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Keywords:

  • Disparity;
  • Childhood Health Assessment Questionnaire;
  • Medicaid;
  • Socioeconomic status;
  • Juvenile idiopathic arthritis;
  • Juvenile rheumatoid arthritis;
  • Health-related quality of life;
  • Pediatric Quality of Life Inventory

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. REFERENCES

Objective

To determine the relationship between health insurance status and disease outcome in children with juvenile rheumatoid arthritis (JRA).

Methods

JRA patients followed at a tertiary pediatric rheumatology center were assessed for the number of active joints and number of joints with limited range of motion. Disease activity, patient well-being, and pain were measured. Disability was assessed by the Childhood Health Assessment Questionnaire, health-related quality of life by the Pediatric Quality of Life Inventory (PedsQL) Generic Core Scale, and the PedsQL Rheumatology Module. Health care resource utilization was estimated based on the number of billing events for health services coded in administrative databases; these databases also provided information on patient health insurance status. Children insured by Medicaid or similar state programs for low-income families were considered to have Medicaid status. Disease outcomes of children with Medicaid status was compared with that of children with private health insurance.

Results

Forty (14%) of the 295 children with JRA had Medicaid status. Patients with Medicaid status were more often of nonwhite race (P ≤ 0.04) and more frequently had a polyarticular or systemic disease course (P = 0.04) compared with other patients (n = 255). After correction for differences in disease duration, race, JRA onset, and JRA course between groups, children with Medicaid status continued to have significantly higher disability (P < 0.0003), and lower mean PedsQL Generic Core Scale scores (P < 0.05), while health resource utilization appeared similar between groups.

Conclusion

Despite apparently similar health resource utilization and joint involvement, Medicaid status is associated with significantly lower health-related quality of life and higher disability in JRA.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. REFERENCES

Juvenile rheumatoid arthritis (JRA) is a group of pediatric autoimmune diseases whose hallmark is chronic inflammation of the joints (1). Females are more commonly diagnosed with JRA than males (female:male ratio 3:1) and the disease is more frequent among whites than minority populations in the US (2). The estimated prevalence of JRA is 132 per 100,000 children (95% confidence interval 119–145 per 100,000) (3). Besides the number of involved joints during the first 6-month period after diagnosis, JRA disease onset types are based on the presence of systemic disease, e.g., fever, rash, and serositis. Systemic-onset JRA is diagnosed in children with systemic disease features, irrespective of the number of involved joints; pauciarticular-onset or polyarticular-onset JRA are present if ≤4 joints or ≥5 joints are involved, respectively. JRA disease course is determined by the presence of systemic features and, in the absence of systemic features, the number of involved joints 6 months after diagnosis (in pauciarticular course it is ≤4 involved joints, in polyarticular course it is ≥5 involved joints). JRA often persists into adulthood (4–7) and is associated with increased mortality (8) as well as a large burden of disease (9–11).

Studies in adults with arthritis suggest that patient socioeconomic status (SES) impacts patient prognosis (12). No information is available whether disease outcome of children with JRA is significantly associated with patient insurance status, e.g., whether health disparities may exist. Medicaid coverage has been used as a surrogate measure of low SES in the past (13). However, there is no proof for this concept and, for example, Medicaid coverage could also be the consequence of a financial down drift due to the impact of poor health of either the affected child or other ill members of the child's family. Despite this uncertainty, we hypothesized that health care coverage by state programs for low income families would be a surrogate of low SES, while having private health insurance for the child with JRA was considered to be an indicator of middle to high SES. The objective of this study was to determine the relationship between patient health insurance coverage and disease outcomes with focus on patient disability and health-related quality of life (HRQOL) for children with JRA.

PATIENTS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. REFERENCES

Patient population.

Prospective assessment for relevant disease outcomes (14) occurred between July 2003 and March 2004 in all patients who fulfilled diagnostic criteria for JRA (1) and were treated at the Cincinnati Children's Hospital Medical Center, Cincinnati, OH, a tertiary pediatric rheumatology center.

Disease-related information was entered into a registry partially sponsored by the Robert-Wood Johnson Foundation as part of an institutional project to improve child health (http://www.cincinnatichildrens.org/about/perfect). With the approval of the local institutional review board, registry data that had been collected for improving clinical care delivery were used in secondary analysis to pursue the study objectives.

Outcome measures.

Information on patient age, disease duration, type of JRA onset, and JRA course, as well as the number of joints with active arthritis and those with limited range of motion were collected on standardized clinic forms. In addition, patient current disease activity as rated by the treating pediatric rheumatologist was measured on an 11-point Likert scale (where 0 = inactive disease and 10 = very active disease). A global rating of patient well-being was obtained from the parents using an 11-point Likert scale (where 0 = very poor and 10 = very good) and presented with the sentence stem “Considering all the ways that a rheumatic disease affects a person, please circle one number on the following scale that best rates how the person seen in clinic today has been doing in the past week.”

Patient pain was rated by the parents on an 11-point Likert scale (where 0 = no pain and 10 = very severe pain) presented with the sentence stem “We are interested in learning whether or not the person to be seen in clinic today has been affected by pain because of his or her illness. By circling a single number between 0–10, indicate how much pain the illness has caused in the past week.”

Patient disability was measured by the Childhood Health Assessment Questionnaire (CHAQ) (15), which has been widely validated for children with musculoskeletal diseases (16). The CHAQ was completed by the parents and consists of 30 questions in 8 domains covering major aspects of daily living over a 1-week period: dressing and grooming, arising, eating, walking, hygiene, reach, grip, and activities. Each domain contains at least 1 item that is developmentally appropriate for children according to their age. Items are rated on a 4-point Likert scale (no difficulty, some difficulty, much difficulty, unable to do) with the option to mark “not applicable,” if a child cannot be expected to perform a certain maneuver because of young age. If aids or devices are used or assistance is required, the minimal score for the corresponding domain is 2. The disability index is calculated as the unweighted average of the 8 domain scores and yields a disability score between 0 (no disability) and 3 (most severe disability).

Patient HRQOL was measured using the Pediatric Quality of Life Inventory (PedsQL), which was completed by a subset of parents. The inventory consists of the PedsQL Generic Core Scale, version 4 (17, 18) as well as several disease-specific HRQOL modules, one of which is the PedsQL Rheumatology Module (19). The PedsQL Generic Core Scale is a generic nonpreference-based measure of HRQOL, and encompasses 4 health domains (physical functioning, emotional functioning, social functioning, and school functioning) for the preceding 4 weeks. Items are scored using a 5-point Likert scale (never, almost never, sometimes, often, always). A total health summary score ranging between 0 and 100 is calculated from the sum of the raw scores of the 23 items, with higher scores indicating higher HRQOL.

The PedsQL Rheumatology Module is a 22-item scale that encompasses 5 different domains (pain and hurt, daily activities, treatment, worry, and communication) for the preceding 4 weeks. Scoring is similar to the PedsQL Generic Core Scale. A 5-point Likert scale is used, and a summary score between 0 and 100 is calculated from the raw scores, with higher scores indicating higher HRQOL (9).

Demographic information, health insurance, and presumed SES.

Information on self-assigned patient race was obtained from administrative databases. No information on patient ethnicity was available. However, based on US Census 2000 estimates, Hispanics contribute no more than 2% to the total population of the Cincinnati area (20).

Information of patient health insurance was coded in administrative databases. During the followup period, all patients had coverage of their health care costs by Medicaid, similar state programs for low-income families of children with chronic diseases (e.g., Bureau of Children with Medical Handicaps, Ohio), or their parents had purchased private health insurance. Private health insurance served as surrogate measure of middle to high SES while all other children were thought to have Medicaid status, which we considered to be an indicator of low SES.

Health care resource utilization.

Health care resource utilization was based on billing events for the included patients with JRA between January 2002 and March 2004. This time period was arbitrarily chosen. Electronic billing events allowed us to quantify the number of clinic visits, radiology testing, laboratory testing, and inpatient care of the study cohort. In an attempt to measure access to health care services, we determined the percentage of patients who received a certain type of health care service. The average number of billing events, corrected for the number of patient-years of followup considered was used to measure the extent of health care services use.

Statistical analysis.

Data were prospectively collected using standardized forms during routine outpatient encounters in the rheumatology clinic and entered into an Oracle database (Oracle Inc, Redwood Shore, CA) using an Access 2002 (Microsoft, Redmond, WA) data entry interface. Patient medical record number was used to link billing events captured in administrative databases to the prospectively collected clinical outcomes. Data were analyzed using SAS 8.2 (SAS, Cary, NC) and Excel 2002 (Microsoft). If patients were seen on several occasions during the study period, only clinical information obtained on the first patient encounter was used for the analysis. Only the results of parametric analyses are presented below to compare patient groups for significant differences. Not all patient outcomes were normally distributed, therefore the entire statistical analysis was repeated using nonparametric statistics without relevant changes in the reported significant differences between groups (21).

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. REFERENCES

A total of 295 children with JRA were seen at least once in the rheumatology clinic between July 2003 and March 2004, and were included in the analysis. English was the first language for all studied patients. The mean ± SD age of the patients at the time of the study encounter was 12.6 ± 4.8 years (range 2.4–20.9 years). Two hundred eight of the 295 children (95%) were white, and 40 (14%) of the children had Medicaid status. Medicaid status was seen significantly more often in nonwhite children (P = 0.04) (Table 1).

Table 1. Patient demographics and disease features by insurance status in 295 patients with juvenile rheumatoid arthritis*
CharacteristicsTotal cohort (n = 295)Private health insurance (n = 255)Medicaid status (n = 40)P
  • *

    Values are the number (percentage) unless otherwise indicated. NS = not significant.

  • Children with state-covered health insurance programs for low-income families.

  • White versus nonwhite.

  • §

    By chi-square test and Fischer's exact test.

  • Pauciarticular-onset versus polyarticular- or systemic-onset.

  • #

    Pauciarticular-course versus polyarticular or systemic course.

Age at interview, mean ± SD years12.6 ± 4.812.1 ± 4.811.7 ± 4.7NS
Disease duration at interview, mean ± SD years5.3 ± 4.65.4 ± 4.74.5 ± 4.0NS
Race    
 White280 (95)245 (96)35 (87.5) 
 African American9 (3)4 (1.5)5 (12.5)0.04§
 Asian4 (1)4 (1.5)0 
 Multiracial2 (1)2 (1)0 
 All patients295 (100)255 (100)40 (100) 
Disease onset    
 Systemic27 (11)17 (8)9 (26) 
 Pauciarticular112 (44)104 (47)8 (24)0.005
 Polyarticular114 (45)97 (45)17 (50) 
 All patients with disease onset information253 (100)219 (100)34 (100) 
Disease course    
 Systemic20 (8)14 (7)6 (18) 
 Pauciarticular89 (35)82 (37)7 (20)0.04#
 Polyarticular143 (57)123 (56)21 (62) 
 All patients with disease course information253 (100)219 (100)34 (100) 

Severe disease features at the time of disease onset, e.g., systemic and polyarticular-onset JRA, were more commonly observed in patients with Medicaid status compared with patients with private health insurance (76% versus 53%; P = 0.005). A polyarticular or systemic disease course was seen more often in children with Medicaid status as compared with those with private health insurance (79% versus 62%; P = 0.04) (Table 1).

Corrected for differences in race (white/nonwhite), JRA onset and course, and disease duration there was a trend towards a higher mean number of joints with active arthritis in the Medicaid group than in the private health insurance group (Table 2). Similarly, children with Medicaid status had somewhat higher mean disease activity, more pain, and a lower level of well-being than children with private health insurance (P not significant).

Table 2. Patient outcomes in patients with juvenile rheumatoid arthritis*
Patients with available informationPrivate health insuranceMedicaid statusP
Mean ± SENo. patientsMean ± SENo. patients
  • *

    NS = not significant; PedsQL = Pediatric Quality of Life Inventory.

  • Children with state-covered health insurance programs for low-income families.

  • Based on analysis of variance. P values adjusted for multiple comparisons using Tukey post-hoc test.

  • §

    Adjusted for differences in race, disease duration, disease onset, and disease course between groups.

Number of joints with limited range of motion§4.1 ± 1.32433.4 ± 1.835NS
Number of joints with active arthritis§3.2 ± 1.42435.1 ± 1.935NS
Disease activity2.1 ± 0.42102.8 ± 0.630NS
Patient well-being9.2 ± 0.52117.5 ± 0.729NS
Pain during the preceding week2.4 ± 0.52413.3 ± 0.735NS
Childhood Health Assessment Questionnaire0.23 ± 0.102550.68 ± 0.1440< 0.0003
PedsQL Generic Core Scale86.5 ± 3.118774.5 ± 4.030< 0.05
PedsQL Rheumatology Module85.8 ± 2.612285.8 ± 4.916NS

Even after adjusting for differences in JRA onset and course, disease duration, and race between groups in multivariate analysis, there was a statistically significant difference in patient disability between groups. Children with Medicaid status had importantly higher mean CHAQ scores than those with private health insurance (0.68 versus 0.23; P < 0.0003) (Table 2). The proportion of children achieving normal physical function (CHAQ = 0) was also significantly lower in the Medicaid group (50% versus 77%; P = 0.0004). Although PedsQL Generic Core Scale scores in the Medicaid group were significantly lower than those in the private health insurance group (mean 74.5 versus 86.5; P < 0.05), this was not the case for the PedsQL Rheumatology Module scores (Table 2).

There was no difference in white (n = 280) versus nonwhite children (n = 15) with regard to patient age, the number of joints with active arthritis, or those with limited range of motion, disease activity, or well-being. Similarly, there were no important differences in the CHAQ, PedsQL Generic Core Scale, and PedsQL Rheumatology Module scores between racial groups.

Using the billing events recorded in administrative databases over a 27-month period, information on 445 patient-years of followup with private health insurance and 68 patient-years of followup with Medicaid status were included in the analysis. There was no significant difference between groups in the mean ± SD duration of followup considered per patient (Medicaid status versus private health insurance 1.9 ± 0.53 years versus 1.8 ± 0.56 years; P not significant). Generally, children with Medicaid status had similar access to health care services as children with private health insurance (Table 3). Exceptions were that, compared with the private health insurance group, children with Medicaid status received significantly fewer magnetic resonance images (MRIs; 8% versus 20%; P = 0.03), they were almost twice as likely to have at least one visit to the emergency department (P = 0.02), and were seen more often in the ophthalmology clinic of the tertiary center (P = 0.04). There were no differences in the proportion of children requiring hospital admission between groups.

Table 3. Access to health care services in patients with juvenile rheumatoid arthritis*
Type of servicePrivate health insuranceMedicaid statusP
  • *

    Values are the number (percentage) of patients with at least 1 billing event. NS = not significant.

  • Children with state-covered health insurance programs for low-income families.

  • Based on chi-square test.

Rheumatology clinic255 (100)40 (100)NS
Occupational or physical therapy188 (74)33 (83)NS
Joint injection under ultrasound guidance17 (7)4 (10)NS
Ophthalmology clinic140 (55)24 (60)0.04
Other clinics171 (67)31 (78)NS
Magnetic resonance imaging50 (20)3 (8)0.03
Other radiology tests156 (61)28 (70)NS
Emergency department43 (17)12 (30)0.02
Inpatient care38 (15)7 (18)NS
Clinical testing34 (13)8 (20)NS
Laboratory testing237 (93)39 (98)NS

During the time period considered for health care resource utilization, some patients received certain health care services on several occasions. Overall, the Medicaid group had at least as many billing events (visits) per patient-year of followup as the private health insurance group (Table 4). An exception was a lower mean number of MRIs per patient-year of followup in the Medicaid as compared with the private health insurance group (0.1 versus 0.3; P < 0.001).

Table 4. Frequency of use of health care services*
Type of servicePrivate health insuranceMedicaid statusP
  • *

    Values are the mean number of billing events per patient per year. NS = not significant.

  • Children with state-covered health insurance programs for low-income families.

  • Based on Student's t-test.

Rheumatology clinic4.45.80.02
Occupational or physical therapy2.22.6NS
Joint injection under ultrasound guidance0.30.2NS
Ophthalmology clinic1.62.0NS
Other clinics4.16.3NS
Magnetic resonance imaging0.30.1< 0.001
Other radiology tests2.32.2NS
Emergency department0.30.7NS
Inpatient care0.40.4NS
Clinical testing0.30.3NS
Laboratory testing39.662.7NS

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. REFERENCES

In January 2000, the US Department of Health and Human Services released new national health goals and objectives in a report entitled “Healthy People 2010” (22). Based on this report, the main objectives of the agency are to help the nation achieve 2 major outcomes: increase the quality and years of healthy life, and eliminate health disparities among different population groups. The National Institutes of Health has defined health disparity as differences in the incidence, prevalence, mortality, and burden of disease, and other adverse health conditions that exist among specific population groups in the US, which, among other factors, can be related to patient race, ethnicity, and SES (23).

Marked inequities of disease outcomes with adult musculoskeletal diseases between ethnic and racial groups have been documented (24). Similar to results found in studies of other pediatric diseases (25), the results of this study support the theory that Medicaid status is associated with more disability and lower HRQOL, even in the absence of apparent differences in health care resource utilization. Based on previous studies and when compared with children with private health insurance, the differences in disability and HRQOL with Medicaid status are not only of statistical but also of clinical significance in JRA (26, 27).

When accepting health insurance coverage as a measure of SES, our findings would suggest that health disparities may also be present in JRA. However, there is a considerable overlap between patient insurance status, race, and ethnicity in the US. At least for some childhood chronic diseases, patient insurance status rather than differences in genetic predisposition is thought to be of high importance for differences in disease outcome (28). Genetic differences with various racial backgrounds could be an important additional factor explaining the differences in disease outcome between groups of JRA patients, but the small number of nonwhite patients in this study limits the power to assess the impact of race.

We cannot exclude the possibility that JRA patients with Medicaid status required a longer time for diagnosis or experienced a delay in receiving expert care for their arthritis. However, we believe that these potential differences did not alter the key findings of our study, because children with Medicaid status were not significantly different from the other patients with respect to joint involvement and disease activity at the time of the study.

The cross-sectional design of the study did not allow us to examine potential causal relationships, and identify main barriers or important mediators that could have led to the differences in disability and HRQOL between groups. However, our results support the fact that the observed differences were unlikely due to inappropriate or insufficient JRA therapies because in our study, children with Medicaid status used at least as many health care services as patients with private health insurance. Similar to the results of other studies, children with Medicaid status presented to the emergency department (29, 30) more frequently than children with private health insurance for reasons not further evaluated in this study. We do not think that more frequent visits to the emergency department or the ophthalmology clinic can explain the observed disparities between groups. The same is also true for the differences in MRI use between groups. In addition, children with Medicaid status had similar ratings on the PedsQL Rheumatology Module as children with private health insurance. The scores of the PedsQL Rheumatology Module are more closely related to the effects of pediatric rheumatology interventions than the Peds QL Generic Core scores (9).

It remains to be determined why insurance status is associated with disability and HRQOL in JRA, given that overall health care resource utilization appeared to not be significantly affected by the type of health insurance. We hypothesize that nontreatment-related factors such as poverty and nonadherence with prescribed treatments might account in part for the observed differences in the HRQOL and disability between groups.

No best measure of determining patient SES has been identified. Like other researchers, we considered health insurance coverage as an indicator of patient SES (12, 31) and used this information because it was reliably available in our databases. Other possible approaches to estimating SES included using the family income or the highest educational degree of the parents, both of which would have been dependent on reports from the family, and therefore might not have been as accurate.

A limitation of our study may be that all patients were followed at a single tertiary health care center. This might have led to a referral bias, as it is possible that pediatric rheumatologist consultations were only obtained for the most severely affected patients with Medicaid coverage. However, based on published US Census 2000 estimates (20), the proportion of the study patients with Medicaid status was similar to the proportion of children who are enrolled in state health insurance programs in Ohio (14% in Cincinnati Children's Hospital Medical Center versus 15–20% in Ohio), supporting the fact that there was minimal to no referral bias. In addition, differences in disability and HRQOL between groups persisted even after adjusting for differences in disease severity between groups.

Another limitation of the study may be that we did not have access to comprehensive information of health resource utilization beyond that accumulated at the tertiary center. We believe that we captured the vast majority of health care resources used by the patients and that the main finding (that Medicaid status is associated with more disability and lower HRQOL in JRA) would not have been altered even if differences in health care resource utilization had been present. In addition, we lacked prospective information on patient comorbidities but, based on the review of the patient medical records, there were no differences in the proportion of children with comorbid conditions between groups.

We believe the current study is the first to document a clinically important association between patient insurance status and disease outcome in JRA. Multicenter, longitudinal, quantitative, and qualitative research is required to further elucidate the mechanisms that lead to the observed differences between groups. Prospective studies are required to determine whether access to and utilization of health care resources are truly equitable in patients with different health insurance status. If repeated in other US cohorts and substantiated by other measures of SES, the findings of our study could indicate that health disparities exist in JRA.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. REFERENCES
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