Abstract 704 Poster Session IV, Tuesday, 5/4 (poster 35)

Background: It has been shown that regionalization of health care services improves access and clinical outcomes while decreasing costs and hospital bed utilization. In spite of previous efforts to study the effects of regionalization, quantitative analysis has been, in large part, lacking.

Objectives: We propose a methodology to quantify regionalization of health care services. We have attempted to use this methodology to study the effects of insurance type on regionalization.

Methods and Results: Data on hospital discharges for 1995 and 1996 in California were obtained from the Office of Statewide Health Planning and Development database. Children (<18 years) who were hospitalized for aortic or pulmonary stenosis, chronic renal failure (defined by principal diagnostic code), or pyloromyotomy, closure of atrial septal defect, bone marrow transplant or liver transplant (defined by principal procedure code) were identified. A Concentration Index (CI) for each diagnosis/procedure was determined by calculating the Gini index derived from the Lorenz curve for the distribution of the diagnosis or procedure among hospitals. These data were used to construct a Regionalization Matrix, a scattergram for each diagnosis or procedure using the CI as the X-axis and Travel Distance (TD) as the Y-axis. We found that, as health care services become more specialized (increasing CI), TD increases (R=0.95 by second order curvilinear regression, p<0.001). We then compared regionalization in patients with different types of insurance by plotting each insurance type separately and using second order curvilinear regression to determine the goodness-of-fit for each subgroup. The correlation coefficient was largest for patients with managed care (HMO/PPO, R=0.94), smaller for Medicaid (R=0.77) and smallest for private insurance (R=0.66). Analysis of CI and TD for each subgroup indicated that the private insurance subgroup tends to travel farther and have a higher CI, while the Medicaid subgroup tends to travel less and have a lower CI.

Conclusions: Concentration Index and Travel Distance are highly correlated for pediatric health care services. This correlation is higher for patients with HMO/PPO when compared with patients having Medicaid or private insurance.

Speculation: We speculate that the Regionalization Matrix, that is the correlation between CI and TD, can be used to measure regionalization of health care services. If this speculation proves to be correct, then our data suggest that regionalization is more pronounced in the HMO/PPO subgroup and least pronounced among patients with private insurance. Further studies are required to substantiate this speculation and determine the applicability of this methodology to other areas of health services research.