Culture and ethnicity have been suggested to influence the presentation of patients with schizophrenia. These factors are thought to affect the diagnoses, courses of treatment, and medical utilization patterns of patients with schizophrenia. Specifically, the differences between whites, African Americans, and Mexican Americans are of particular importance, as these groups comprise the majority of the population in the United States today. The traditional course of treatment for many patients with schizophrenia is the drug haloperidol. However, research has shown that some ethnic groups (African Americans and Mexican Americans) may respond better to atypical drugs, such as olanzapine, but may be less likely to receive these drugs. A better response to the course of treatment results in improved medical utilization patterns. The purpose of this study was to examine if ethnicity helped predict whether Texas Medicaid patients were prescribed haloperidol versus olanzapine when other factors were controlled for.
The study population consisted of 726 patients whose index drug was haloperidol and 1875 patients whose index drug was olanzapine. Patients had an ICD-9-CM diagnosis of schizophrenia or schizoaffective disorder. Texas medical and prescription claims data were used in a logistic regression analysis to determine significant predictors of the type of antipsychotic (haloperidol vs. olanzapine) patients were prescribed. Variables included in the analysis were ethnicity, gender, age, region, other mental illness comorbidities, and previous utilization of medications and resources. Data were collected from Jan. 1, 1996, to Aug. 31, 1998.
The results show that when other demographic and utilization factors were controlled for, African Americans were less likely than whites to receive olanzapine rather than haloperidol.
Ethnicity is a significant predictor of the type of antipsychotic that is prescribed.
"Successfully meeting this goal requires work at the state level particularly focused on individuals enrolled in public health programs such as Medicaid given that such programs provide services to a disproportionate share of minority populations in the United States (Centers for Medicare and Medicaid Services (CMS) 2000). Largely based on administrative claims data, academic researchers have recently documented important race disparities among Medicaid enrollees in a host of areas including the general use of health care services (Tai- Seale, Freund, and LoSasso 2001), behavioral health care (Opolka et al. 2003), and dental care (Dasanayake et al. 2002) as well as the treatment of AIDS (Kahn et al. 2002), cardiovascular disease (Litaker and Koroukian 2004), and diabetes (Shaya et al. 2005). Interpretation of these findings as well as the ability of states to both monitor and eliminate racial and ethnic disparities in the care provided by these programs rests heavily upon the collection of valid race and ethnicity information. "
[Show abstract][Hide abstract] ABSTRACT: This paper measures agreement between survey and administrative measures of race/ethnicity for Medicaid enrollees. Level of agreement and the demographic and health-related characteristics associated with misclassification on the administrative measure are examined.
Minnesota Medicaid enrollee files matched to self-report information from a telephone/mail survey of 4,902 enrollees conducted in 2003.
Measures of agreement between the two measures of race/ethnicity are computed. Using logistic regression, we also assess whether misclassification of race/ethnicity on administrative files is associated with demographic factors, health status, health care utilization, or ratings of quality of health care.
Race/ethnicity fields from administrative Medicaid files were extracted and merged with self-report data.
The administrative data correctly classified 94 percent of cases on race/ethnicity. Persons who self-identified as Hispanic and those whose home language was English had the greater odds (compared with persons who self-identified as white and those whose home language was not English) of being misclassified in administrative data. Persons classified as unknown/other on administrative data were more likely to self-identify as white.
In this case study in Minnesota, researchers can be reasonably confident that the racial designations on Medicaid administrative data comport with how enrollees self-identify. Moreover, misclassification is not associated with common measures of health status, utilization, and ratings of quality of care. Further replication is recommended given variation in how race information is collected and coded by Medicaid agencies in different states.
Health Services Research 01/2008; 42(6 Pt 2):2373-88. DOI:10.1111/j.1475-6773.2007.00771.x · 2.78 Impact Factor
"One issue that has not been systematically addressed in genetic linkage studies of schizophrenia is the possibility of genetic heterogeneity due to racial differences, which would be consistent with racial differences in prevalence, clinical features, and treatment response that have been reported [Opolka et al., 2003; Barrio et al., 2003a,b]. Because gene frequencies vary among racial groups, some functional polymorphisms may be more predominant in one group than another. "
[Show abstract][Hide abstract] ABSTRACT: Genome-wide linkage analyses of schizophrenia have identified several regions that may harbor schizophrenia susceptibility genes but, given the complex etiology of the disorder, it is unlikely that all susceptibility regions have been detected. We report results from a genome scan of 166 schizophrenia families collected through the Department of Veterans Affairs Cooperative Studies Program. Our definition of affection status included schizophrenia and schizoaffective disorder, depressed type and we defined families as European American (EA) and African American (AA) based on the probands' and parents' races based on data collected by interviewing the probands. We also assessed evidence for racial heterogeneity in the regions most suggestive of linkage. The maximum LOD score across the genome was 2.96 for chromosome 18, at 0.5 cM in the combined race sample. Both racial groups showed LOD scores greater than 1.0 for chromosome 18. The empirical P-value associated with that LOD score is 0.04 assuming a single genome scan for the combined sample with race narrowly defined, and 0.06 for the combined sample allowing for broad and narrow definitions of race. The empirical P-value of observing a LOD score as large as 2.96 in the combined sample, and of at least 1.0 in each racial group, allowing for narrow and broad racial definitions, is 0.04. Evidence for the second and third largest linkage signals come solely from the AA sample on chromosomes 6 (LOD = 2.11 at 33.2 cM) and 14 (LOD = 2.13 at 51.0). The linkage evidence differed between the AA and EA samples (chromosome 6 P-value = 0.007 and chromosome 14 P-value = 0.004).
American Journal of Medical Genetics Part B Neuropsychiatric Genetics 11/2005; 139B(1):91-100. DOI:10.1002/ajmg.b.30213 · 3.42 Impact Factor
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.