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Keywords:

  • Rheumatoid arthritis;
  • DMARDs;
  • Access to care;
  • Drug utilization;
  • Health services research

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES
  9. APPENDIX A

Objective

The National Committee on Quality Assurance has determined that all patients with rheumatoid arthritis (RA) should be treated with disease-modifying antirheumatic drugs (DMARDs). Our objective was to determine the rate and predictors of DMARD use in a cohort of elderly patients with RA.

Methods

We analyzed health care utilization data for 5,864 Medicare beneficiaries with RA who also participated in a state-run pharmaceutical benefit program in Pennsylvania. Patients with RA were defined as those with at least 3 diagnoses of RA (International Classification of Diseases, Ninth Revision code 714.xx) at least 1 week apart who were enrolled in these programs for at least 12 months during 1995–2004. Multivariate logistic regression was used to assess predictors of synthetic or biologic DMARD use in the 12 months after cohort entry.

Results

Thirty percent of patients filled a DMARD prescription during 12 months of followup. Frequency of DMARD use increased steadily over time: 24% received DMARDs in 1996 compared with 43% in 2003 (P for trend <0.001). Of patients with at least 1 rheumatologist visit, 41% received a DMARD in 1996 compared with 70% in 2003 (P < 0.001). After the introduction of biologic DMARDs in 1998, 6% of all patients with RA received a biologic, including 12% who saw a rheumatologist. Patients ages 75–84 were 52% less likely to receive DMARDs (95% confidence interval [95% CI] 46–58%) and patients ages ≥85 were 74% less likely (95% CI 69–79%) compared with patients ages 65–74.

Conclusion

In this cohort of patients in the community with full prescription drug coverage, most patients diagnosed with RA did not receive a DMARD during the 12 months after cohort entry. Older patients and those not seeing a rheumatologist were less likely to receive a DMARD and may provide a target for quality improvement interventions.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES
  9. APPENDIX A

There is widespread agreement that treatment with disease-modifying antirheumatic drugs (DMARDs) is essential to prevent joint destruction and long-term disability in patients with rheumatoid arthritis (RA) (1). Experts suggest that every patient with established, active RA be treated with DMARDs at the earliest stage of disease, ideally within 3 months of onset (2). A comprehensive set of process measures for RA developed through the Arthritis Foundation Quality Indicators Project came to similar conclusions (3). Furthermore, the National Committee for Quality Assurance revised HEDIS 2006 (Health Plan Employer Data and Information Set), the annually updated tool that US health plans use to assess and report on their performance, to contain a measure recommending the prescription of DMARDs for all patients with active RA unless there is documented contraindication or patient refusal.

Prior US data on DMARD prescribing comes from the 1980s and 1990s: investigators using the National Ambulatory Medical Care Survey and the Arthritis, Rheumatism, and Aging Medical Information System (ARAMIS) database found rates of DMARD use to range from 30% to 44% in nonspecialized outpatient settings, and upwards of 70% in rheumatology subspecialty clinics (4, 5). An analysis of a database of Medicare and Medicaid beneficiaries with a pharmacy benefit in New Jersey suggested that in the elderly, only 13% of patients with RA receive DMARDs (6). More recent studies using administrative databases in Canada describe DMARD use in patients diagnosed with RA as ranging from 31% to 77%, even in patients who have contact with a rheumatologist (7, 8). Several studies from Sweden, Spain, Germany, and the US have investigated rates of DMARD use among patients seen regularly by rheumatologists. The percentages of patients receiving DMARDs in such studies range from 37% to 91% (9–15). Rates of DMARD use in US patients have not been assessed since the introduction of biologic DMARDs, including the tumor necrosis factor α antagonists.

Few studies address disparities in the use of DMARDs. Two large Canadian studies suggest that contact with a rheumatologist in addition to patient characteristics (including age and socioeconomic status) predict the use of DMARDs in patients with RA. However, there are conflicting results on the role of sex and comorbidities in the prescription of DMARDs (7, 8). Small studies from Sweden and the US demonstrate that increasing age is an important determinant of less aggressive RA care (16, 17).

The present study examined a large health care utilization database to assess the frequency and predictors of DMARD use in a cohort of older adults during a 12-month followup period. We provide information on the size of the gap between current care and optimal care for patients with RA.

PATIENTS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES
  9. APPENDIX A

Study population and data sources.

We performed an observational closed-cohort study of older adults diagnosed with RA to study the frequency and predictors of DMARD use. All individuals enrolled in both Medicare and the Pharmaceutical Assistance Contract for the elderly (PACE) in Pennsylvania were eligible for the study. The PACE program provides drug insurance for patients over age 65 with low to moderate income (annual household incomes in the range of $10,000–$17,000). We required that study participants be active users of Medicare and PACE for at least 3 consecutive 6-month periods during 1995–2004. Active users were defined as persons who filled at least 1 prescription and had at least 1 health care encounter in each of the three 6-month periods. Because we did not have data prior to 1994, the cohort defined in 1995 was substantially different from the other annual cohorts; therefore, these analyses focus on the patients entering the cohort between 1996 and 2004.

From this pool of eligible participants, we selected patients to be included in the cohort if they had at least 3 outpatient or inpatient diagnoses for RA (International Classification of Diseases, Ninth Revision [ICD-9] code 714.xx). Three of these visits for RA must have been separated by at least 1 week. A similar inclusion criterion has been used in prior studies of RA using administrative data (3,7). To obtain adequate baseline and followup information, we required that all patients be included in the database and be eligible for a minimum of 12 months prior (baseline period) to the third recorded RA diagnosis (index date) and 12 months following this date. In addition, we studied a subgroup of patients who had at least 1 visit to a rheumatologist during the baseline period.

Study end point: DMARD use.

We studied the use of synthetic and biologic DMARDs, oral glucocorticoids, and nonsteroidal antiinflammatory drugs (NSAIDs) in these populations. To be as inclusive as possible, we purposefully used an expanded list of synthetic DMARDs, including azathioprine, cyclophosphamide, cyclosporine, D-penicillamine, oral and injectable gold, hydroxychloroquine, leflunomide, methotrexate, minocycline, mycophenolate mofetil, sulfasalazine, and tacrolimus. Biologic DMARDs included adalimumab, anakinra, etanercept, and infliximab. (During the study period, neither rituximab nor abatacept had been approved for RA.) NSAIDs included both nonselective drugs and selective cyclooxygenase 2 inhibitors, which were fully covered by the PACE drug plan with a small dispensing fee.

We gathered prescription drug information through pharmacy claims submitted to PACE. For all prescriptions, this database includes the drug name, dose, dispensing date, quantity dispensed, and prescriber code for drugs paid for by PACE. Information is linked to specific patients and prescribers through unique identifiers. All research was approved by the Partners Healthcare Institutional Review Board and was conducted under the appropriate Data Use Agreements with Medicare and PACE.

The primary end point was the use of any DMARD (synthetic or biologic) in the 12-month period following the first eligible RA diagnosis during the study period. We defined DMARD use as having filled at least 1 prescription for a synthetic or biologic DMARD described above. Multiple prescriptions for the same DMARD were counted only at the first use. If a patient received multiple prescriptions for different DMARDs during the 12-month followup period, each DMARD was counted separately. Secondary end points included use of synthetic and biologic DMARDs separately, use of specific DMARDs, and use of oral glucocorticoids or NSAIDs without the use of a DMARD.

Statistical analysis.

We evaluated the baseline characteristics of the study cohort using data from the 12 months prior to the first eligible RA diagnosis, including demographic, clinical, and health system use variables. Specific ICD-9 codes used to define comorbid conditions are listed in Appendix A. We also grouped these conditions into a comorbidity index (18). We attempted to assign a primary prescriber to each patient, which was defined as the physician who prescribed the majority of all prescriptions (DMARD and non-DMARD) filled during the baseline period. Physicians were categorized according to the American Medical Association Master File as being an internist, family physician, general practitioner, rheumatologist, or other. Internists or family physicians with subspecialties (other than rheumatology) were assigned to the internist or family physician category, respectively. If a patient did not have a physician who prescribed the majority of medications, then that patient was designated as not having a primary prescriber.

We evaluated the proportion of patients receiving different treatments for RA, including DMARDs, oral glucocorticoids, and NSAIDs. These analyses were stratified by key patient characteristics such as age, sex, and comorbidity index. Finally, we used multivariable logistic regression to model DMARD use as a function of patient and physician predictors. Separate models were constructed for patients who had seen a rheumatologist during the baseline period. In sensitivity analyses, potential nonindependence of patient observations by clustering within a given prescriber was explored using generalized estimating equations (GEE) (19).

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES
  9. APPENDIX A

The characteristics of the patients in the baseline 12-month period are shown in Table 1. All of the patients were over age 65 years, and 94% were white, reflecting the composition of the source population from the PACE database. Of the total population, 1,947 patients (33%) had at least 1 visit to a rheumatologist during the 12-month baseline period. Of these patients who saw a rheumatologist during the baseline period, 90% also saw a rheumatologist at least once during the 12-month followup period. Patients in the study had both new and old diagnoses of RA: 59% of patients did not have any visits for RA during the 12-month baseline assessment period. This suggests that either they had newly diagnosed RA or that they did not have a health encounter for RA during the baseline period.

Table 1. Characteristics of patients diagnosed with rheumatoid arthritis, 1996–2004, during the 12 months prior to the index date*
CharacteristicTotal cohort (n = 5,864)Patients seen by a rheumatologist during baseline period (n = 1,947)
  • *

    Values are the number (percentage) unless otherwise indicated. NSAIDs = nonsteroidal antiinflammatory drugs; NA = not applicable; IM = internal medicine physicians (including subspecialists).

Female sex5,184 (88.4)1,738 (89.3)
Race  
 White5,490 (93.6)1,813 (93.1)
 African American316 (5.4)111 (5.7)
 Other58 (1.0)23 (1.2)
Age, years  
 65–742,002 (34.1)908 (46.6)
 75–842,815 (48.0)822 (42.2)
 ≥851,047 (17.9)217 (11.2)
Charlson score  
 01,004 (17.1)199 (10.2)
 11,595 (27.2)564 (29.0)
 21,332 (22.7)494 (25.4)
 >21,933 (33.0)690 (35.4)
Coronary or cerebral vascular disease966 (16.5)293 (15.1)
Congestive heart failure699 (11.9)173 (8.9)
Pulmonary disease1,037 (17.7)344 (17.7)
Renal disease126 (2.2)41 (2.1)
Diabetes649 (11.1)203 (10.4)
Malignancy541 (9.2)187 (9.6)
Anemia or other hematologic disease1,258 (21.5)415 (21.3)
Depression218 (3.7)78 (4.0)
Hospitalization1,722 (29.4)554 (28.5)
Nursing home resident349 (6.0)93 (4.8)
At least 1 radiologic procedure4,255 (72.6)1,536 (78.9)
At least 1 surgical procedure563 (9.6)213 (10.9)
At least 1 rheumatologist visit1,947 (33.2)1,947 (100.0)
In followup, at least 1 rheumatologist visit2,653 (45.2)1,475 (89.6)
 Glucocorticoids prescribed during baseline1,364 (23.3)704 (36.2)
 NSAIDs prescribed during baseline2,971 (50.7)1,046 (53.7)
 No. of prescriptions, mean ± SD9.4 ± 5.69.8 ± 5.9
 No. of physician visits, mean ± SD11.0 ± 7.613.6 ± 8.4
 No. of visits with rheumatologist, mean ± SD1.5 ± 3.44.6 ± 4.4
No. patients with a primary prescriber4,805 (81.9)1,439 (73.9)
 No. of unique primary prescribers2,773 (NA)978 (NA)
 Patients with IM as primary prescriber (including subspecialists)1,986 (33.9)492 (25.3)
 Patients with rheumatologist as primary prescriber494 (8.4)476 (24.4)
 Patients with general or family practice as primary prescriber2,007 (34.2)398 (20.4)
 Patients with other specialty as primary prescriber318 (5.4)73 (3.7)

We determined the primary prescriber of each patient during the baseline period (Table 1). Eighty-two percent of patients in the total cohort had a designated primary prescriber. For most patients, the primary prescriber was a general practitioner, family physician, or internist. The primary prescriber was a rheumatologist for 494 (8%) of patients in the cohort. Of those patients who saw a rheumatologist at least once during the baseline period, 24% had a primary prescriber who was a rheumatologist.

The utilization of antirheumatic treatments in this cohort of patients with RA is shown in Table 2. Thirty percent of patients filled a prescription for a DMARD, either synthetic or biologic, during the 12-month followup period. Sixteen percent of patients received oral glucocorticoids but no DMARD, and 27% of patients received NSAIDs only (no oral glucocorticoids, no DMARDs). Twenty-seven percent of patients received neither DMARDs, glucocorticoids, nor NSAIDs. In the subgroup of patients with at least 1 visit to a rheumatologist during the baseline period, 53% filled a prescription for a DMARD during 12 months of followup (P < 0.001 compared with patients not seen by a rheumatologist during baseline), 14% received oral glucocorticoids but no DMARD, and 16% received NSAIDs only (no glucocorticoids, no DMARDs). Seventeen percent received neither DMARDs, glucocorticoids, nor NSAIDs.

Table 2. Prescribing of treatments for patients with rheumatoid arthritis during the 12 months following cohort entry*
 Total cohort (n = 5,864)Patients seen by a rheumatologist during baseline period (n = 1,947)
  • *

    Values are the number (percentage). Synthetic DMARD and biologic DMARD groups are not mutually exclusive. DMARD = disease-modifying antirheumatic drug; NSAID = nonsteroidal antiinflammatory drug; none of the above = patients who received neither DMARDs, glucocorticoids, nor NSAIDs.

Any DMARD1,763 (30.1)1,037 (53.3)
 Any synthetic DMARD1,736 (29.6)1,016 (52.2)
 Any biologic DMARD143 (2.4)114 (5.9)
Glucocorticoids, no DMARDs932 (15.9)272 (14.0)
Only NSAIDs1,579 (26.9)313 (16.1)
None of the above1,590 (27.1)325 (16.7)

The trends of DMARD use over time are shown in Figure 1. During the 9-year study period, the proportion of patients who received DMARDs in the total population ranged from 24% in 1996 to 43% in 2003 (P for trend <0.001). Of patients with at least 1 visit to a rheumatologist, 41% received a DMARD in 1996 compared with 70% in 2003. After the introduction of biologic DMARDs in 1998, 6% of all patients with RA filled a prescription for one of these agents, including 12% of patients who saw a rheumatologist during the 12 months prior to cohort entry. The group seeing rheumatologists had higher rates of synthetic DMARD and biologic DMARD use during all years when compared with the entire cohort.

thumbnail image

Figure 1. Trends of disease-modifying antirheumatic drug (DMARD) use over time, from 1996 through 2003. Patients were assigned the calendar year in which they entered the study cohort. Diamonds represent patients from the entire cohort who received any DMARD; squares represent patients from the entire cohort who received a biologic DMARD; triangles represent patients from the rheumatologist-visiting subgroup who received any DMARD; circles represent patients from the rheumatologist-visiting subgroup who received a biologic DMARD.

Download figure to PowerPoint

The frequency of use of different drug combinations in the entire RA cohort is illustrated in Figure 2. When patients were grouped according to age at the first eligible RA diagnosis, older patients were less likely to receive DMARDs: patients ages 65–74 received a DMARD 44% of the time, those ages 75–84 received a DMARD 26% of the time, and those 85 and older received a DMARD 15% of the time (P for trend <0.001). When patients were grouped according to their Charlson comorbidity score, patients with a score of 0 had lower rates of DMARD use compared with patients with Charlson scores of ≥1 (P < 0.001).

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Figure 2. Frequency of different drug combinations in the entire rheumatoid arthritis cohort. Patients are subdivided A, according to age at the time of cohort inception and B, by Charlson comorbidity score. In A, darkly shaded bars represent ages 65–74 (n = 2,002), lightly shaded bars represent ages 75–84 (n = 2,815), and hatched bars represent ages >85 (n = 1,047). In B, darkly shaded bars represent Charlson score 0 (n = 1,004), lightly shaded bars represent Charlson score 1 (n = 1,595), hatched bars represent Charlson score 2 (n = 1,332), and open bars represent Charlson score >2 (n = 1,933). DMARD = disease-modifying antirheumatic drug; NSAIDs = nonsteroidal antiinflammatory drugs.

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Similar patterns were seen in the subgroup of patients who saw a rheumatologist at least once during the baseline period: patients ages 65–74 received a DMARD 65% of the time, those ages 75–84 received a DMARD 46% of the time, and those 85 and older received a DMARD 32% of the time (P for trend <0.001). In this subgroup, patients with a Charlson score of 0 received a DMARD 28% of the time, those with a Charlson score of 1 received a DMARD 57% of the time, those with a Charlson score of 2 received a DMARD 59% of the time, and those with a Charlson score of ≥3 received a DMARD 54% of the time.

The frequency of use of specific DMARDs in the total population and in the subgroup that visited a rheumatologist is shown in Figure 3. For both groups, the most commonly used DMARD was methotrexate, followed by hydroxychloroquine. In the entire cohort, sulfasalazine was the third most common synthetic DMARD; among patients who visited a rheumatologist, leflunomide was the third most common synthetic DMARD. Etanercept was the most commonly prescribed biologic DMARD in both groups.

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Figure 3. Frequency of specific disease-modifying antirheumatic drugs (DMARDs) used in the total population and the subgroup that visited a rheumatologist. Frequencies are represented as a percentage of the total prescriptions for that type of DMARD, either synthetic or biologic. Lightly shaded bars represent the entire cohort (n = 1,763); darkly shaded bars represent patients seen by a rheumatologist (n = 1,037). IM = intramuscular; PO = by mouth.

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The results of a multivariable logistic regression model examining predictors of not receiving a DMARD are shown in Table 3. In the total population, increasing age was associated with significantly decreased rates of DMARD use (patients ages 75–84: adjusted odds ratio [OR] 0.47, 95% confidence interval [95% CI] 0.42–0.54 and patients ages ≥85: adjusted OR 0.25, 95% CI 0.20–0.30) compared with patients ages 65–74. Patients whose primary prescriber was not a rheumatologist also had a 4-fold lower probability of receiving a DMARD (adjusted OR 0.22, 95% CI 0.18–0.27). Depressed patients also had lower rates of use (adjusted OR 0.67, 95% CI 0.48–0.94) compared with patients who did not carry a diagnosis of depression. Results did not change meaningfully after adjusting for clustering using GEE methods.

Table 3. Adjusted associations between patient characteristics and disease-modifying antirheumatic drug use during the 12 months following cohort entry among patients with rheumatoid arthritis*
ParameterReference groupTotal cohortPatients seen by a rheumatologist during baseline period
  • *

    Values are the odds ratio (95% confidence interval). No rheumatologist = patients who had another type of physician as a primary prescriber or who did not have a primary prescriber assigned; CCVD = coronary and cerebral vascular disease.

Male sexFemale sex0.98 (0.81–1.18)1.11 (0.81–1.52)
African American raceWhite0.98 (0.75–1.28)0.67 (0.44–1.01)
Other raceWhite1.08 (0.60–1.95)0.49 (0.20–1.22)
Age 75–84Age 65–740.47 (0.42–0.54)0.47 (0.38–0.57)
Age ≥85Age 65–740.25 (0.20–0.30)0.26 (0.19–0.36)
No rheumatologistPrimary prescriber rheumatologist0.22 (0.18–0.27)0.82 (0.78–0.85)
CCVDNo CCVD0.89 (0.75–1.07)1.11 (0.84–1.48)
Heart failureNo heart failure0.83 (0.67–1.01)0.88 (0.62–1.25)
Pulmonary diseaseNo pulmonary disease1.03 (0.88–1.21)1.10 (0.85–1.43)
DiabetesNo diabetes1.15 (0.95–1.39)1.09 (0.79–1.49)
MalignancyNo malignancy1.09 (0.89–1.34)0.94 (0.68–1.29)
AnemiaNo anemia1.06 (0.90–1.26)1.07 (0.82–1.40)
DepressionNo depression0.67 (0.48–0.94)0.69 (0.42–1.13)
Prior hospitalizationNo prior hospitalization1.08 (0.93–1.26)1.15 (0.90–1.46)
3–8 prescription drugs<3 prescription drugs1.21 (0.93–1.59)1.09 (0.72–1.66)
>8 prescription drugs<3 prescription drugs1.31 (0.99–1.73)0.79 (0.51–1.23)

Similarly, among patients who had seen a rheumatologist at least once during the baseline period, increasing age was found to be a significant predictor of not receiving a DMARD (patients ages 75–84 years: adjusted OR 0.47, 95% CI 0.38–0.57 and patients ≥85 years: adjusted OR 0.26, 95% CI 0.19–0.36) compared with patients ages 65–74. Patients without a rheumatologist as a primary prescriber had a lower probability of receiving a DMARD (adjusted OR 0.82, 95% CI 0.78–0.85).

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES
  9. APPENDIX A

We examined the frequency of DMARD use and predictors of use among a large cohort of older adults diagnosed with RA who were beneficiaries of Medicare and the PACE program in Pennsylvania during the period 1995–2004. During a 12-month followup period, approximately one-third of all patients with RA received a DMARD. The frequency of treatment with a DMARD was doubled among patients who saw a rheumatologist at least once during their disease course. Similarly, after biologic DMARDs became available in 1998, 6% of all patients with RA filled a prescription for a biologic DMARD, including 12% of patients who saw a rheumatologist. Adjusted regression models suggest that increasing age and a diagnosis of depression are significant predictors of failure to use a DMARD. Among patients in the entire cohort, having a rheumatologist as a primary prescriber increased the likelihood of DMARD use by a factor of 4. Concerns about polypharmacy did not seem to account for these findings because there was no significant difference in prescribing patterns among patients who filled between 1 and more than 8 prescription drugs.

The overall frequency of DMARD use appears low in this group of patients, but it is not significantly different from that documented in other community-based cohorts where socioeconomic status is not part of the selection criteria. In the mid 1990s, a study based on the National Ambulatory Medical Care Survey reported that fewer than 44% of patients with RA used DMARDs. More recently, reports from Canada found that rates of DMARD use were only 31% in British Columbia (during a 12-month period) (7) and 58% in Ontario (during a 36-month period) (8). Prior studies have also found that the use of DMARDs has increased over time (4). Methotrexate and hydroxychloroquine remain the most frequently prescribed DMARDs; this is consistent with other recent studies of rheumatologist prescribing patterns (5–7, 10–15, 20–22).

Our research has important limitations. First, the diagnosis of RA is based on 3 visits coded with the RA diagnosis (ICD 714.xx). We recognize that some of these patients may not fulfill formal classification criteria for RA and that we cannot discern the duration or activity of their disease (23). This misclassification may account for some of the apparent undertreatment of RA. However, even patients who were diagnosed with RA and were seeing rheumatologists did not uniformly receive DMARDs. Second, some patients may have contraindications to DMARD treatment or may have refused treatment with a DMARD, and we would not know this from the administrative data. Third, some patients may have tried DMARDs prior to the study period but because of adverse effects or lack of efficacy decided not to continue them. Because we do not have a complete lifetime record of these patients' drug utilization, this would have biased our results as well. Finally, some patients may receive DMARDs outside of the PACE and Medicare programs. However, this would be unusual in a means-tested program in which patients must actively enroll and receive drugs with a minimal copayment. Although there are several limitations to this study, none is likely to affect the relative comparison of drug use between older and younger patients or between nonspecialists and rheumatologists.

The new HEDIS measure suggests that the vast majority of patients with RA should be treated with DMARDs early in the course of their disease. The present study, in addition to previous community-based cohorts, indicates that current practice does not meet this goal. More data need to be collected in additional, more diverse populations to clarify the scope of RA undertreatment. If our results are confirmed, quality improvement efforts to address suboptimal RA care will need development. Initially, these programs might focus on groups at particular risk of undertreatment, most notably patients over the age of 75 and possibly persons with depression. Based on the low rate of DMARD use among patients treated principally by their primary care physicians, programs to expedite referrals to rheumatologists (or at least physicians with experience treating RA) are needed so that these patients can be started on DMARD therapy. Although the increase in the prescription of DMARDs, in particular biologic DMARDs, among patients seeing rheumatologists may be due to these physicians' familiarity in treating RA, another significant factor might be that these medications are easier to prescribe from the specialty clinic. Specialists may have samples and teaching videos in their offices and may be able to infuse the drugs themselves. Nevertheless, education programs for primary care physicians should focus on the morbidity and mortality associated with RA; the comorbidities associated with this disease such as heart disease, infection, and malignancy; the importance of DMARD therapy in the treatment of patients with RA; and the role of the rheumatologist in this setting.

AUTHOR CONTRIBUTIONS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES
  9. APPENDIX A

Dr. Solomon 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 design. Schmajuk, Schneeweiss, Weinblatt, Setoguchi, Avorn, Solomon.

Acquisition of data. Schmajuk, Avorn, Levin, Solomon.

Analysis and interpretation of data. Schmajuk, Schneeweiss, Katz, Weinblatt, Setoguchi, Levin, Solomon.

Manuscript preparation. Schmajuk, Katz, Weinblatt, Solomon.

Statistical analysis. Schmajuk, Schneeweiss, Setoguchi, Levin, Solomon.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES
  9. APPENDIX A

APPENDIX A

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES
  9. APPENDIX A
Table  . INTERNATIONAL CLASSIFICATION OF DISEASES, NINTH REVISION CODES USED TO DEFINE COMORBID CONDITIONS
Coronary or cerebrovascular disease36, 410–413, 433–436
Heart failure425, 428
Pulmonary disease135, 490–496, 500–505, 508, 515, 516–518.3, 518.6, 518.83, 518.89
Renal disease582–583, 585–587
Diabetes250, 357.2
Malignancy140–208, 230–238, V58, V66, V67
Anemia280, 281, 285.9
Other hematologic diseases273, 279, 282–289, except 285.9
Depression296.2, 296.3, 300.4, 311