Analysis of the Joint Distribution of Disproportionate Share Hospital Payments

5. Evaluating Current Distribution of DSH
Using General Measures of Financial Pressure and Vulnerability

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Contents

• General Measures of Financial Vulnerability
• Data.
• Methods
• Results
• Conclusions

Endnotes

In this chapter, we discuss general measures of financial viability that could be used to evaluate how well the DSH allocation policy targets financially vulnerable safety net hospitals. The measures that we evaluated are:

• FY 1998 total margin net of DSH payments;
• Three-year average total margin net of DSH payments (FY1997-1999);
• A three-year composite index of four financial indicators: total margin net of DSH payments, current ratio, cash flow to current debt, and asset turnover.

Measures related to the direct effect of serving low-income populations on a hospital's financial condition are addressed separately in Chapter 8. These measures include uncompensated care and revenue shortfalls from Medicaid and indigent care programs.

General Measures of Financial Vulnerability

A hospital's total revenue margin is the most commonly used measure of financial viability. This measure equals the difference between total net revenues and total expenses as a percentage of total net revenues and is the most direct indicator of whether the hospital is able to cover its overall expenses with its overall revenues. Since a critical question for targeting DSH payments is whether the hospital would be financially viable in the absence of those payments, the hospital's total margins net of DSH payments is a better measure of financial viability for purposes of identifying financially vulnerable safety net hospitals. Comparing total margin net of DSH to total margin including DSH subsidies under alternative DSH allocation methodologies provides an indication of how the hospital's financial viability would be affected assuming no behavioral changes occur in the services it provides or in the revenues it receives from Medicaid and other payers. One of the issues in interpreting the measure is the extent to which Medicaid DSH funds represent "new money" to the hospitals.

The literature suggests that margins alone- and a single year margin in particular- should not be used to assess hospital financial viability. Drawing on the studies discussed in Chapter 2, (AHA 1998; Bazzoli 1995; Prince 1998; Zeller 1997), we constructed a composite index that takes into account four financial indicators:

• Total margin net of Medicare DSH and the federal share of Medicaid DSH payments. This measure is defined as (net income - DSH)/net revenues.
• Current ratio. This measure (total assets/total liability) is a widely-used measure of liquidity.
• Cash flow to total debt. Cash flow is defined as net income plus depreciation. Cash flow as a percentage of total liabilities is used as a measure of capital structure to predict future financial problems (CHIPS 2000).
• Fixed asset turnover. This commonly used measure of operating efficiency is defined as the ratio of net patient revenues to fixed assets.

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Data

We calculated indicators of financial pressure for FY1997-FY1999 using the Medicare HCRIS public use files for PPS 13-16 as of June 30, 2001. The HCRIS cost report information is based on the hospital's fiscal year. For example, the PPS-13 files have cost report data for hospital cost reporting periods beginning on or after October 1, 1996 and before October 1, 1997 (i.e., cost reporting periods beginning in FY 1997). Table 1 summarizes the status of the cost reports we use in our analysis.

Methods

Since our information for Medicare and Medicaid expenditures is for FY1998, we developed the financial indicators on a federal fiscal year basis using the Medicare cost reports that overlap at least some portion of the three federal fiscal years we are interested in. In those cases where the hospital's fiscal year does not coincide with the federal fiscal year, we calculated

the indicators for the federal fiscal year as a weighted average of values in the two cost reporting periods with portions occurring in the federal fiscal year. We used the proportion of the federal fiscal year occurring in each of the two cost reporting periods as our weights. For example, for a hypothetical hospital with cost reporting period starting on July 1 and ending on June 30, the FY1997 values would be calculated as ¾ of PPS-13 value (which corresponds to the period from October 1, 1996 to June 30, 1997) and ¼ of PPS-14 value (which corresponds to the period from July 1 1997 to September 30 1997). All periods were measured in days.

In about five percent of the cost reports, the reporting period is less than one full year. For some of those hospitals, there is a break in continuous coverage. In such cases, we used the data that are available and prorated it to a full year. Where no cost reporting information was available for a particular provider for either cost reporting period overlapping the federal fiscal year, the hospital was considered as missing for that year.

The analysis file covers all acute care hospitals (and does not include hospitals that are exempt from the Medicare prospective payment system). Table 5.2 shows the number of hospitals for which data were available and the number remaining after eliminating those with incomplete data or outlier values.

Total Margins Net of DSH Payments

Our estimates of FY 1998 Medicare DSH payments relied on the PPS Impact file (which we used to estimate Medicare DSH payments in Chapter 4). For FY 1997 and FY 1999, we used the DSH payment amounts reported on the Medicare cost reports. Our estimate of actual FY 1998 Medicare DSH payments using the PPS impact files closely matches the reported amounts on the cost reports.⁽¹⁾

For the Medicaid component of DSH payments, we assumed that the "new" DSH or net gain to the hospital from DSH payments is the Federal share of total DSH payments reported by the State as being paid to the hospital. We have the FY 1998 reported amounts. We approximated payments for FY1997 and FY1999 based on the FY 1998 data. To do so, we applied state-level Medicaid DSH program growth rates in Federal DSH payments (FY1997/FY1998 and FY1998/FY1999) to the FY1998 data.

Total Margin Net of DSH 3-Year Index

We ranked all hospitals according to their three-year average total margin net of DSH payments. We used only one or two years if data for all years were not available in order to retain the maximum number of hospitals in the analysis file.

Composite Index

We constructed a composite index based on four indicators of financial vulnerability: total margin net of DSH payments, current ratio, cash flow to total debt, and fixed asset turnover. This index is an ordinal measure (shows only the order in a sequence) that ranks all hospitals in the sample according to the extent of their financial vulnerability. This rank is not an indicator of the absolute magnitude of hospitals' financial vulnerability.

We constructed the composite index both for 1998 and for three years overall. For 1998, we derived the index by averaging each hospital's rank according to each of the four indicators of financial vulnerability. For example, if a hospital ranks 10 for total margin (lower ranks always implying weaker positions), 200 for current ratio, 100 for cash flow to total debt, and 50 for fixed assets turnover, the composite rank would be (10+200+100+50)/4 = 90. We derived the final index (hospital ordering) by ranking these averages in the ascending order. For the overall 3-year index, one more step is added: a hospital's rank for each year for the same indicator is averaged before the same procedure is applied to the three-year averages.

Two important assumptions underlie the construction of this composite index. First, we assume all four indicators contribute equally to the overall financial health of hospitals (i.e., they have the same importance and thus are weighted equally). Second, we assume that each of the individual indicators conveys separate information that is not duplicative of the other indicators. The validity of these assumptions can be examined based on their substantive meaning for the hospitals, but the definitions of each indicator, as well as the statistical properties of the obtained series, do not appear to contradict these assumptions.

Technically, we calculated the composite index in three steps. First, we calculated the composite index for those hospitals for which all four indicators of financial pressure were available (96.5% of the hospitals that have any indicators calculated). Second, we excluded about one percent of the observations for having outlier values. The outlier cut-offs are:

• Total margin net of DSH payments: absolute value exceeds 70%;
• Current ratio: absolute value exceeds 12;
• Cash flow to total debt: absolute value exceeds 4;
• Fixed asset turnover: absolute value exceeds 18.

Third, we predicted values for the hospitals that had missing values for one or more of the indicators (3.5%) using a regression analysis model that used the available values of indicators for these hospitals as independent variables.

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Results

Table 5.3 summarizes the FY 1998 values for the financial indicators. Included is both a simple mean across all facilities and a discharge-weighted mean. For comparison purposes, we include the cut-off value for the 10th percentile of hospitals as well as the median value for hospitals with Standard and Poor bond ratings of BBB+/BBB/BBB-. The 10th percentile cut-offs are substantially below the median for the BBB rated hospitals. The latter are generally comparable to the median values for all hospitals.

Year-to-year stability of the indicators of financial vulnerability

We found that the indicators of financial vulnerability are fairly stable across the three fiscal years. We summarize in Table 5.4 the correlation across fiscal years for each of the indicators. The current ratio and fixed asset turnover rate are somewhat more stable than the margin and cash flow to debt ratio.

To further explore the cross-year dynamics, we also divided each series of indicators into 10 equal parts (deciles), following the ranking for that series from hospitals with the weakest values to hospitals with the strongest values for the indicator. Thus, the first deciles always contain hospitals with the weakest values for the indicator. We then constructed transition matrices for each year-to-year pair within the series. These matrices show in detail by deciles how the hospitals from the first year become redistributed in the second year. The decile redistributions mirror the statistical relationships described above, but provide more precise and detailed pictures of these relationships.

To illustrate, we show in Table 5.5 the matrix comparing hospital deciles for FY 1997 and FY 1998 for total margin net of DSH payments. Each row represents a decile (498 hospitals) of rankings in FY1997 while each column represents a decile (494 hospitals) of rankings in FY1998. Only 240 of the 498 hospitals (48%) that ranked in the first decile in FY1997 also ranked in the first decile in FY 1998. The percent of hospitals moving to the second and third deciles were 19% and 8 %, respectively. The remainder were either dispersed across the remaining deciles (12%) or were not reported in the FY 1998 data (13%). Of the 494 hospitals in the first decile in FY 1998, 16 % had been in the second decile in FY1997 and 12% had been in the third. Nine percent were not reported in the FY 1997 data. Thirty-nine percent of the hospitals that were reported in both years fell below the 50th percentile in both years (1904 out of 4855).

Consistency across the indicators for the same fiscal year

We report the Spearman rank correlations across the indicators for FY 1998 in Table 5.6. Total margin net of DSH is highly correlated with the cash flow to total debt indicator. Both measures are driven largely by net revenues. At the same time, the relationship between these two measures and the remaining two - current ratio and fixed asset turnover - is much weaker or nonexistent. This reflects the fact that balance sheet dynamics, especially the long-term one, may not necessarily coincide with the dynamics of current net revenues. Finally, current ratio and fixed asset turnover also appear to be independent of one another. In sum, the weak correlation between most of the financial indicators supports the theoretical understanding that each indicator provides a measure of a different domain of a hospital's financial viability (profitability, liquidity, capital structure, and asset efficiency) and should be thus considered jointly in evaluating a hospital's overall financial health. We are not concerned by the correlation between total margin net of DSH and total cash flow to debt since both reflect what we believe is the most important measure of financial viability: net income. Including both indicators is a way of giving greater weight to net income.

To further explore the cross-indicator dynamics among the indicators of financial vulnerability, we also divided each series into 10 equal parts (deciles), following the ranking for that series from hospitals with the weakest values of an indicator to hospitals with the strongest values of the indicator. We then constructed comparison matrices for each pair of indicators. To illustrate, we show in Table 5.7 the matrix comparing the FY 1998 deciles for total margin with total margin net of DSH. The results confirm that while the first and tenth deciles are relatively stable, a number of hospitals move into a different decile when the total margin is adjusted for DSH payments. Twenty-two percent of the hospitals in the first decile for total margin move to the second decile of the total margin net of DSH ranking. About 90 percent of the hospitals (2215 of 2470) in the 50th percentile or lower on the total margin ranking are also in the 50th percentile or lower on the total margin net of DSH ranking.

Summary by Classes of Hospitals

Table 5.8 summarizes the main financial indicators by low-income patient utilization and three categories of hospitals based on the decile rankings for: FY 1998 total margins net of DSH, the three-year average of total margins net of DSH, and the 3-year average composite index. (See Appendix C for summaries of the financial indicators by other hospital classes). Columns 3 and 4 report the discharge- weighted means for FY 1998 total margin and total margin net of DSH payments, respectively. For hospital classes with positive margins, the differences in total margins and total margins net of DSH are slight compared to the differences for hospitals with negative margins. For example, for hospitals with total margins net of DSH between -10% and -20%, the average total margin (net of DSH) increases from -14.0% to -7.0 % when DSH payments are taken into account.

Column 5 reports the 3-year average (discharge-weighted) ranking for each hospital class based on margins net of DSH payments. The average discharge-weighted ranking is in the 54.8 percentile of hospitals. Column 6 shows the discharge-weighted average rankings for FY 1998 total margins net of DSH. The average rankings for each hospital class for FY 1998 are very similar to the rankings for a three-year average. Column 7 reports the weighted average rankings based on the three-year composite index are reported in Column 7.

Across the various utilization measures for low-income populations, the financial indicator rankings of the hospitals serving a higher proportion of low-income patients are lower than those of hospitals serving a relatively low proportion of low-income patients. However, the changes in rankings as the proportion of low-income patients increases are not consistently monotonic. For example, rankings based on total margins net of DSH are lower for hospitals with a low-income patient ratio between .40 and .60 than for hospitals with low- income patient ratios between .60 and .80. ⁽²⁾ Our decision to remove only the federal share of Medicaid DSH in computing the margin may contribute to this result.

The relationship between Medicaid utilization and margins is evident in the lower rankings for hospitals with higher Medicaid utilization (and may be indicative of Medicaid shortfalls and uncompensated care). The discharge-weighted average ranking for hospitals one standard deviation above the mean Medicaid utilization for the state is 38.0% compared to 58.1% for those within one standard deviation from the mean. Overall, the difference in rankings across low-income patient categories is greater using total margins net of DSH than the composite index. For example, the mean composite index ranking for hospitals one standard deviation above the mean Medicaid utilization rate is 41.7% compared to 52.6 % for those within one standard deviation from the mean.

Columns 8-11 report the distribution of FY1998 Medicare and Medicaid (federal share only) DSH funds. Key findings include the following:

• Except for the 32 hospitals with lowest margins (-50 to -70 percent), the average FY 1998 DSH payment per discharge increases as the total margin net of DSH decreases.
• Across the total margin net of DSH deciles, the average FY 1998 DSH payment to the hospitals in Decile 1 is nearly twice the average payment to the hospitals in the Decile 2. Using the deciles for the 3-year average net of DSH payments, the average per discharge DSH payment in Decile 1 is $1,378 compared to $701 in Decile 2. The concentration of DSH payments in Decile 1 is attributable to Medicaid payments. The average payment per discharge decreases with each decile through the eighth decile. The average DSH payment per discharge for hospitals in Deciles 9-10 is slightly larger than the payment to hospitals in Deciles 6-7.
• Medicaid DSH payments are more concentrated than Medicare payments in the hospitals in the lower margin deciles. Using the 3-year average margin deciles, 61 percent of Medicare DSH and 82% of Medicaid DSH payments are concentrated in the hospitals in Deciles 1-5. Thirty-five percent of Medicaid DSH payments go to hospitals in Decile 1 compared to 12% of Medicare DSH payments.
• While the average DSH payment per discharge declines as the composite index decile increases, the differences in payments across these deciles are not as great as those for the total margin deciles. The overall concentration of DSH payments in Deciles 1-5 is similar to the finding with respect to the total margin deciles (60% of Medicare DSH and 82% of Medicaid DSH). However, only 13.1% of Medicaid DSH payments go to hospitals in Decile 1 of the composite index.

Table 5.9 summarizes the financial indicators by state using the same columns as Table 5.8.

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Conclusions

The comparison of the measures for total margin and total margin net of DSH payments shows that while there is an overall correlation between the measures, the choice of measure has implications for individual hospitals, particularly those with the lowest margin levels. We believe total margin net of DSH payments is most consistent measure for evaluating how well DSH payments are targeted toward financially vulnerable safety net hospitals.

The composite measure identifies a somewhat different set of hospitals as financially vulnerable. The relationship between serving low-income patients and performance on this measure is not as strong as the relationship between low-income patients and total margins net of DSH. Similarly, the relationship between the composite index and current DSH funding is not as strong. This may be attributable in part to our choice of measures and the equal weighting given each measure. While we include the composite index rankings as a hospital class variable, we believe total margin net of DSH payments should be given more weight as an evaluation tool since, of the financial indicators we examined, it is most directly related to the impact of providing uncompensated care.

The individual measures of financial viability are relative stable from year to year. In particular, the consistency of the 1-year and 3-year total margin figures suggests that only one of the measures is needed in the analysis of alternative allocation methodologies. The three-year measure has the advantage of allowing us to include some hospitals for which we are missing FY 1998 margin data and of smoothing out some year-to-year differences for some hospitals. These advantages are most important if margins are taken into account in the allocation formula (rather than being used solely as an evaluation tool). There are, however, disadvantages to using the 3-year average. The first is the need to impute the FY 1997 and FY 1999 DSH payments in determining total payments net of DSH payments. The second is the partial completeness of the FY1999 cost report files and their "as filed" status. We are missing about 20 percent of the cost reports beginning in FY 1999. Given the funding reductions in the Balanced Budget Act of 1997, the use of a two-year average for some hospitals and a three-year average for others could bias the results. Using the FY1998 margins also simplifies our analysis of alternative allocation policies for FY 1998 DSH funds. Therefore, we use only the FY 1998 margins net of DSH funds in our simulations in Chapters 7 and 8.

Endnotes

1.  The correlation coefficient between the two series is equal to 0.95, there is less than 0.5% difference in total DSH payments, and the mean and standard deviation values are similar (0.5% and 1% difference, correspondingly).

2.  The low-income patient ratio for this analysis is defined as the percentage of inpatient days attributable to Medicare SSI and Medicaid (non-Medicare) patients.

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