Analysis of the Joint Distribution of Disproportionate Share Hospital Payments. Correlation Analysis

09/01/2002

We examined the relationship between selected measures of serving low-income patients using 614 hospitals in the three-state analysis file (Table 8.13). We found that the correlation between the ratio of financial risk to operating costs and financial risk per day was .675. It suggests that using an allocation policy using the ratio of financial risk to operating costs could result in a considerably different DSH distribution than a policy that uses financial risk per day or another direct measure of the hospital's financial risk in the allocation policy. The correlation between financial risk as a percent of operating expenses and the percentage of low-income revenues (Medicare SSI, Medicaid, local indigent care programs, uncompensated care and bad debt) was .591. The correlation between the financial risk ratio and other measures of low-income patient services were slightly lower. The percentage of revenues was slightly more correlated with the financial risk ratio than the percentage of inpatient days and the measures that included Medicare SSI patients were also slightly more correlated than the measures that excluded these patients. Between the low-income patient utilization and revenue measures, the correlation was moderately high. For example, the correlation between % low-income days and % low-income revenues was .811 for all patients and .803 for non-Medicare patients only.

Next, we examined the relationship between the percentage of self-pay and no-charge patients and the percentage of operating expenses attributable to uncompensated care and bad debt. The issue is whether a hospital's proportion of self-pay and no-charge patients using claims data is a good proxy for its uncompensated care and bad debt costs. We found that the two measures were poorly correlated (.106). Further investigation is needed to understand why a correlation was not found.

 

Table 8.13
Selected Measures of Serving Low-Income Patients:
Hospital-Weighted Means and Correlation Between Measures Using 3-State Analysis File
  Ratio of FR to Operating Expenses FR Per Day % Low-income days % Low-income revenue % Non-Medicare low-income days % Non-Medicare low-income revenue
MEAN 0.077 96..349 0.256 0.246 0.210 0.212
STD 0.071 145.119 0.184 0.178 0.169 0.166
N hospitals 614 614 614 614 614 614
Pearson's Correlation Coefficient*
Ratio of FR to Operating Expenses 1.000 0.675 0.567 0.591 0.560 0.579
Financial Risk Per Day 1.000 0.447 0.396 0.453 0.383
% Low-income days 1.000 0.826 0.979 0.786
% Low-income revenue 1.000 0.811 0.984
% Non-Medicare low-income days 1.000 0.803
% Non-Medicare low-income revenue 1.000

* All values p<.0001


Finally, we examined for safety net hospitals the relationship between DSH allocations, financial risk and the hospital's net income (Table 8.14). We expected to find a negative correlation between the hospital's net income and its financial risk; that is, hospitals with high financial risk have more difficulty generating revenues to cover their expenses. The correlation was moderate (-0.57).

  • The correlation between joint DSH funds under current policies and financial risk was .74. Interestingly, the correlation between the joint Medicare and Medicaid current policy DSH funds and the two financial risk measures was higher than either the new Medicaid DSH or Medicare DSH policies separately. The correlation between financial risk and Simulations A and B was similar to the joint distribution.
  • The correlation between joint DSH funds and net income is -0.52. The correlation was the same for Medicaid "new" DSH and lower for Medicare DSH (-.41). None of the DSH alternatives are as strongly correlated with net income as joint DSH funds. The highest correlations are with Simulations C and D, which use financial risk as an allocation statistic.
  • There is a strong correlation between Simulation C and financial risk (.882). This means that the use of the indirect measure of financial risk (ratio of financial risk to operating expenses X wage index X adjusted patient days) works fairly well for safety net hospitals.
  • The correlations between the allocation factors used in Simulations A (utilization) and B (revenues) is very high (.96).
Table 8.14
Safety Net Hospitals
Correlation Between Financial Status Measures and Alternative DSH Allocation Polices
  Income net DSH
($ mill)
Financial risk
($ mill)
Joint DSH funds
($ mill)
Medicaid New DSH
($ mill)
Medicare DSH
($ mill)
Sim A
($ mill)
Sim B
($ mill)
Sim C
($ mill)
Sim D
($ mill)
MEAN -8.351 12.025 8.568 4.752 3.816 8.917 8.349 8.265 8.436
STD 26.222 19.924 16.025 13.784 4.902 17.778 18.361 15.532 19.732
N 307 307 307 307 307 307 307 307 307
Pearson's Correlation Coefficient*
Income net DSH 1.00 -0.57 -0.52 -0.41 -0.52 -0.24 -0.29 -0.44 -0.40
Financial risk 1.00 0.74 0.64 0.63 0.73 0.73 0.83 0.79
Joint DSH funds   1.00 0.96 0.58 0.80 0.81 0.78 0.76
New Medicaid funds     1.00 0.31 0.79 0.81 0.77 0.77
Current law Medicare funds     1.00 0.40 0.35 0.40 0.29
Sim A: % Non-Medicare low-income days w/WI   1.00 0.96 0.81 0.77
Sim B: % Low-income revenues     1.00 0.85 0.83
Sim C: Financial risk     1.00 0.98
Sim D : Sliding scale based on financial risk         1.00

* All values p<.0001

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