We explored various approaches to classifying diagnoses within the Medicaid population. Our goal was to identify an algorithm that would classify the types of diagnoses found within the foster care population and then allow us to compare the distributions of diagnoses to those found in the general Medicaid population. Specifically, we wanted to be able to differentiate between physical and mental conditions. If possible, we also wanted to distinguish the level of severity within diagnostic groups. We explored approaches developed by Kronick et al. (2000), Burwell et al. (1997), and Perrin et al. (1999), as well as the crosswalk used by the Social Security Administration (SSA 1998).
We selected the Chronic Illness and Disability Payment System (CDPS), because it not only identifies severe and chronic conditions among children but also differentiates according to the severity or complexity of the case within a given diagnostic category (Kronick et al. 2000). Specifically, the CDPS identifies 20 diagnostic categories and identifies gradients of high-, medium- and low-cost subcategories within each.(6)
For our purposes, the approach by Burwell et al. (1997) was more limited because it did not define specific diagnostic groups (beyond physical and mental conditions in the aggregate) and did not allow for differentiation of severity within the broad categories. Nor did the crosswalk by Perrin et al. (1999) allow for as fine a breakdown of diagnostic groups. Although the SSA crosswalk contains a wide range of diagnostic codes to classify those receiving SSI benefits into broad diagnostic categories, it is not appropriate for identifying chronic or disabling conditions within the general population.
Outpatient diagnostic data were only available for two of the three states; Florida did not report diagnostic information on its outpatient SMRF files. Therefore, the diagnostic comparisons were performed only for California and Pennsylvania.
In addition to examining chronic illness and disability among low-income children, we also compared the prevalence of deliveries across each of the Medicaid eligibility categories. We developed a measure of the number of girls, ages 15 to 17, who delivered a baby in 1994. We used the SMRF delivery indicator, which was based on ICD-9-CM codes signifying a live birth.(7) Age was measured as of the end of the year (December 31, 1994). We restricted the measure to include only girls ages 15-17, to compare these rates with national benchmarks from vital statistics (Ventura et al. 1996).