RECOMMENDATIONS

Supplemental Studies

The below studies have been completed in response to panel questions about the use of various measures in a SON Index. Please click on the report titles below to access the full report.

The Feasibility and Impact of Adjusting Ryan White Program, Part A Services to Account for Variations in Medicare and Medicaid Enrollment, 2006.

This report, prepared by the Contractor Team (RTI), examined the extent to which Ryan White clients in Part A areas are getting care needs met by Medicaid and/or Medicare, thus reducing their need for Ryan White resources. A number of federal data sets were used to determine the number of HIV/AIDS cases, those getting Medicaid and/or Medicare, the services they were getting, and what Ryan White was providing. Among the findings: an estimated 25% of all patients with HIV/AIDS who reside in Part A areas were getting some form of Medicare or Medicaid insurance. Adjusting for program adequacy, state contributions, and Ryan White Program resource requirements, federal Medicare and Medicaid programs paid for an estimated 7.9% of the Part A resource needs that would otherwise need to be provided through the Ryan White Program. The study concluded that a severe need index could account for these federal sources of care and adjust Ryan White funding from more generous to less generous states—without penalizing states that make additional contributions with state funds.

Should Patient Characteristics Be Included in a Severity of Need Index for Ryan White Program, Part A Services? An Evaluation Based on the Medical Expenditure Panel Survey.

This 2007 evaluation investigated the impact of various patient characteristics, such as demographics and exposure category, on severe need—specifically in terms of cost. The five variables examined included: patient age, gender, race/ethnicity, HIV or AIDS current status designation, and injection drug use exposure category (the latter was measured using the proxy measure of a viral hepatitis diagnostic code). No significant association was found between any of these variables and outpatient costs, leading the study to conclude that findings did not support inclusion of patient characteristics in a SON Index for nonprescription services (the impact on prescription drug consumption was not tested in this study).

The study also concluded that additional research should examine the role of injection drug use exposure on demand for services because the study imprecisely measured this variable through use of the above-referenced proxy measure. A final conclusion: policy makers should revisit these issues in the future to account for potential changes in the utilization of health services and to incorporate newer sources of data.