Prospective payment for Medicare inpatient psychiatric care: assessing the alternatives

Health Care Financing Review, Fall, 2004 by Philip G. Cotterill, Frederick G. Thomas

These relationships are evident in Table 4. Under Model 1, public hospitals have per case payments that average only 72 percent of their average per case cost. This result is consistent with the relatively high per case cost and long LOS of public hospitals shown in Table 1. Similarly, the largest CPUs and hospitals tend to be underpaid relative to cost with ratios of 0.81 and 0.83, respectively. For Model 2, the results are dramatically reversed. Public hospitals (relatively low per diem cost) have average per case payments that exceed their average per case cost by 44 percent. However, the per diem cost of public hospitals could be understated due to their frequently limited cost accounting systems and intergovernmental transfers. Also, large facilities (both hospitals and CPUs) have payment to cost ratios substantially greater than 1.0. Conversely, it is the relatively high per diem cost very small facilities and rural facilities whose average payments are less than average cost.

Model 2 Versus Model 3

The comparison of Models 2 and 3 shows the effects of additional per diem rate adjustors for a patient's age, DRG, comorbidifies, LOS, and the level of a facility's teaching activity and rural/urban location. These variables increase the slope coefficient from 0.63 to 0.70, which can be interpreted as a 10-percent reduction in the systematic bias of Model 2. That is, under Model 3, there are reductions in the overpayment of low per case payment facilities and underpayment of high per case payment facilities. The payment to cost ratios tell a similar story. The Model 2 ratios that are well above 1.0 are reduced in Model 3, and the Model 2 ratios that are below 1.0 increase in Model 3. The effect of the specific adjustment for rural facilities in Model 3 raises their payment to cost ratio from 0.83 to 0.94. Also, Model 3 raises the payment to cost ratio for the smallest group of CPUs (0.76 in Model 2 and 0.81 in Model 3).

The precision of the per diem model increases, as the [R.sup.2] rises from 0.59 to 0.64, a 9-percent increase. Although these gains are not trivial, clearly there remains room for further improvement.

Model 3 Versus Model 4

Model 3 reflects the use of most variables available in current administrative data that were found to be statistically important in explaining per diem cost variation and that generally have been judged acceptable for use in PPS. Model 4 contains payment adjustors for the size (as measured by average daily census) and the occupancy rate of the psychiatric facility--adjustments with potentially negative effects on efficiency. For example, smaller facilities that may be unable to take advantage of economies of scale would receive higher per diem payments than larger facilities, and low occupancy facilities that use their available resources less efficiently would receive higher per diem payments than high occupancy facilities. Nevertheless, Table 3 shows that Model 4 substantially improves both the bias and precision of the per diem payment system. The slope coefficient rises to 0.99, a 32-percent improvement over Model 3. The [R.sup.2] increases to 0.80, compared with Model 3's [R.sup.2] of 0.64. The payment-to-cost ratios of Model 4 generally improve compared with those of Model 3. However, there are a few cases where the changes overcompensate. For example, in Table 4, the Model 3 ratio for the largest group of CPUs is 1.16, and under Model 4, it falls to 0.88.