy/colonoscopy, mammography, diet and nutrition counseling, and exercise and activity counseling. Two statistically significant associations were found in the direction opposite of that anticipated: compared with those living in PCSAs where physicians were most plentiful, women in one mid-range physician density group were less likely to have missed a Pap smear for cervical cancer detection and tobacco users in another mid-range group were less likely to not have been counseled about tobacco use.
We examined four modifications of the full models to test several possible reasons why so few associations were found between PCSA population-per-primary care physician ratios and indicators of access to office physician care. We first added a dichotomous indicator of the presence of FQHCs within each subject's PCSA to the full logistic models of each access indicator to assess if the presence of FQHCs somehow blunted the measured associations between physician availability and access. (Note: FQHCs were not accounted for in the original models because of concerns of model endogeneity, in that FQHCs are intended to attract new physicians into shortage areas for the specific purpose of improving access.) The model findings did not change.
Secondly, we added a variable to the full logistic models indicating the number of square miles within each PCSA to control for the effects PCSA size might have on travel times and other access indicators. Again, the model findings were not different.
Thirdly, we wondered if state-to-state variations in either population-per-physician ratios or access indicators added background “noise” to the analyses obscuring associations. We added state indicator variables to the full models, and again the findings of the original models of and held, with two exceptions: (1) people living in PCSAs with more than 3,500 people per physician were now found to more often report that costs of care were a problem for them than people in PCSAs with fewest people per physician (odds ratio 1.34, p=.04); and (2) the paradoxical finding of the original models of a higher Pap smear rate for women in PCSAs of 2,500–3,499 people per physician now dropped below the level of statistical significance (odds ratio 0.21, p=.082).
Lastly, it is possible that model findings are at least partially driven by spatial correlations in that counties are correlated in unobserved ways with nearby counties, an expression of Tobler's First Law of Geography (Sui 2004
)—“everything is related to everything else, but near things are more related than distant things.” We looked, therefore, for evidence of unobserved factors influencing the measured associations between physician densities and access. We first calculated standardized Pearson residuals (Hosmer and Lemeshow 1989
) from the logistic models for a sample of six access measures—the three indicators with positive findings (traveling more than 30 minutes for care, finding travel to care generally difficult, and having not been immunized against influenza) and three measures with null findings that are among the key indicators of each of the three principal dimensions of access, specifically use of services, barriers to care and satisfaction (having no physician visit in the past 12 months, finding it generally difficult to get care, and overall satisfaction with care). We then computed the county average of these residuals and analyzed them subjectively by mapping and visually examining them for clustering and objectively by computing Moran's I
(Waller and Gotway 2004
). Only one of the six measures—finding it generally difficult to get care—exhibited evidence of positive spatial correlation. This means that for this variable the estimated standard error of the initial measured association is likely biased downward making the p
-value we calculated smaller than it should be, but this merely strengthens our conclusion that people's assessment of their overall difficulty in obtaining care is unrelated to local primary care physician availability.
Subgroup Analyses: Elderly and Medicaid/Uninsured Populations
Among subjects age 65 and older arrayed into three population-per-physician groups, there was only one significant association in the direction anticipated between group membership and an access measure (, top). Elderly in PCSAs with 2,800 or more people per physician were more likely to report traveling more than 30 minutes for care than those in PCSAs with fewest people per physician (33.3 versus 24.5 percent). One new association was found in the unanticipated direction: elderly women in the middle PCSA group with 1,500–2,499 people per physician had less often missed their mammograms in the past year than those in PCSAs with fewest people per physician (40.3 versus 50.2 percent).
Table 4 Sub-Group Analyses: Subjects Age 65 Years and Older and Subjects Age 18–64 Insured under Medicaid or Uninsured Who Experienced Impaired Access to Outpatient Care, Stratified by the Population-per-Physician Ratios of the PCSAs Where They Live: (more ...)
More significant associations were found for subjects insured under Medicaid or uninsured (, bottom). Within this population, those who lived in PCSAs with more people per physician more often reported (1) traveling more than 30 minutes for outpatient care, (2) difficulty traveling to care, (3) difficulty contacting a medical person by phone, (4) dissatisfaction overall with the care they received, and (5) dissatisfaction with how welcome and comfortable they felt where they received care. There were no differences in the rates at which preventive health services were received across the three population-per-physician PCSA groups for this population.