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This project included several inter-related tasks:
Overall, we found that despite the known issues with the current Medicare and Medicaid DSH policies, the current distribution targets financially vulnerable safety net hospitals at least as well as the alternatives that we examined. The multiple Medicare formula and the flexibility of the Medicaid program may allow for better targeting than a single formula-driven allocation policy. Nevertheless, it is clear that there is room for improvement in the current policies and that further study is warranted. In particular, a multi-variate analysis of the factors affecting financial risk and financial viability is needed. Ideally, the analysis would involve a national database with information on each's hospitals uncompensated care and shortfalls from Medicaid and local indigent care programs. Given the diversity of Medicaid DSH program, a national database is needed to fully understand the potential impact of alternative allocation policies at both the national and market levels.
Medicare DSH Payments. We estimate Medicare FY 1998 actual DSH payments at $4.83 billion. If the FY2003 DSH payment rules had been in effect and all other FY1998 payment parameters remained unchanged, payments would have been $358 million higher, or $5.18 billion. Consistent with the changes in the formula, most payment increases occurred among rural hospitals and small urban hospitals. Although rural hospitals provided 19% of total Medicare inpatient days, they received only 3.1% of the Medicare DSH payments. Under BIPA, the rural share of DSH payments will more than double to 7.2%.
Medicaid DSH Payments. Nationally, we found that the states reported $15 billion in DSH payments to hospitals, with about 23% of this amount paid to institutes for mental disease. The states with the largest DSH programs are California, New York, New Jersey, and Texas. Utilizing the estimates made by Coughlin et al. for FY 1997, we estimate that 11 states retained DSH funds: California, Connecticut, Georgia, Indiana, Kentucky, Massachusetts, Mississippi, Missouri, North Carolina, Rhode Island, and Texas. The amounts retained by the 11 states represented 15% of federal DSH payments. If we assume that only the federal share of DSH payments represents new money to facilities, "new" DSH funds would total $8.3 billion.
Five states together receive almost half of the total amount of DSH funds: California (16.7%), New York (12.7%), Texas (9.3%), New Jersey (5.7%), and Louisiana (4.3%). At the same time, these states have only 28% of the total adjusted patient days (7.9, 9.7, 5.8, 2.7, and 1.9 %, respectively).
For the acute care hospitals in our analysis file, DSH payments based on actual Medicare FY 1998 payments and the federal share of DSH payments totaled $9.3 billion.
We explored several types of criteria that could be used to identify safety net hospitals, including inpatient claims-based measures and measures derived from hospital financial data. Our analysis of both the HCUP and three-state data suggest that the definition of the patient population (e.g., with or without Medicare SSI beneficiaries) that is to be considered in the DSH allocation statistic is more important than how the care provided to those patients is quantified. Generally, the measures that included Medicare SSI beneficiaries along with all other low-income patients generally performed better than those that did not in targeting financially vulnerable hospitals. If an "all low-income" patient measure is not administratively feasible, using Medicaid patients only is preferable to Medicare SSI and Medicaid days or the Medicare DSH patient percentage, both of which are less correlated with low-income patients.
The different measures quantifying the amount of inpatient care provided to a low-income population (days, discharges, or charges) are highly correlated. However, the choice could have implications for certain hospitals. Those which have a high volume of Medicaid maternity cases or shorter than average length of stay (e.g. California hospitals) would benefit if discharges were used instead of days as the measure of the proportion of care provided to low-income patients. The Medicare case mix index is not a good proxy for the hospital's low-income patient case mix. In the absence of data on the case mix of low-income patients, days or charges should be used instead of discharges as the allocation statistic.
From the financial data for the three states we were able to compare how a revenue statistic that includes both inpatient and outpatient care compares to one that includes inpatient care only. The correlation between low-income days and low-income revenues indicates the choice of measure could have significant implications for some hospitals. The measure of the proportion of a hospital's gross revenues that is attributable to low-income patients was slightly more highly correlated with the hospital's ratio of financial risk to operating expenses than the other utilization measures. It is not clear from the correlation results that including all care significantly improves the targeting of DSH funds to financially vulnerable safety net hospitals. Also, the inclusion of outpatient care raises issues regarding subsidies to other ambulatory care providers. The role that non-hospital ambulatory care providers play in the safety net for low-income populations is discussed in Appendix E. A policy that concentrates federal support for uncompensated care solely on hospitals may serve to discourage community providers from furnishing substantial amounts of care to indigent populations. It may also have implications for the relative generosity of Medicaid payments for services provided in hospital outpatient departments and clinics and in physician offices. This is an area that warrants further investigation.
We developed two types of measures of financial vulnerability. We defined the first measure as the hospital's financial risk associated with serving low-income patients. Developed from hospital financial data for the three states, a hospital's financial risk was computed as the sum of Medicaid and local indigent care shortfalls and uncompensated care (including bad debt). For evaluation purposes, we also developed three measures of financial viability from financial data available on the Medicare cost report:
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. We found that 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.
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. We used the FY1998 margins to simply our analysis of alternative allocation policies for FY 1998 DSH funds. In some analyses, we used related measures such as the ratio of revenues to expenses and income net of DSH payments.
Neither the current DSH allocation policies nor the alternatives that we examined in the analysis target DSH payments in a way that is strongly correlated with net income. This is an issue that warrants further investigation and understanding. The different Medicare formulae and the Medicaid DSH program's flexibility may provide mechanisms to target financially vulnerable hospitals in a way that a single formula-driven allocation may not. Targeting financially vulnerable safety net hospitals may require taking into consideration more factors than the amount of care a hospital provides to low-income patients. A multi-variate analysis of the factors affecting a hospital's financial risk and its overall financial status using a broader set of hospitals could help identify additional factors that should be considered in an allocation policy.
Allocations based on the proportion of care provided to low-income patients (e.g. revenues) result in very different distributions than an allocation based on financial risk (Medicaid shortfalls, uncompensated care and bad debt). Financial risk, however, is not the same as financial viability (i.e., total margins net of DSH payments). Some hospitals with substantial financial risk also have positive margins. The results across all three states highlighted the need to clarify the policy goals for DSH funding. The key issue is the extent to which subsidies should be given to hospitals that serve low-income patients but do not incur financial risk or are able to cover their risk with other revenues. A closer examination of the hospitals with substantial gains or losses in moving from an allocation policy based on serving low-income patients to incurring financial risk might help clarify the issues. This examination should consider the role of other federal subsidies such as the Medicare indirect teaching adjustment in explaining why some hospitals with substantial financial risk appear to be in a strong financial position.
Examining the relationship between the financial status of hospitals and the distribution of DSH payments was a complex task. Particular areas where data issues became potentially problematic included:
The "snapshot" approach of looking at one year's data may not be sufficient for an adequate understanding of the financial implications of serving low-income patients. In California, the FY1998 payments included payments from the state's fiscal year 1997 and thus overstated the average DSH payments. The New York indigent care pool was in transition during FY1998 and additional changes were enacted in 2000. Wisconsin's uncompensated care costs have increased 60 percent since 1997. Only the first-year impacts of the Balanced Budget Amendment are reflected in the FY1998 data. These considerations suggest that a multi-year study- perhaps with periodic updating- would be appropriate.
Even more troubling than using one year's data is the lack of a national database that provides uniform information on the quantity of care provided to low-income patients and the financial risk associated with that care. The BBRA provision requiring the Secretary to collect through the Medicare cost report data on uncompensated costs should help. This provision is effective for cost reporting periods beginning on or after October 1, 2001. A national database is needed to understand the potential re-distributions that might occur both at the market level and across states under a national allocation policy.
Absent a national database with uncompensated care data and other information needed to develop measures of financial risk, three areas of investigation could be pursued that would provide valuable information related to federal support for hospitals that provide a disproportionate share of care to poor patients.
A national database is needed to fully understand the potential impact of alternative allocation policies at both the national and market levels. Having the national database would facilitate:
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