Volume 49 | Number S2 | December 2014

Abstract List

Laura R. Wherry Ph.D., Marguerite E. Burns Ph.D., Lindsey Jeanne Leininger Ph.D.


To assess the ability of different self‐reported health () measures to prospectively identify individuals with high future health care needs among adults eligible for Medicaid.

Data Sources

The 1997–2008 rounds of the National Health Interview Survey linked to the 1998–2009 rounds of the Medical Expenditure Panel Survey ( = 6,725).

Study Design

Multivariate logistic regression models are fitted for the following outcomes: having an inpatient visit; membership in the top decile of emergency room utilization; and membership in the top cost decile. We examine the incremental predictive ability of six different domains (health conditions, mental health, access to care, health behaviors, health‐related quality of life [], and prior utilization) over a baseline model with sociodemographic characteristics. Models are evaluated using the ‐statistic, integrated discrimination improvement, sensitivity, specificity, and predictive values.

Principal Findings

Self‐reports of prior utilization provide the greatest predictive improvement, followed by information on health conditions and . Models including these three domains meet the standard threshold of acceptability (statistics range from 0.703 to 0.751).


measures provide a promising way to prospectively profile Medicaid‐eligible adults by likely health care needs.