Inpatient hospital service utilization of the uninsured in Nebraska: policy implications for addressing uncompensated care.
In order better to inform policymakers about financing uncompensated hospital care through appropriate allocation of resources among Nebraska communities, this study used seven years (1996-2002) of county-level data from multiple sources to examine the relationship between population economic factors and the hospital inpatient care use by uninsured patients. The generalized estimating equation (GEE) regression analysis showed that, at the county level, the population uninsurance rate and other economic factors (e.g., per capita income, the percentage of population receiving welfare) are statistically significant predictors of average hospital self-pay inpatient charge per resident. Residents in the three western regions of the state also incurred statistically higher per-resident hospital self-pay inpatient charges than did their counterparts in the three eastern regions. State policymakers in Nebraska can use our study results to allocate resources on the basis of community economic characteristics and geographic location, to help reduce the financial burden of caring for the uninsured to safety net hospitals. The study may have a wide application to other states examining the same policy issues. The model used in this study can be easily created for other states, as the required data are readily available.
Chen
Li-Wu
LW
Department of Health Services Research and Administration, College of Public Health, University of Nebraska Medical Center, 984350 Nebraska Medical Center, Omaha, NE 68198-4350, USA. liwuchen@unmc.edu
Shambaugh-Miller
Michael D
MD
Meza
Jane L
JL
Zhang
Wanqing
W
Shaw
Kelly L
KL
Mueller
Keith J
KJ
D006761:Hospitals / Q000706:statistics & numerical data*; D006801:Humans; D007297:Inpatients / Q000706:statistics & numerical data; D017057:Medically Uninsured / Q000706:statistics & numerical data; D008962:Models, Theoretical; D009329:Nebraska; D011050:Policy Making; D011159:Population Surveillance / Q000379:methods; D012044:Regression Analysis; D017664:Uncompensated Care