This study analyzed racial and ethnic disparities in the use of all new medications using MEPS data and the negative binomial model. None of the confidence intervals for the dispersion parameter alphas included zero, indicating that it is appropriate to use the negative binomial model in this study.
Both the descriptive and multivariable analyses revealed significant racial disparities: the number of times when new medications were obtained was higher among non-Hispanic whites than non-Hispanic blacks. These findings are consistent with previous studies on racial disparities in the use of prescription drugs at the aggregate level (Hanlon et al. 1992
; Hahn 1995
; Khandker and Simoni-Wastila 1998
; Chen and Chang 2002
; Philips and Atherly 2002
). Our study extends the prior results regarding racial disparities. The fact that racial disparities were still significant after we adjusted for the total number of other prescription medications in the model suggests that the racial disparities in the use of new medications might be greater than racial disparities in older medications.
This study also found ethnic disparities between non-Hispanic whites and Hispanic whites in new medication use based on descriptive analysis. These disparities were not evident in the multivariable analysis. Most previous studies found that Hispanics have lower utilization of prescription drugs in general compared with their white or non-Hispanic white counterparts (Smith and Kirking 1999
; Chen and Chang 2002
When comparing racial and ethnic disparities, this study found that ethnic disparities were smaller (5–16 percent) than racial disparities (22–33 percent) after adjusting for confounding factors. However, it was the opposite before adjusting for confounding factors. In addition to the fact that ethnic disparities were not always significant in the multivariate analysis but racial disparities were, these findings suggest that ethnic disparities can be explained by confounding factors, including demographic characteristics, economic characteristics, and health status, to a greater degree than racial disparities. As Mayberry et al. have summarized, although access to health care for racial and ethnic minorities in general is poorer than the majority population, it is more problematic for the individuals with skin color different from the majority population (Mayberry, Mili, and Ofili 2000
). Part of this might be due to historical discrimination and maltreatment toward “blacks” and this might impact health care in a subtle way (Mayberry, Mili, and Ofili 2000
Since none of the coefficients of interaction terms between racial and ethnic variables and criteria for new drugs were significant, there is no evidence of decreasing racial or ethnic disparities in the early years of drug products' life cycles. This is consistent with the limited empirical literature. Previous studies have examined a longer time period when looking at the trend of racial and ethnic disparities without a specific focus on the early period of drugs' life cycles. These studies have not found a statistically significant time trend of racial or ethnic disparities in the use of medications (Blazer et al. 2000
; Daumit et al. 2003
). The test of the trends in this study may be confounded with period effects including industry effects, which were not specifically examined in the analyses. However, as the approval years of the new medications examined in this study spanned a long period of time and we found that disparities did not decrease over time in early years of drug products' life cycles, the racial disparities in new medication use are concerning.
A discussion of possible sources of racial and ethnic disparities in the use of new medications is warranted in order to inform policy-making process. This can be done following the Behavioral Model of Health Services Utilization (Andersen and Davidson 2001
). The predisposing variable of age was a significant determinant for the use of new prescription drugs. Significant enabling factors included the generosity of prescription drug benefits. Need factors, including the number of medical conditions, the number of other prescription medications, and the number of office-based physician visits, were also significant; self-perceived health status was almost always significant.
Age and the generosity of prescription drug benefits had positive effects on the use of new prescription drugs. The rate ratios of age were always 1.02. This suggests that as age increased by 1 year, the number of times a person obtained new drugs would increase by 2 percent. The rate ratios for the generosity of prescription drug benefit were always greater than two. This suggests that if a person's health insurance covered 100 percent of the drug cost, the number of times this person obtained new drugs would at least double compared with an individual with no drug benefit. As the number of medical conditions was increased by one, the number of times that a person obtained new medications increased by 2 percent. When the number of other prescription medications was increased by one, the number of times that a person obtained new medications would increase by 7–11 percent. When the number of office-based physician visits increased by one, an individual used 1–3 percent more new medications. Compared to a person with self-perceived excellent health status, the number of times when new drugs were obtained could be 18–115 percent higher among individuals with self-perceived very good, good, fair, or poor health status.
The significant effects of these factors suggest that individual factors conceptualized in the Behavioral Model of Health Services Utilization are associated with new prescription drug use and are modifiers of racial and ethnic disparities in new prescription drug use. However, racial disparities were still significant after controlling for these factors, so these factors do not account for all racial disparities. This inference is in keeping with previous studies that have shown that confounding factors did not account for all racial disparities (Smith and Kirking 1999
; Blazer et al. 2000
; Chen and Chang 2002
; Daumit et al. 2003
What might be sources of significant racial disparities after adjusting for confounding factors? Racial disparities may be related in part to individual behaviors. Members of a minority population might engage in risky health behaviors, such as failing to fill or refill prescriptions (Daumit et al. 2003
). However, this study examined only prescription users, so the role of failing to fill or refill prescriptions is likely to be less important as a source for racial disparities.
Other individual characteristics might have also contributed to the observed racial disparities in the use of new medications. For example, mistrust of the health care system serves as barriers to health care use by a minority population (LaVeist, Nickerson, and Bowie 2000
; Mayberry, Mili, and Ofili 2000
). Minorities might be less likely to try new drugs or may delay seeking health care (Blazer et al. 2000
). There is a growing literature that suggests that minority neighborhood may have fewer pharmacies and some pharmacies in these neighborhoods might not carry certain categories of medications (Morrison et al. 2000
; Spernak et al. 2005
). This would have an impact on the use of drugs.
It has been reported that the incidence and prevalence rates of various disease and medical conditions vary across racial and ethnic groups (Daumit et al. 2003
). However, the variation across racial and ethnic groups should not be overemphasized: the list of genetic characteristics much more common in African Americans than other racial and ethnic groups is small (Stolley 1999
Causes of racial disparities in the use of new medications might also come from the health care providers (Jones 2000
). In the event of differential prescribing patterns by physicians, minorities may not be prescribed new drugs at the same rate (Shaya et al. 2005
). These factors could not be explored in this study.
The study strengths included the following aspects. The first strength lies in the data source. MEPS is the first national expenditure survey that has taken measures to address the issue of underreporting of prescription drug use by obtaining computerized printouts from respondents' pharmacy providers (Agency for Healthcare Research and Quality 2003
). Moreover, the study sample covered a cross-section of U.S. citizens who were prescription users, which makes the results more generalizable compared with most previous research on the racial and ethnic disparities in the use of prescription drugs. Additionally, MEPS oversampled Hispanics to make possible reliable estimates for this population. Most previous household surveys did not have the statistical power to adequately compare Hispanics with other racial and ethnic groups.
Some of the limitations include the fact that nonusers of prescription drugs were excluded from the study; thus, the results cannot be generalized to nonusers of prescribed medications. However, we have examined this research question in a national sample and this study addresses an important research question: whether there are racial and ethnic disparities in the use of new prescription medications even among prescription users. Additionally, members of racial and ethnic minority groups may be less likely than non-Hispanic whites to purchase prescription drugs in the first place. Therefore, based on these considerations, the findings from this study may understate the disparities. This study used drug approval dates in the criteria for new drugs as a proxy for marketing dates. Although marketing dates would be a more accurate measure, these were unavailable. Moreover, there has not been a unanimous definition of new prescription medication, but an acceptable way of defining them is the 5-year criterion that we used (Barents Group LLC 1999
; Express Scripts 2000
; Mullins et al. 2001
). One additional limitation lies in the measure of new medication use. If a patient was prescribed a new medication in December of a year, he or she would not have the same opportunity to refill the prescription as a patient received the prescription in January of the year. The fact that a patient could stay in the sample for 2 years might help to alleviate this problem.
The generalizability of this study is also limited by the inclusion of only new chemical entities. New chemical entities had been in the market for up to 5 years before the utilization. The study results do not generalize to generic drugs. However, racial disparities in the use of new medications were still significant when the number of other prescription medications was included in the model. This suggests that the racial disparities in the use of the new prescription medications may be even greater than the racial disparities in the use of older medications. Finally, differential patterns of new drug use were examined in this study but not the appropriateness of the patterns. However, disparities in the use of new drugs across racial groups are not reassuring since previous literature has reported the benefits of new drugs in general (Lichtenberg 2001