Variation in types of service use and expenditures for individuals with developmental disabilities.
BACKGROUND
this study examined the types of services and expenditures for 8 service categories provided by regional centers to 138,336 individuals with developmental disabilities living at home and in the community in California in 2004-2005.


METHODS
logistic regressions of secondary data were used to predict the types of services received, and ordinary least squares regressions were used to predict types of service expenditures.


RESULTS
higher client needs generally were associated with higher odds of receiving services and with expenditures, although the types of services varied by client need. Controlling for client needs and other factors, males were more likely to receive out-of-home services. Individuals aged 3-21 years were generally less likely to receive many services but were more likely to receive in-home and out-of-home respite services than were those over age 62. All racial and ethnic minority groups were less likely to receive support and out-of-home services than were whites and had lower expenditures, although these varied by the types of services. The supply of nursing homes, community care facilities, area population characteristics, and regional centers also predicted variations in service use and expenditure patterns.


CONCLUSIONS
studies of the underlying reasons for the variations are needed to ensure equity in access to all types of services and expenditures.
Department of Social and Behavioral Sciences, University of California, San Francisco, San Francisco, CA 94143-0612, USA.
Taewoon
T
Kang
Charlene
C
Harrington
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002140:California; D002648:Child; D002675:Child, Preschool; D003153:Community Health Services / Q000191:economics* / Q000706:statistics & numerical data; D016001:Confidence Intervals; D002658:Developmental Disabilities / Q000191:economics* / Q000453:epidemiology; D005006:Ethnicity / Q000706:statistics & numerical data; D005260:Female; D005102:Health Expenditures / Q000706:statistics & numerical data*; D006296:Health Services / Q000191:economics / Q000706:statistics & numerical data; D054624:Health Status Disparities; D006801:Humans; D016015:Logistic Models; D008297:Male; D006278:Medicare / Q000191:economics / Q000706:statistics & numerical data; D008875:Middle Aged; D016017:Odds Ratio; D012737:Sex Factors; D014481:United States; D055815:Young Adult