Analysis of the Joint Distribution of Disproportionate Share Hospital Payments. Summary of Findings and Conclusions


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 hospital’s uncompensated care and shortfalls from Medicaid and local indigent care programs. Given the diversity of the 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.

Criteria to Measure Care Provided to Low-Income Patients. 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 analyses suggest that how the patient population (e.g., with or without Medicare SSI beneficiaries) is defined in the DSH allocation statistic is more important than how the care provided to those patients is quantified (e.g. days, discharges, revenues). 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.

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 total (inpatient and outpatient) revenues was .811, which 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 correlated with the hospital’s ratio of financial risk to operating expenses (.591) than the other utilization measures. However, 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. 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.

Evaluation of Alternative Allocation Policies. 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 simulations 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 one based on 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.

Data Issues and Limitations. 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:

  • Matching hospitals across multiple data sources: Medicare cost reports, state DSH reports, AHA survey data, HCUP, and (in the case of California, New York and Wisconsin) state financial reports. The inclusion of Medicare provider numbers on the state DSH reports would facilitate matching hospitals with their DSH payments. Universal adoption of the uniform provider number would also help.
  • For Medicaid DSH, the net gains to the hospital are more important than the reported DSH payments. CMS should give consideration to obtaining this information. It could be included in the state reports on DSH payments (in which case the information would be available for all hospitals) or it could be required as part of the Medicare cost report. Even knowing the net DSH payments to individual hospitals is not enough; it is also important to know how DSH payments (and any provider contributions) are handled in reporting Medicaid contractual allowances and patient revenues.
  • The differences in state accounting and reporting practices made it difficult to determine Medicaid shortfalls and to take “new” DSH payments into account. The financial data for several public hospitals was problematic. It is important to understand how financing occurs for county-owned hospitals in terms of other intergovernmental transfers and deficit funding. An allocation based on financial measures would require uniform reporting by payer.

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 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.

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