Arthritis Care & Research Vol. 66, No. 11, November 2014, pp 1634 –1643 DOI 10.1002/acr.22333 © 2014, American College of Rheumatology
ORIGINAL ARTICLE
Relationships Between Driving Distance, Rheumatoid Arthritis Diagnosis, and Disease-Modifying Antirheumatic Drug Receipt JENNIFER M. POLINSKI,1 M. ALAN BROOKHART,2 JOHN Z. AYANIAN,1 JEFFREY N. KATZ,1 SEOYOUNG C. KIM,1 JOYCE LII,1 CHRIS TONNER,3 EDWARD YELIN,3 AND DANIEL H. SOLOMON1
Objective. Disease-modifying antirheumatic drugs (DMARDs) are recommended for all patients with rheumatoid arthritis (RA). Some estimate that approximately one-half of patients with RA do not receive DMARDs. We hypothesized that patients with RA living farther from rheumatologists would be less likely to receive RA diagnoses and to receive DMARDs. Methods. US-based Medicare patients ages >65 years were study eligible. We calculated driving distance from patients’ homes to the nearest rheumatologist. Using multivariable logistic regression, we assessed relationships between driving distance and RA diagnosis and between driving distance and DMARD receipt. In one set of analyses, distance was divided into quartiles: 0 –2, 2.1–5, 5.1–15.9, and >16 miles. In a second set of analyses, we used predefined categories: 0 –15, 15.1–30, 30.1– 60, and >60 miles. Results. Among 59,426 Medicare beneficiaries, 918 had diagnosed RA. Compared to the first quartile, increased distance was associated with decreased odds of RA diagnosis (odds ratio [OR] 0.96 [95% confidence interval (95% CI) 0.80 –1.16] in second quartile, OR 0.88 [95% CI 0.72–1.07] in third quartile, and OR 0.72 [95% CI 0.56 – 0.93] in fourth quartile; P < 0.01 for trend). Similar results were observed using predefined categories. Among those with RA, increased distance was associated with increased odds of DMARD receipt across quartiles (OR 1.15 [95% CI 1.06 –1.25] in second quartile, OR 1.41 [95% CI 1.29 –1.54] in third quartile, and OR 1.32 [95% CI 1.18 –1.46] in fourth quartile; P ⴝ 0.001 for trend). There was no relationship between predefined categories and DMARD receipt (P ⴝ 0.45 for trend). Conclusion. Increased driving distance to rheumatologists was associated with decreased odds of RA diagnosis. Among those with diagnosed RA, the odds of DMARD receipt rose as distance increased from 16 (n ⴝ 6,632)
77 ⫾ 7 3,505 (45) 3,179 (41) 1,130 (14)
76 ⫾ 7 3,444 (52) 2,432 (37) 736 (11)
75 ⫾ 7 3,563 (54) 2,361 (36) 708 (11)
5,965 (76) 912 (12) 937 (12) 5,926 (76) 6⫾5 10 ⫾ 5
5,644 (85) 520 (8) 448 (7) 4,962 (75) 6⫾5 10 ⫾ 5
5,783 (87) 555 (8) 294 (4) 4,803 (72) 5⫾4 10 ⫾ 6
0.2 ⫾ 0.6
0.2 ⫾ 0.6
0.3 ⫾ 0.7
2,524 (32) 2,364 (30) 2,252 (29) 104 (1) 2⫾2 1,473 (19) 2,421 (31) 482 (6) 115 (1) 466 (6)
2,447 (37) 1,974 (30) 2,217 (34) 109 (2) 2⫾2 1,184 (18) 1,809 (27) 346 (5) 95 (1) 381 (6)
2,624 (40) 2,056 (31) 2,507 (38) 117 (2) 2⫾2 1,033 (16) 1,766 (27) 352 (5) 78 (1) 325 (5)
3,043 (39) 1,750 (22) 1,611 (21) 1,410 (18)
2,958 (45) 1,775 (27) 1,228 (19) 651 (10)
1,092 (16) 1,715 (26) 2,421 (37) 1,404 (21)
2,838 (36) 1,646 (21) 2,050 (26) 1,280 (16)
1,988 (30) 1,686 (26) 2,061 (31) 877 (13)
4,094 (62) 1,795 (27) 655 (10) 88 (1)
6,435 (82) 832 (11) 426 (5) 121 (2) 52,114 ⫾ 27,479
5,955 (90) 411 (6) 187 (3) 59 (1) 52,683 ⫾ 22,846
5,551 (84) 701 (11) 310 (5) 70 (1) 36,465 ⫾ 12,721
3,696 (47) 1,755 (22) 1,291 (17) 1,072 (14)
3,504 (53) 1,684 (25) 994 (15) 430 (7)
1,700 (26) 2,225 (34) 2,063 (31) 644 (10)
3,819 (49) 2,187 (28) 1,654 (21) 154 (2)
3,547 (54) 1,859 (28) 1,110 (17) 96 (1)
5,434 (82) 981 (15) 203 (3) 14 (0)
5,827 (75) 751 (10) 636 (8) 600 (8) 7,666 (98) 1.29 (0.97–1.73)
5,646 (85) 497 (8) 259 (4) 210 (3) 5,260 (80) 1.09 (0.77–1.49)
5,668 (85) 644 (10) 217 (3) 103 (2) 2,786 (42) 0.65 (0.42–1.01)
* Values are the number (percentage) unless indicated otherwise. NSAID ⫽ nonsteroidal antiinflammatory drug; RTI ⫽ Research Triangle Institute; SES ⫽ socioeconomic status; HSA ⫽ hospital service area (collection of zip codes whose residents receive most of their hospitalizations from the hospitals in that area); IQR ⫽ interquartile range.
184 (1.2) 160 (1.1) 158 (1.1) 1.08 (0.88–1.34) 0.94 (0.76–1.17) 0.93 (0.75–1.16) 1.03 (0.83–1.28) 0.89 (0.71–1.13) 0.77 (0.58–1.03)
141 (1.0) 136 (0.9) 136 (0.9) 0.98 (0.78–1.24) 0.94 (0.75–1.20) 0.94 (0.75–1.20) 0.94 (0.73–1.19) 0.92 (0.71–1.19) 0.88 (0.64–1.21)
170 (1.1) Ref. Ref.
144 (1.0) Ref. Ref.
>17.6 (n ⴝ 14,853)
246 (1.7) 221 (1.5) 200 (1.4) 0.98 (0.82–1.17) 0.88 (0.73–1.05) 0.79 (0.66–0.96) 0.96 (0.80–1.16) 0.88 (0.72–1.07) 0.72 (0.56–0.93)
5.71–17.5 (n ⴝ 14,858)
251 (1.7) Ref. Ref.
2.61–5.7 (n ⴝ 14,857)
* Values are the odds ratio (95% confidence interval) unless indicated otherwise.
Cohort 1 definition (2 diagnoses) No. (%) Unadjusted Adjusted Cohort 2 definition (3 diagnoses) No. (%) Unadjusted Adjusted Cohort 3 definition (2 diagnoses ⫹ steroid prescription) No. (%) Unadjusted Adjusted
0–2.6 (n ⴝ 14,858)
Quartiles of driving distance, miles
0.52
⬍ 0.05
⬍ 0.01
P for trend
411 (1.0) Ref. Ref.
502 (1.1) Ref. Ref.
701 (1.6) Ref. Ref.
0–15 (n ⴝ 43,000)
30.1–60 (n ⴝ 6,171)
>60 (n ⴝ 2,889)
71 (1.0) 46 (0.8) 29 (1.0) 1.01 (0.78–1.30) 0.78 (0.57–1.06) 1.05 (0.72–1.53) 0.92 (0.69–1.23) 0.71 (0.48–1.05) 0.98 (0.62–1.56)
84 (1.1) 55 (0.9) 31 (1.1) 0.98 (0.77–1.23) 0.77 (0.58–1.01) 0.92 (0.64–1.32) 0.83 (0.64–1.10) 0.61 (0.43–0.87) 0.74 (0.48–1.15)
106 (1.4) 73 (1.2) 38 (1.3) 0.88 (0.72–1.08) 0.72 (0.57–0.92) 0.80 (0.58–1.12) 0.79 (0.63–1.00) 0.63 (0.47–0.86) 0.72 (0.49–1.06)
15.1–30 (n ⴝ 7,366)
Predefined categories of driving distance, miles
0.58
⬍ 0.05
0.02
P for trend
Table 2. Number and frequency, unadjusted odds, and adjusted odds of rheumatoid arthritis diagnosis in the 6% patient sample at 365 days, by 2 approaches to define driving distance categories*
Driving Distance, RA Diagnosis, and DMARD Receipt 1639
2,979 (45) 1.85 (1.72–2.00) 1.41 (1.29–1.54)
463 (7) 1.31 (1.13–1.53) 1.05 (0.89–1.24)
546 (8) 1.55 (1.34–1.80) 1.17 (1.00–1.37)
2,291 (35) 1.84 (1.69–1.99) 1.41 (1.29–1.55)
465 (6) 1.10 (0.95–1.28) 1.02 (0.87–1.19)
512 (7) 1.21 (1.05–1.40) 1.09 (0.93–1.28)
2,139 (27) 1.31 (1.21–1.42) 1.17 (1.07–1.28)
5.1–15.9 (n ⴝ 6,612)
2,826 (36) 1.28 (1.19–1.38) 1.15 (1.06–1.25)
2.1–5.0 (n ⴝ 7,814)
2,408 (36) 1.98 (1.82–2.14) 1.33 (1.19–1.49)
583 (9) 1.66 (1.44–1.92) 1.23 (1.02–1.49)
429 (6) 1.21 (1.04–1.40) 1.00 (0.81–1.22)
3,159 (48) 2.06 (1.91–2.22) 1.32 (1.18–1.46)
>16 (n ⴝ 6,632)
0.003
0.08
0.80
0.001
P for trend
5,584 (28) Ref. Ref.
1,337 (7) Ref. Ref.
1,208 (6) Ref. Ref.
7,395 (38) Ref. Ref.
0–15 (n ⴝ 19,698)
1,082 (35) 1.37 (1.26–1.48) 1.07 (0.97–1.18)
261 (8) 1.27 (1.11–1.46) 1.11 (0.95–1.31)
192 (6) 1.02 (0.87–1.19) 0.96 (0.80–1.15)
1,419 (46) 1.42 (1.31–1.53) 1.09 (0.99–1.19)
15.1–30 (n ⴝ 3,083)
960 (37) 1.50 (1.38–1.63) 1.08 (0.95–1.22)
237 (9) 1.39 (1.20–1.61) 1.16 (0.95–1.42)
172 (7) 1.09 (0.93–1.29) 1.08 (0.86–1.35)
1,249 (48) 1.56 (1.44–1.70) 1.03 (0.91–1.16)
30.1–60 (n ⴝ 2,579)
451 (37) 1.46 (1.30–1.65) 1.04 (0.89–1.22)
109 (9) 1.34 (1.09–1.64) 1.07 (0.83–1.39)
85 (7) 1.14 (0.91–1.43) 1.07 (0.80–1.43)
598 (49) 1.57 (1.40–1.77) 1.06 (0.91–1.23)
>60 (n ⴝ 1,230)
Predefined categories of driving distance, miles
* Values are the odds ratio (95% confidence interval) unless indicated otherwise. DMARD ⫽ disease-modifying antirheumatic drug.
Receipt of any DMARD No. (%) 1,697 (31) Unadjusted Ref. Adjusted Ref. Receipt of a biologic DMARD No. (%) 300 (5) Unadjusted Ref. Adjusted Ref. Receipt of combination DMARDs No. (%) 303 (5) Unadjusted Ref. Adjusted Ref. Majority of time on DMARDs No. (%) 1,239 (22) Unadjusted Ref. Adjusted Ref.
0–2.0 (n ⴝ 5,532)
Quartiles of driving distance, miles
Table 3. Number and frequency, unadjusted odds, and adjusted odds of DMARD use at 365 days in cohort 1, by 2 approaches to define driving distance*
0.45
0.04
0.60
0.45
P for trend
1640 Polinski et al
Driving Distance, RA Diagnosis, and DMARD Receipt to receive a DMARD as driving distance increased (n ⫽ 1,697 [31%] in first quartile, n ⫽ 2,826 [36%] in second quartile, n ⫽ 2,979 [45%] in third quartile, and n ⫽ 3,159 [48%] in fourth quartile) (Table 3). Patients with RA were also more likely to spend the majority of time on DMARDs as driving distance increased (n ⫽ 1,239 [22%] in first quartile versus n ⫽ 2,408 [36%] in fourth quartile). The same patterns were observed when predefined categories of driving distance were used. In multivariable logistic analyses, increased driving distance, modeled in quartiles, was significantly associated with an increased likelihood of receiving any DMARD. As compared to patients with driving distances in the first quartile, second quartile patients had 15% greater odds of receiving any DMARD (95% CI 1.06 –1.25), third quartile patients had 41% greater odds (95% CI 1.29 –1.54), and fourth quartile patients had 32% greater odds (95% CI 1.18 –1.46, P ⫽ 0.001 for trend). Similarly, compared to first quartile patients, increased distance to a rheumatologist was associated with an increased likelihood of spending the majority of time on DMARDs (odds ratio [OR] 1.17 [95% CI 1.07–1.28] in second quartile, OR 1.41 [95% CI 1.29 –1.55] in third quartile, and OR 1.33 [95% CI 1.19 – 1.49] in fourth quartile; P ⫽ 0.003 for trend). There was a trend toward increased odds of combination DMARD receipt with increased driving distance. No relationship between increased distance and receipt of a biologic DMARD was observed. In contrast, when driving distance was modeled using predefined categories, no relationships between increased driving distance and any of the DMARD receipt outcomes were observed. For example, as compared to patients who lived 0 –15 miles from the nearest rheumatologist, patients in higher categories had no greater or lesser odds of DMARD receipt (OR 1.09 [95% CI 0.99 –1.19] for 15.1–30 miles, OR 1.03 [95% CI 0.91–1.16] for 30.1– 60 miles, and OR 1.06 [95% CI 0.91–1.23] for ⬎60 miles; P ⫽ 0.45 for trend). Analogous results to those observed in cohort 1 were found in cohorts 2 and 3 (data not shown). In each of the multivariable models, multiple covariates were associated with DMARD receipt. Positive associations included rural versus urban residence (OR 1.24 [95% CI 1.12–1.36]) and higher scores (indicating higher SES) on the RTI SES index (OR 1.12 [95% CI 1.09 –1.16] per 10point increase). Characteristics negatively associated with DMARD receipt included diagnoses of diabetes mellitus (OR 0.75 [95% CI 0.70 – 0.81]), chronic lung disease (OR 0.73 [95% CI 0.64 – 0.83]), cancer (OR 0.89 [95% CI 0.82– 0.97]), and/or myocardial infarction/stroke (OR 0.62 [95% CI 0.58 – 0.67]); all results shown are from the predefined driving distance model.
DISCUSSION Among a sample of patients ages ⬎65 years with comprehensive medical and prescription drug coverage through the US government–sponsored Medicare program, we examined relationships between driving distance and RA diagnosis and between driving distance and DMARD receipt. We observed that increased driving distance to the
1641 nearest rheumatologist was associated with decreased odds of RA diagnosis, a result that was consistent across driving distance definitions. Among patients with an RA diagnosis, the relationship between driving distance and DMARD receipt was sensitive to the exposure definition: while increased driving distance quartiles were associated with a 12–32% increased odds of receiving any DMARD, no association was found between predefined driving distance categories and DMARD receipt. Our observations suggest that driving distance acts as a proxy for at least some of the burden of obtaining rheumatologic care, but has less importance in determining DMARD receipt. The association we observed between increased driving distance and decreased odds of RA diagnosis is important for both health care policymakers and the rheumatology community as they strategize ways to maximize the impact of a limited rheumatologist workforce. These results are in agreement with other studies that have found increased driving distance to be associated with reduced access to specialty health care services. Chan et al found that increasing rurality was associated with an 8% increase in the share of overall visits to generalist providers and a corresponding 10% decrease in the share of visits to medical specialists (13). Currently, the Health Professional Shortage Area (HPSA) Physician Bonus Program offers a 10% bonus to physicians, including rheumatologists, who practice in primary care HPSA and provide services to Medicare beneficiaries (28). Whether the program has expanded access to rheumatology care for elderly beneficiaries is beyond the scope of this study, but merits consideration. In evaluating the relationship between driving distance and DMARD receipt among those with a diagnosis of RA, our results depended on the granularity of the category definitions. When driving distance was defined in quartiles, with finer discrimination among shorter distances (75% of patients lived within 16 miles), patients who lived farther from the nearest rheumatologist were more likely to receive DMARDs. This paradox is known as distance bias, where unmeasured factors such as disease severity, patient resources, and motivation may explain better treatment among patients who live greater distances from care. One potential interpretation of our quartile findings is that patients who live a greater distance from a rheumatologist and are still diagnosed with RA are the patients who possess greater resources, severity of disease, and/or motivation for care that drive them to seek out the best treatment for their condition, i.e., DMARDs. Such interpretations have been described frequently in the oncologic and other literature (14 –17). In a multicenter study of 1,479 patients with multiple myeloma, patients who lived 0 –9 miles from the center had 1.34 times greater odds of death than patients who lived ⬎150 miles away, 10 – 49 miles away (OR 1.25), and 50 –149 miles away (OR 1.19) (16). In another study among 716 patients with lymphoma, the survival of patients who traveled long distances was better than that of patients who lived nearest to the hospital, even though patients who traveled long distances were more likely to have aggressive and advanced disease (17). Ballard et al observed that those who traveled ⬍10 miles for treatment at a referral center hospital had 20% in-
1642 creased odds of death as compared to those who traveled ⬎10 miles (14). Despite evidence of distance bias, other studies have found conflicting results. In a recent study that better controlled for the severity of patients’ disease prior to surgical intervention, no distance bias was observed across quintiles of driving distance, although these quintiles encompassed substantial distances (mean 15.9 miles for quintile 1, 56.1 miles for quintile 2, 117.6 miles for quintile 3, 232.7 miles for quintile 4, and 702.0 miles for quintile 5) (8). Strauss et al observed that increased driving distance was associated with decreased glycemic control among patients with diabetes mellitus and postulated that their results might be due to providers’ reluctance to prescribe more aggressive medication regimens that would increase patients’ risk of hypoglycemia; the mean ⫾ SD for driving distance traveled was 12.2 ⫾ 16.7 km (12). With these examples in mind, we sought corroborating evidence for our initial results by using an alternative definition of the exposure, one that focused on differences across larger distances but did not make fine distinctions for distances less than 15 miles, by using predefined categories of driving distance meant to approximate travel time. In these analyses, we observed no relationship between driving distance and DMARD receipt. Once a patient received an RA diagnosis, treatment in accordance with recommended guidelines was as likely across patients. Taken together, our 2 approaches to defining driving distance and our corresponding results describe only some of the disparity in DMARD receipt, and then only across very short (⬍16 miles) as opposed to longer distances (⬎15 miles). This suggests that driving distance plays a minimal role in DMARD receipt, where ⬎70% of our population reside, and that other factors such as socioeconomic barriers, clinical comorbidities and disease severity, and health-seeking behaviors may better explain previously observed disparities in DMARD use (7–10). With the increasing availability of geographic information systems software and comprehensive data sources that include street addresses, researchers have expanded opportunities to evaluate relationships between driving distance, access to care, and health outcomes. Our study points to the sensitivity of these relationships to the definition of driving distance and suggests that multiple definitions should be employed to test the robustness of observed results. Our results also raise questions as to whether driving distance is a good measure of access to medical care and to medical treatments and procedures. Prescription drug receipt may sometimes be dependent on diagnosis, a likely explanation for the significant trends we observed when the RA diagnosis definition included only diagnosis codes (cohorts 1 and 2) as opposed to the nonsignificant trends we observed when the RA diagnosis definition required a prescription for ⬎1 oral glucocorticoid (cohort 3). In our study, diagnosis was more strongly related to distance; this may hold implications for research examining the utilization of medical interventions or prescription drug treatments based on geography. The sociodemographic characteristics of patients in specific geographies must also be considered. In the US, persons living in urban areas often have lower SES than those
Polinski et al living in suburban or even rural areas, whereas in other countries, persons living in urban areas have higher SES as compared to those living in rural areas. This information provides further context for our US-based results. A strength of our study is that we were able to adjust for multiple individual- and neighborhood-level characteristics that are associated with SES and potential disparities in personal resources that might explain the relationship between driving distance and DMARD receipt (8,14,25,29). Of note, ⬎70% of patients lived within 15 miles of a rheumatologist; patients who live farther away from rheumatology care may be underrepresented in our data due to the potentially reduced likelihood of having prescription drug coverage. Our data source includes patients enrolled in the US government–sponsored Medicare program who have comprehensive health coverage. Our population is age ⬎65 years, and so our results may not generalize to younger patients. Although DMARD treatment is recommended for all patients with RA (2), we acknowledge that physicians’ and patients’ decision making regarding treatment options may be substantially different depending on patients’ age, treatment goals, risk versus benefit considerations, and overall lived experience. Finally, elderly patients’ access to RA diagnosis and treatment may be different from that for younger patients. While comprehensive, our data source for patients does not have information on RA disease severity or on patients’ motivation/health-seeking behavior, both thought to be associated with distance bias. Because information on these factors is unavailable, it is not possible to quantify their impact on the results we observed. Data sources with this information may further elucidate the impact of these factors. Another limitation is the low PPV of our primary definition of RA. We used 2 alternative definitions to explore this and found analogous results. There is strong consensus regarding the utility and importance of DMARDs in treating RA (2). Disparities in DMARD receipt have been well documented and continue to merit concern (3–5). In this study, we explored the relationships between driving distance and RA diagnosis and between driving distance and DMARD receipt. Increased driving distance to a rheumatologist was associated with decreased odds of receiving an RA diagnosis. Once patients did receive the diagnosis, the relationship between driving distance and DMARD receipt depended on the distance traveled: within approximately 16 miles, patients with RA had increased relative odds of DMARD receipt as driving distance increased. Beyond 16 miles, we did not find such a distance bias, observing an essentially flat relationship between driving distance and DMARD receipt. These data points together suggest that urban residents who live closer to a rheumatologist likely have other financial or socioeconomic barriers to DMARD use. While driving distance to the nearest rheumatologist, as a proxy for access, appears to play an important role in receiving an RA diagnosis, it does not appear to explain much of the variability in DMARD receipt. Interventions to shorten the distance to rheumatologic care will likely increase the incidence of RA diagnosis, but are unlikely on their own to lead to improved rates of DMARD use.
Driving Distance, RA Diagnosis, and DMARD Receipt
1643
AUTHOR CONTRIBUTIONS All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. Dr. Polinski had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study conception and design. Polinski, Brookhart, Ayanian, Katz, Kim, Yelin, Solomon. Acquisition of data. Polinski, Lii. Analysis and interpretation of data. Polinski, Brookhart, Ayanian, Katz, Kim, Lii, Tonner, Yelin, Solomon.
15.
16.
17.
REFERENCES 1. Wailoo AJ, Bansback N, Brennan A, Michaud K, Nixon RM, Wolfe F. Biologic drugs for rheumatoid arthritis in the Medicare program: a cost-effectiveness analysis. Arthritis Rheum 2008;58:939 – 46. 2. Olsen NJ, Stein CM. New drugs for rheumatoid arthritis. N Engl J Med 2004;350:2167–79. 3. Ward MM. Trends in the use of disease modifying antirheumatic medications in rheumatoid arthritis, 1980-1995: results from the National Ambulatory Medical Care Surveys. J Rheumatol 1999;26:546 –50. 4. Schmajuk G, Schneeweiss S, Katz JN, Weinblatt ME, Setoguchi S, Avorn J, et al. Treatment of older adult patients diagnosed with rheumatoid arthritis: improved but not optimal. Arthritis Rheum 2007;57:928 –34. 5. Lacaille D, Anis AH, Guh DP, Esdaile JM. Gaps in care for rheumatoid arthritis: a population study. Arthritis Rheum 2005;53:241– 8. 6. Shipton D, Glaizer RH, Guan J, Badley EM. Effects of use of specialty services on disease-modifying antirheumatic drug use in the treatment of rheumatoid arthritis in an insured elderly population. Med Care 2004;42:907–13. 7. Adler NE. Examining the health disparities research plan of the National Institutes of Health: unfinished business. Washington, DC: National Academies Press; 2006. 8. Etzioni DA, Fowl RJ, Wasif N, Donohue JH, Cima RR. Distance bias and surgical outcomes. Med Care 2013;51:238 – 44. 9. Krieger N, Moss N. Accounting for the public’s health: an introduction to selected papers from a U.S. conference on “measuring social inequalities in health.” Int J Health Serv 1996;26:383–90. 10. Schneider EC, Zaslavsky AM, Epstein AM. Racial disparities in quality of care for enrollees in Medicare managed care. JAMA 2002;287:1288 –94. 11. Deal CL, Hooker R, Harrington T, Birnbaum N, Hogan P, Bouchery E, et al. The United States rheumatology workforce: supply and demand, 2005–2025. Arthritis Rheum 2007;56: 722–9. 12. Strauss K, MacLean C, Troy A, Littenberg B. Driving distance as a barrier to glycemic control in diabetes. J Gen Intern Med 2006;21:378 – 80. 13. Chan L, Hart LG, Goodman DC. Geographic access to health care for rural Medicare beneficiaries. J Rural Health 2006;22: 140 – 6. 14. Ballard DJ, Bryant SC, O’Brien PC, Smith DW, Pine MB,
18.
19. 20. 21. 22. 23.
24. 25. 26. 27.
28.
29.
Cortese DA. Referral selection bias in the Medicare hospital mortality prediction model: are centers of referral for Medicare beneficiaries necessarily centers of excellence? Health Serv Res 1994;28:771– 84. Lamont EB, Hayreh D, Pickett KE, Dignam JJ, List MA, Stenson KM, et al. Is patient travel distance associated with survival on phase II clinical trials in oncology? J Natl Cancer Inst 2003;95:1370 –5. Lenhard RE, Enterline JP, Crowley J, Ho GY. The effects of distance from primary treatment centers on survival among patients with multiple myeloma. J Natl Cancer Inst 1987;5: 1640 –5. Paltiel O, Ronen I, Polliack A, Epstein L. Two-way referral bias: evidence from a clinical audit of lymphoma in a teaching hospital. J Clin Epidemiol 1998;51:93– 8. Gillis JZ, Yazdany J, Trupin L, Julian L, Panopalis P, Criswell LA, et al. Medicaid and access to care among persons with systemic lupus erythematosus. Arthritis Rheum 2007;57: 601–7. Kim SY, Servi A, Polinski JM, Mogun H, Weinblatt ME, Katz JN, et al. Validation of rheumatoid arthritis diagnoses in health care utilization data. Arthritis Res Ther 2011;13:R32. Gabriel SE. The sensitivity and specificity of computerized databases for the diagnosis of rheumatoid arthritis. Arthritis Rheum 1994;37:821–3. Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol 1992;45:613–9. US Census Bureau. American Community Survey. URL: http://www.census.gov/acs/www/. Bonito AJ, Bann C, Eicheldinger C, Carpenter L. Creation of new race-ethnicity codes and socioeconomic status (SES) indicators for Medicare beneficiaries. 2008. URL: http://www.ahrq.gov/research/findings/final-reports/ medicareindicators/index.html. The Dartmouth Atlas of Health Care. Zip code crosswalk files. 2006. URL: http://www.dartmouthatlas.org/tools/downloads. aspx#crosswalks. The Dartmouth Atlas of Health Care. Selected hospital and physician capacity measures. 2006. URL: http://www. dartmouthatlas.org/tools/downloads.aspx#resources. The Dartmouth Atlas of Health Care. Glossary. 2013. URL: http://www.dartmouthatlas.org/tools/glossary.aspx. Krieger N, Chen JT, Waterman PD, Soobader MJ, Subramanian SV, Carson R. Geocoding and monitoring of US socioeconomic inequalities in mortality and cancer incidence: does the choice of an area-based measure and geographic level matter? The Public Health Disparities Geocoding Project. Am J Epidemiol 2002;156:471– 82. Medicare Learning Network. Health professional shortage area (HPSA) physician bonus, HPSA surgical incentive payment, and primary care incentive payment programs. 2012. URL: http://www.cms.gov/Outreach-and-Education/ Medicare-Learning-Network-MLN/MLNProducts/downloads/ HPSAfctsht.pdf. Krieger N, Chen JT, Waterman PD, Rehkopf DH, Subramanian SV. Painting a truer picture of US socioeconomic and racial/ ethnic health inequalities: the Public Health Disparities Geocoding Project. Am J Public Health 2005;95:312–23.
ORIGINAL ARTICLE
Relationships Between Driving Distance, Rheumatoid Arthritis Diagnosis, and Disease-Modifying Antirheumatic Drug Receipt JENNIFER M. POLINSKI,1 M. ALAN BROOKHART,2 JOHN Z. AYANIAN,1 JEFFREY N. KATZ,1 SEOYOUNG C. KIM,1 JOYCE LII,1 CHRIS TONNER,3 EDWARD YELIN,3 AND DANIEL H. SOLOMON1
Objective. Disease-modifying antirheumatic drugs (DMARDs) are recommended for all patients with rheumatoid arthritis (RA). Some estimate that approximately one-half of patients with RA do not receive DMARDs. We hypothesized that patients with RA living farther from rheumatologists would be less likely to receive RA diagnoses and to receive DMARDs. Methods. US-based Medicare patients ages >65 years were study eligible. We calculated driving distance from patients’ homes to the nearest rheumatologist. Using multivariable logistic regression, we assessed relationships between driving distance and RA diagnosis and between driving distance and DMARD receipt. In one set of analyses, distance was divided into quartiles: 0 –2, 2.1–5, 5.1–15.9, and >16 miles. In a second set of analyses, we used predefined categories: 0 –15, 15.1–30, 30.1– 60, and >60 miles. Results. Among 59,426 Medicare beneficiaries, 918 had diagnosed RA. Compared to the first quartile, increased distance was associated with decreased odds of RA diagnosis (odds ratio [OR] 0.96 [95% confidence interval (95% CI) 0.80 –1.16] in second quartile, OR 0.88 [95% CI 0.72–1.07] in third quartile, and OR 0.72 [95% CI 0.56 – 0.93] in fourth quartile; P < 0.01 for trend). Similar results were observed using predefined categories. Among those with RA, increased distance was associated with increased odds of DMARD receipt across quartiles (OR 1.15 [95% CI 1.06 –1.25] in second quartile, OR 1.41 [95% CI 1.29 –1.54] in third quartile, and OR 1.32 [95% CI 1.18 –1.46] in fourth quartile; P ⴝ 0.001 for trend). There was no relationship between predefined categories and DMARD receipt (P ⴝ 0.45 for trend). Conclusion. Increased driving distance to rheumatologists was associated with decreased odds of RA diagnosis. Among those with diagnosed RA, the odds of DMARD receipt rose as distance increased from 16 (n ⴝ 6,632)
77 ⫾ 7 3,505 (45) 3,179 (41) 1,130 (14)
76 ⫾ 7 3,444 (52) 2,432 (37) 736 (11)
75 ⫾ 7 3,563 (54) 2,361 (36) 708 (11)
5,965 (76) 912 (12) 937 (12) 5,926 (76) 6⫾5 10 ⫾ 5
5,644 (85) 520 (8) 448 (7) 4,962 (75) 6⫾5 10 ⫾ 5
5,783 (87) 555 (8) 294 (4) 4,803 (72) 5⫾4 10 ⫾ 6
0.2 ⫾ 0.6
0.2 ⫾ 0.6
0.3 ⫾ 0.7
2,524 (32) 2,364 (30) 2,252 (29) 104 (1) 2⫾2 1,473 (19) 2,421 (31) 482 (6) 115 (1) 466 (6)
2,447 (37) 1,974 (30) 2,217 (34) 109 (2) 2⫾2 1,184 (18) 1,809 (27) 346 (5) 95 (1) 381 (6)
2,624 (40) 2,056 (31) 2,507 (38) 117 (2) 2⫾2 1,033 (16) 1,766 (27) 352 (5) 78 (1) 325 (5)
3,043 (39) 1,750 (22) 1,611 (21) 1,410 (18)
2,958 (45) 1,775 (27) 1,228 (19) 651 (10)
1,092 (16) 1,715 (26) 2,421 (37) 1,404 (21)
2,838 (36) 1,646 (21) 2,050 (26) 1,280 (16)
1,988 (30) 1,686 (26) 2,061 (31) 877 (13)
4,094 (62) 1,795 (27) 655 (10) 88 (1)
6,435 (82) 832 (11) 426 (5) 121 (2) 52,114 ⫾ 27,479
5,955 (90) 411 (6) 187 (3) 59 (1) 52,683 ⫾ 22,846
5,551 (84) 701 (11) 310 (5) 70 (1) 36,465 ⫾ 12,721
3,696 (47) 1,755 (22) 1,291 (17) 1,072 (14)
3,504 (53) 1,684 (25) 994 (15) 430 (7)
1,700 (26) 2,225 (34) 2,063 (31) 644 (10)
3,819 (49) 2,187 (28) 1,654 (21) 154 (2)
3,547 (54) 1,859 (28) 1,110 (17) 96 (1)
5,434 (82) 981 (15) 203 (3) 14 (0)
5,827 (75) 751 (10) 636 (8) 600 (8) 7,666 (98) 1.29 (0.97–1.73)
5,646 (85) 497 (8) 259 (4) 210 (3) 5,260 (80) 1.09 (0.77–1.49)
5,668 (85) 644 (10) 217 (3) 103 (2) 2,786 (42) 0.65 (0.42–1.01)
* Values are the number (percentage) unless indicated otherwise. NSAID ⫽ nonsteroidal antiinflammatory drug; RTI ⫽ Research Triangle Institute; SES ⫽ socioeconomic status; HSA ⫽ hospital service area (collection of zip codes whose residents receive most of their hospitalizations from the hospitals in that area); IQR ⫽ interquartile range.
184 (1.2) 160 (1.1) 158 (1.1) 1.08 (0.88–1.34) 0.94 (0.76–1.17) 0.93 (0.75–1.16) 1.03 (0.83–1.28) 0.89 (0.71–1.13) 0.77 (0.58–1.03)
141 (1.0) 136 (0.9) 136 (0.9) 0.98 (0.78–1.24) 0.94 (0.75–1.20) 0.94 (0.75–1.20) 0.94 (0.73–1.19) 0.92 (0.71–1.19) 0.88 (0.64–1.21)
170 (1.1) Ref. Ref.
144 (1.0) Ref. Ref.
>17.6 (n ⴝ 14,853)
246 (1.7) 221 (1.5) 200 (1.4) 0.98 (0.82–1.17) 0.88 (0.73–1.05) 0.79 (0.66–0.96) 0.96 (0.80–1.16) 0.88 (0.72–1.07) 0.72 (0.56–0.93)
5.71–17.5 (n ⴝ 14,858)
251 (1.7) Ref. Ref.
2.61–5.7 (n ⴝ 14,857)
* Values are the odds ratio (95% confidence interval) unless indicated otherwise.
Cohort 1 definition (2 diagnoses) No. (%) Unadjusted Adjusted Cohort 2 definition (3 diagnoses) No. (%) Unadjusted Adjusted Cohort 3 definition (2 diagnoses ⫹ steroid prescription) No. (%) Unadjusted Adjusted
0–2.6 (n ⴝ 14,858)
Quartiles of driving distance, miles
0.52
⬍ 0.05
⬍ 0.01
P for trend
411 (1.0) Ref. Ref.
502 (1.1) Ref. Ref.
701 (1.6) Ref. Ref.
0–15 (n ⴝ 43,000)
30.1–60 (n ⴝ 6,171)
>60 (n ⴝ 2,889)
71 (1.0) 46 (0.8) 29 (1.0) 1.01 (0.78–1.30) 0.78 (0.57–1.06) 1.05 (0.72–1.53) 0.92 (0.69–1.23) 0.71 (0.48–1.05) 0.98 (0.62–1.56)
84 (1.1) 55 (0.9) 31 (1.1) 0.98 (0.77–1.23) 0.77 (0.58–1.01) 0.92 (0.64–1.32) 0.83 (0.64–1.10) 0.61 (0.43–0.87) 0.74 (0.48–1.15)
106 (1.4) 73 (1.2) 38 (1.3) 0.88 (0.72–1.08) 0.72 (0.57–0.92) 0.80 (0.58–1.12) 0.79 (0.63–1.00) 0.63 (0.47–0.86) 0.72 (0.49–1.06)
15.1–30 (n ⴝ 7,366)
Predefined categories of driving distance, miles
0.58
⬍ 0.05
0.02
P for trend
Table 2. Number and frequency, unadjusted odds, and adjusted odds of rheumatoid arthritis diagnosis in the 6% patient sample at 365 days, by 2 approaches to define driving distance categories*
Driving Distance, RA Diagnosis, and DMARD Receipt 1639
2,979 (45) 1.85 (1.72–2.00) 1.41 (1.29–1.54)
463 (7) 1.31 (1.13–1.53) 1.05 (0.89–1.24)
546 (8) 1.55 (1.34–1.80) 1.17 (1.00–1.37)
2,291 (35) 1.84 (1.69–1.99) 1.41 (1.29–1.55)
465 (6) 1.10 (0.95–1.28) 1.02 (0.87–1.19)
512 (7) 1.21 (1.05–1.40) 1.09 (0.93–1.28)
2,139 (27) 1.31 (1.21–1.42) 1.17 (1.07–1.28)
5.1–15.9 (n ⴝ 6,612)
2,826 (36) 1.28 (1.19–1.38) 1.15 (1.06–1.25)
2.1–5.0 (n ⴝ 7,814)
2,408 (36) 1.98 (1.82–2.14) 1.33 (1.19–1.49)
583 (9) 1.66 (1.44–1.92) 1.23 (1.02–1.49)
429 (6) 1.21 (1.04–1.40) 1.00 (0.81–1.22)
3,159 (48) 2.06 (1.91–2.22) 1.32 (1.18–1.46)
>16 (n ⴝ 6,632)
0.003
0.08
0.80
0.001
P for trend
5,584 (28) Ref. Ref.
1,337 (7) Ref. Ref.
1,208 (6) Ref. Ref.
7,395 (38) Ref. Ref.
0–15 (n ⴝ 19,698)
1,082 (35) 1.37 (1.26–1.48) 1.07 (0.97–1.18)
261 (8) 1.27 (1.11–1.46) 1.11 (0.95–1.31)
192 (6) 1.02 (0.87–1.19) 0.96 (0.80–1.15)
1,419 (46) 1.42 (1.31–1.53) 1.09 (0.99–1.19)
15.1–30 (n ⴝ 3,083)
960 (37) 1.50 (1.38–1.63) 1.08 (0.95–1.22)
237 (9) 1.39 (1.20–1.61) 1.16 (0.95–1.42)
172 (7) 1.09 (0.93–1.29) 1.08 (0.86–1.35)
1,249 (48) 1.56 (1.44–1.70) 1.03 (0.91–1.16)
30.1–60 (n ⴝ 2,579)
451 (37) 1.46 (1.30–1.65) 1.04 (0.89–1.22)
109 (9) 1.34 (1.09–1.64) 1.07 (0.83–1.39)
85 (7) 1.14 (0.91–1.43) 1.07 (0.80–1.43)
598 (49) 1.57 (1.40–1.77) 1.06 (0.91–1.23)
>60 (n ⴝ 1,230)
Predefined categories of driving distance, miles
* Values are the odds ratio (95% confidence interval) unless indicated otherwise. DMARD ⫽ disease-modifying antirheumatic drug.
Receipt of any DMARD No. (%) 1,697 (31) Unadjusted Ref. Adjusted Ref. Receipt of a biologic DMARD No. (%) 300 (5) Unadjusted Ref. Adjusted Ref. Receipt of combination DMARDs No. (%) 303 (5) Unadjusted Ref. Adjusted Ref. Majority of time on DMARDs No. (%) 1,239 (22) Unadjusted Ref. Adjusted Ref.
0–2.0 (n ⴝ 5,532)
Quartiles of driving distance, miles
Table 3. Number and frequency, unadjusted odds, and adjusted odds of DMARD use at 365 days in cohort 1, by 2 approaches to define driving distance*
0.45
0.04
0.60
0.45
P for trend
1640 Polinski et al
Driving Distance, RA Diagnosis, and DMARD Receipt to receive a DMARD as driving distance increased (n ⫽ 1,697 [31%] in first quartile, n ⫽ 2,826 [36%] in second quartile, n ⫽ 2,979 [45%] in third quartile, and n ⫽ 3,159 [48%] in fourth quartile) (Table 3). Patients with RA were also more likely to spend the majority of time on DMARDs as driving distance increased (n ⫽ 1,239 [22%] in first quartile versus n ⫽ 2,408 [36%] in fourth quartile). The same patterns were observed when predefined categories of driving distance were used. In multivariable logistic analyses, increased driving distance, modeled in quartiles, was significantly associated with an increased likelihood of receiving any DMARD. As compared to patients with driving distances in the first quartile, second quartile patients had 15% greater odds of receiving any DMARD (95% CI 1.06 –1.25), third quartile patients had 41% greater odds (95% CI 1.29 –1.54), and fourth quartile patients had 32% greater odds (95% CI 1.18 –1.46, P ⫽ 0.001 for trend). Similarly, compared to first quartile patients, increased distance to a rheumatologist was associated with an increased likelihood of spending the majority of time on DMARDs (odds ratio [OR] 1.17 [95% CI 1.07–1.28] in second quartile, OR 1.41 [95% CI 1.29 –1.55] in third quartile, and OR 1.33 [95% CI 1.19 – 1.49] in fourth quartile; P ⫽ 0.003 for trend). There was a trend toward increased odds of combination DMARD receipt with increased driving distance. No relationship between increased distance and receipt of a biologic DMARD was observed. In contrast, when driving distance was modeled using predefined categories, no relationships between increased driving distance and any of the DMARD receipt outcomes were observed. For example, as compared to patients who lived 0 –15 miles from the nearest rheumatologist, patients in higher categories had no greater or lesser odds of DMARD receipt (OR 1.09 [95% CI 0.99 –1.19] for 15.1–30 miles, OR 1.03 [95% CI 0.91–1.16] for 30.1– 60 miles, and OR 1.06 [95% CI 0.91–1.23] for ⬎60 miles; P ⫽ 0.45 for trend). Analogous results to those observed in cohort 1 were found in cohorts 2 and 3 (data not shown). In each of the multivariable models, multiple covariates were associated with DMARD receipt. Positive associations included rural versus urban residence (OR 1.24 [95% CI 1.12–1.36]) and higher scores (indicating higher SES) on the RTI SES index (OR 1.12 [95% CI 1.09 –1.16] per 10point increase). Characteristics negatively associated with DMARD receipt included diagnoses of diabetes mellitus (OR 0.75 [95% CI 0.70 – 0.81]), chronic lung disease (OR 0.73 [95% CI 0.64 – 0.83]), cancer (OR 0.89 [95% CI 0.82– 0.97]), and/or myocardial infarction/stroke (OR 0.62 [95% CI 0.58 – 0.67]); all results shown are from the predefined driving distance model.
DISCUSSION Among a sample of patients ages ⬎65 years with comprehensive medical and prescription drug coverage through the US government–sponsored Medicare program, we examined relationships between driving distance and RA diagnosis and between driving distance and DMARD receipt. We observed that increased driving distance to the
1641 nearest rheumatologist was associated with decreased odds of RA diagnosis, a result that was consistent across driving distance definitions. Among patients with an RA diagnosis, the relationship between driving distance and DMARD receipt was sensitive to the exposure definition: while increased driving distance quartiles were associated with a 12–32% increased odds of receiving any DMARD, no association was found between predefined driving distance categories and DMARD receipt. Our observations suggest that driving distance acts as a proxy for at least some of the burden of obtaining rheumatologic care, but has less importance in determining DMARD receipt. The association we observed between increased driving distance and decreased odds of RA diagnosis is important for both health care policymakers and the rheumatology community as they strategize ways to maximize the impact of a limited rheumatologist workforce. These results are in agreement with other studies that have found increased driving distance to be associated with reduced access to specialty health care services. Chan et al found that increasing rurality was associated with an 8% increase in the share of overall visits to generalist providers and a corresponding 10% decrease in the share of visits to medical specialists (13). Currently, the Health Professional Shortage Area (HPSA) Physician Bonus Program offers a 10% bonus to physicians, including rheumatologists, who practice in primary care HPSA and provide services to Medicare beneficiaries (28). Whether the program has expanded access to rheumatology care for elderly beneficiaries is beyond the scope of this study, but merits consideration. In evaluating the relationship between driving distance and DMARD receipt among those with a diagnosis of RA, our results depended on the granularity of the category definitions. When driving distance was defined in quartiles, with finer discrimination among shorter distances (75% of patients lived within 16 miles), patients who lived farther from the nearest rheumatologist were more likely to receive DMARDs. This paradox is known as distance bias, where unmeasured factors such as disease severity, patient resources, and motivation may explain better treatment among patients who live greater distances from care. One potential interpretation of our quartile findings is that patients who live a greater distance from a rheumatologist and are still diagnosed with RA are the patients who possess greater resources, severity of disease, and/or motivation for care that drive them to seek out the best treatment for their condition, i.e., DMARDs. Such interpretations have been described frequently in the oncologic and other literature (14 –17). In a multicenter study of 1,479 patients with multiple myeloma, patients who lived 0 –9 miles from the center had 1.34 times greater odds of death than patients who lived ⬎150 miles away, 10 – 49 miles away (OR 1.25), and 50 –149 miles away (OR 1.19) (16). In another study among 716 patients with lymphoma, the survival of patients who traveled long distances was better than that of patients who lived nearest to the hospital, even though patients who traveled long distances were more likely to have aggressive and advanced disease (17). Ballard et al observed that those who traveled ⬍10 miles for treatment at a referral center hospital had 20% in-
1642 creased odds of death as compared to those who traveled ⬎10 miles (14). Despite evidence of distance bias, other studies have found conflicting results. In a recent study that better controlled for the severity of patients’ disease prior to surgical intervention, no distance bias was observed across quintiles of driving distance, although these quintiles encompassed substantial distances (mean 15.9 miles for quintile 1, 56.1 miles for quintile 2, 117.6 miles for quintile 3, 232.7 miles for quintile 4, and 702.0 miles for quintile 5) (8). Strauss et al observed that increased driving distance was associated with decreased glycemic control among patients with diabetes mellitus and postulated that their results might be due to providers’ reluctance to prescribe more aggressive medication regimens that would increase patients’ risk of hypoglycemia; the mean ⫾ SD for driving distance traveled was 12.2 ⫾ 16.7 km (12). With these examples in mind, we sought corroborating evidence for our initial results by using an alternative definition of the exposure, one that focused on differences across larger distances but did not make fine distinctions for distances less than 15 miles, by using predefined categories of driving distance meant to approximate travel time. In these analyses, we observed no relationship between driving distance and DMARD receipt. Once a patient received an RA diagnosis, treatment in accordance with recommended guidelines was as likely across patients. Taken together, our 2 approaches to defining driving distance and our corresponding results describe only some of the disparity in DMARD receipt, and then only across very short (⬍16 miles) as opposed to longer distances (⬎15 miles). This suggests that driving distance plays a minimal role in DMARD receipt, where ⬎70% of our population reside, and that other factors such as socioeconomic barriers, clinical comorbidities and disease severity, and health-seeking behaviors may better explain previously observed disparities in DMARD use (7–10). With the increasing availability of geographic information systems software and comprehensive data sources that include street addresses, researchers have expanded opportunities to evaluate relationships between driving distance, access to care, and health outcomes. Our study points to the sensitivity of these relationships to the definition of driving distance and suggests that multiple definitions should be employed to test the robustness of observed results. Our results also raise questions as to whether driving distance is a good measure of access to medical care and to medical treatments and procedures. Prescription drug receipt may sometimes be dependent on diagnosis, a likely explanation for the significant trends we observed when the RA diagnosis definition included only diagnosis codes (cohorts 1 and 2) as opposed to the nonsignificant trends we observed when the RA diagnosis definition required a prescription for ⬎1 oral glucocorticoid (cohort 3). In our study, diagnosis was more strongly related to distance; this may hold implications for research examining the utilization of medical interventions or prescription drug treatments based on geography. The sociodemographic characteristics of patients in specific geographies must also be considered. In the US, persons living in urban areas often have lower SES than those
Polinski et al living in suburban or even rural areas, whereas in other countries, persons living in urban areas have higher SES as compared to those living in rural areas. This information provides further context for our US-based results. A strength of our study is that we were able to adjust for multiple individual- and neighborhood-level characteristics that are associated with SES and potential disparities in personal resources that might explain the relationship between driving distance and DMARD receipt (8,14,25,29). Of note, ⬎70% of patients lived within 15 miles of a rheumatologist; patients who live farther away from rheumatology care may be underrepresented in our data due to the potentially reduced likelihood of having prescription drug coverage. Our data source includes patients enrolled in the US government–sponsored Medicare program who have comprehensive health coverage. Our population is age ⬎65 years, and so our results may not generalize to younger patients. Although DMARD treatment is recommended for all patients with RA (2), we acknowledge that physicians’ and patients’ decision making regarding treatment options may be substantially different depending on patients’ age, treatment goals, risk versus benefit considerations, and overall lived experience. Finally, elderly patients’ access to RA diagnosis and treatment may be different from that for younger patients. While comprehensive, our data source for patients does not have information on RA disease severity or on patients’ motivation/health-seeking behavior, both thought to be associated with distance bias. Because information on these factors is unavailable, it is not possible to quantify their impact on the results we observed. Data sources with this information may further elucidate the impact of these factors. Another limitation is the low PPV of our primary definition of RA. We used 2 alternative definitions to explore this and found analogous results. There is strong consensus regarding the utility and importance of DMARDs in treating RA (2). Disparities in DMARD receipt have been well documented and continue to merit concern (3–5). In this study, we explored the relationships between driving distance and RA diagnosis and between driving distance and DMARD receipt. Increased driving distance to a rheumatologist was associated with decreased odds of receiving an RA diagnosis. Once patients did receive the diagnosis, the relationship between driving distance and DMARD receipt depended on the distance traveled: within approximately 16 miles, patients with RA had increased relative odds of DMARD receipt as driving distance increased. Beyond 16 miles, we did not find such a distance bias, observing an essentially flat relationship between driving distance and DMARD receipt. These data points together suggest that urban residents who live closer to a rheumatologist likely have other financial or socioeconomic barriers to DMARD use. While driving distance to the nearest rheumatologist, as a proxy for access, appears to play an important role in receiving an RA diagnosis, it does not appear to explain much of the variability in DMARD receipt. Interventions to shorten the distance to rheumatologic care will likely increase the incidence of RA diagnosis, but are unlikely on their own to lead to improved rates of DMARD use.
Driving Distance, RA Diagnosis, and DMARD Receipt
1643
AUTHOR CONTRIBUTIONS All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. Dr. Polinski had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study conception and design. Polinski, Brookhart, Ayanian, Katz, Kim, Yelin, Solomon. Acquisition of data. Polinski, Lii. Analysis and interpretation of data. Polinski, Brookhart, Ayanian, Katz, Kim, Lii, Tonner, Yelin, Solomon.
15.
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17.
REFERENCES 1. Wailoo AJ, Bansback N, Brennan A, Michaud K, Nixon RM, Wolfe F. Biologic drugs for rheumatoid arthritis in the Medicare program: a cost-effectiveness analysis. Arthritis Rheum 2008;58:939 – 46. 2. Olsen NJ, Stein CM. New drugs for rheumatoid arthritis. N Engl J Med 2004;350:2167–79. 3. Ward MM. Trends in the use of disease modifying antirheumatic medications in rheumatoid arthritis, 1980-1995: results from the National Ambulatory Medical Care Surveys. J Rheumatol 1999;26:546 –50. 4. Schmajuk G, Schneeweiss S, Katz JN, Weinblatt ME, Setoguchi S, Avorn J, et al. Treatment of older adult patients diagnosed with rheumatoid arthritis: improved but not optimal. Arthritis Rheum 2007;57:928 –34. 5. Lacaille D, Anis AH, Guh DP, Esdaile JM. Gaps in care for rheumatoid arthritis: a population study. Arthritis Rheum 2005;53:241– 8. 6. Shipton D, Glaizer RH, Guan J, Badley EM. Effects of use of specialty services on disease-modifying antirheumatic drug use in the treatment of rheumatoid arthritis in an insured elderly population. Med Care 2004;42:907–13. 7. Adler NE. Examining the health disparities research plan of the National Institutes of Health: unfinished business. Washington, DC: National Academies Press; 2006. 8. Etzioni DA, Fowl RJ, Wasif N, Donohue JH, Cima RR. Distance bias and surgical outcomes. Med Care 2013;51:238 – 44. 9. Krieger N, Moss N. Accounting for the public’s health: an introduction to selected papers from a U.S. conference on “measuring social inequalities in health.” Int J Health Serv 1996;26:383–90. 10. Schneider EC, Zaslavsky AM, Epstein AM. Racial disparities in quality of care for enrollees in Medicare managed care. JAMA 2002;287:1288 –94. 11. Deal CL, Hooker R, Harrington T, Birnbaum N, Hogan P, Bouchery E, et al. The United States rheumatology workforce: supply and demand, 2005–2025. Arthritis Rheum 2007;56: 722–9. 12. Strauss K, MacLean C, Troy A, Littenberg B. Driving distance as a barrier to glycemic control in diabetes. J Gen Intern Med 2006;21:378 – 80. 13. Chan L, Hart LG, Goodman DC. Geographic access to health care for rural Medicare beneficiaries. J Rural Health 2006;22: 140 – 6. 14. Ballard DJ, Bryant SC, O’Brien PC, Smith DW, Pine MB,
18.
19. 20. 21. 22. 23.
24. 25. 26. 27.
28.
29.
Cortese DA. Referral selection bias in the Medicare hospital mortality prediction model: are centers of referral for Medicare beneficiaries necessarily centers of excellence? Health Serv Res 1994;28:771– 84. Lamont EB, Hayreh D, Pickett KE, Dignam JJ, List MA, Stenson KM, et al. Is patient travel distance associated with survival on phase II clinical trials in oncology? J Natl Cancer Inst 2003;95:1370 –5. Lenhard RE, Enterline JP, Crowley J, Ho GY. The effects of distance from primary treatment centers on survival among patients with multiple myeloma. J Natl Cancer Inst 1987;5: 1640 –5. Paltiel O, Ronen I, Polliack A, Epstein L. Two-way referral bias: evidence from a clinical audit of lymphoma in a teaching hospital. J Clin Epidemiol 1998;51:93– 8. Gillis JZ, Yazdany J, Trupin L, Julian L, Panopalis P, Criswell LA, et al. Medicaid and access to care among persons with systemic lupus erythematosus. Arthritis Rheum 2007;57: 601–7. Kim SY, Servi A, Polinski JM, Mogun H, Weinblatt ME, Katz JN, et al. Validation of rheumatoid arthritis diagnoses in health care utilization data. Arthritis Res Ther 2011;13:R32. Gabriel SE. The sensitivity and specificity of computerized databases for the diagnosis of rheumatoid arthritis. Arthritis Rheum 1994;37:821–3. Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol 1992;45:613–9. US Census Bureau. American Community Survey. URL: http://www.census.gov/acs/www/. Bonito AJ, Bann C, Eicheldinger C, Carpenter L. Creation of new race-ethnicity codes and socioeconomic status (SES) indicators for Medicare beneficiaries. 2008. URL: http://www.ahrq.gov/research/findings/final-reports/ medicareindicators/index.html. The Dartmouth Atlas of Health Care. Zip code crosswalk files. 2006. URL: http://www.dartmouthatlas.org/tools/downloads. aspx#crosswalks. The Dartmouth Atlas of Health Care. Selected hospital and physician capacity measures. 2006. URL: http://www. dartmouthatlas.org/tools/downloads.aspx#resources. The Dartmouth Atlas of Health Care. Glossary. 2013. URL: http://www.dartmouthatlas.org/tools/glossary.aspx. Krieger N, Chen JT, Waterman PD, Soobader MJ, Subramanian SV, Carson R. Geocoding and monitoring of US socioeconomic inequalities in mortality and cancer incidence: does the choice of an area-based measure and geographic level matter? The Public Health Disparities Geocoding Project. Am J Epidemiol 2002;156:471– 82. Medicare Learning Network. Health professional shortage area (HPSA) physician bonus, HPSA surgical incentive payment, and primary care incentive payment programs. 2012. URL: http://www.cms.gov/Outreach-and-Education/ Medicare-Learning-Network-MLN/MLNProducts/downloads/ HPSAfctsht.pdf. Krieger N, Chen JT, Waterman PD, Rehkopf DH, Subramanian SV. Painting a truer picture of US socioeconomic and racial/ ethnic health inequalities: the Public Health Disparities Geocoding Project. Am J Public Health 2005;95:312–23.
