Differences between symptom-specific and general survey questions of unmet need in measuring insurance and racial/ethnic disparities in access to care.
OBJECTIVE
To examine differences in insurance and racial/ethnic disparities in access to care between a single-item measure of general unmet medical need and a multi-item measure of symptom-specific unmet medical need.


METHODS
The 2003 Community Tracking Study Household Survey, which included both a single question about any unmet medical needs over the last year, and a measure of unmet medical need keyed to the recent occurrence of 1 of 15 symptoms that a panel of physicians considered serious enough to warrant seeking medical care.


METHODS
We constructed 3 measures of unmet need (general perceived unmet need, perceived unmet need for a specific new symptom, and actual unmet need for the new symptom). We used multivariate logistic regression analysis to determine whether the measures have similar implications for access disparities by insurance status and by race/ethnicity, while controlling for income, health, and other sociodemographic characteristics.


RESULTS
Uninsured people are consistently more likely than privately insured people to have unmet medical needs across the 3 measures of unmet need, and these differences were not due to differences in the perceived need for care. However, racial/ethnic disparities were apparent only for the symptom-specific measures of unmet need, and not the general measure of unmet need.


CONCLUSIONS
Using a symptom-specific measure of unmet medical need is probably not worth the added survey complexity and cost if the primary objective is to measure access disparities by insurance coverage. However, a general measure of unmet medical needs may not adequately capture racial/ethnic disparities in access.
Cunningham
Peter J
PJ
Center for Studying Health System Change, Washington, DC 20024, USA. pcunningham@hschange.org
Hadley
Jack
J
D000328:Adult; D000368:Aged; D005006:Ethnicity / Q000706:statistics & numerical data*; D005260:Female; D006297:Health Services Accessibility / Q000706:statistics & numerical data*; D006301:Health Services Needs and Demand / Q000706:statistics & numerical data*; D006801:Humans; D019458:Insurance Coverage / Q000706:statistics & numerical data*; D007348:Insurance, Health / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D012959:Socioeconomic Factors; D014481:United States / Q000453:epidemiology