Analysis of the Joint Distribution of Disproportionate Share Hospital Payments. Measures Derived From Financial Data


Measures 2.1 and 2.2 use financial data to measure the percentage of gross revenue attributable to low-income patients. Measure 2.1 is similar to MedPAC model's definition of a hospital's low-income share.1 Gross revenues derived from financial data have several advantages over those derived from inpatient claims data.

  • Secondary payers are accounted for (assuming the reporting is accurate).
  • Both inpatient and outpatient volume are directly measured,
  • Implicit recognition is given to differences in severity across the hospital's patient population.

There are issues, however, regarding uniform reporting of financial data generally, and uncompensated care and bad debt in particular. We decided to use both bad debt and uncompensated care costs in the models derived from financial data because of reporting inconsistencies (see Chapter 2). Basing a policy on uncompensated care only (with uniform definitions) or uncompensated care and bad debt attributable to self-pay patients might be more appropriate policies to target financially vulnerable safety net hospitals than including bad debt associated with care provided to insured patients. Nevertheless, given current reporting inconsistencies, we have included all bad debt and uncompensated care in our models that use financial data.

Measures 3.1 and 3.2 focus on the financial risk associated with serving low-income patients. Measure 3.1 defines financial risk in terms of shortfalls from Medicaid and local indigent care programs, bad debt, and uncompensated care. Medicare SSI patients and Medicaid patients to the extent the Medicaid payment covers the cost of their care are not taken into consideration. The Medicaid shortfall could be attributable to either low-payment rates or to hospital inefficiency. In computing the Medicaid shortfall, we exclude DSH funds so that the measure is financial risk in the absence of DSH funding (see more detailed discussion of methodology in Chapter 8). There is some danger that including the Medicaid shortfall could provide a perverse incentive to reduce payment rates. The actual incentive will depend on the relationship between the state's FMAP and the generosity of the DSH payments. An alternative to including the Medicaid shortfall would be to count only a portion (e.g. 50%) of gross Medicaid revenues in constructing a revenue measure.

Finally, Measure 4.1 measures each urban hospital's market share of uncompensated care and bad debt. The market is defined by MSA. Conceptually, this measures hospital's uncompensated care load in relation to its market rather than the national market.

1.  The AHA data used by MedPAC does not have a separate category for patients under local indigent care programs. As a result, MedPAC assumes that the shortfalls in the "other" patient category are attributable to the local indigent care program. Specific information on local indigent care program revenues is available in our financial data.

View full report


"report.pdf" (pdf, 829.97Kb)

Note: Documents in PDF format require the Adobe Acrobat Reader®. If you experience problems with PDF documents, please download the latest version of the Reader®