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Appendix A. Technical Documentation for Estimating DSH Payments
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Data Sources Used to Estimate Medicare Payments
We drew on several data sources to estimate Medicare DSH payments: the Provider of Service (POS) file, the PPS Impact files for FY 1998 and FY2000, and the Provider-specific File (PSF) and HCRIS files. Our starting point for a hospital listing was the CMS Provider of Service (POS) file. According to this file, there were 8,868 providers classified as "hospital" in the United States in FY1998. Of this total, we identified as our initial sample approximately 6,200 acute care hospitals that could be theoretically eligible to receive Medicare DSH payments. We used the information in the PPS Impact files and the PSF files to simulate DSH payments to these hospitals.
PPS Impact Files
The PPS impact files that CMS produces each year as part of the annual update in the hospital prospective payment system contain information that can be used to estimate each hospital's payments for the upcoming federal fiscal year. The variables include current payment parameters (e.g. the applicable wage index for the upcoming fiscal year), hospital characteristics from the most recently filed cost report, and patient characteristics from Medicare claims data from two years prior (e.g. the FY2000 impact file includes data on FY1998 claims received through March 31, 1999). We used a combination of PPS impact files to develop our estimate. That is, the impact file for FY1998 provides the best information on the payment parameters in effect for that fiscal year. The impact file for FY2000 provides the best information on patient characteristics, including SSI percentage, for patients discharged during FY1998. It also provides the best match for the DSH patient percentage that would have been applicable during FY1998.
Provider-specific Files
We used several payment variables from the PSF (and in some case HCRIS) that are not available on the PPS impact file to improve the estimation for capital-related costs. These elements are:
- whether the hospital is paid under the fully prospective methodology or the hold-harmless methodology for capital-related costs. For urban hospitals with 100 or more beds, this information is relevant to determining the federal rate payment eligible for the DSH add-on.
- new capital payment ratio. For hospitals paid under the hold-harmless methodology for old capital costs, the ratio determines the proportion of the federal rate that is payable for new capital.
Summary of Data Sources
We summarize the data sources used to estimate Medicare DSH payments in Table A.1.
Table A.1
Summary of Data Sources Used
to Estimate Medicare DSH and Total PaymentsPayment Variable FY 1998 Standard payment rate FY1998 FR- Table 1 MSA for standard payment rate FY1998 impact Wage indices Wage index history Cost of living adjustment FY1998 impact Number of discharges(1) FY2000 impact Case-mix index 1 FY2000 FR-Table 3C DSH patient percentage(2) FY2000 impact DSH operating adjustment factor FY1998 rules DSH capital adjustment factor FY1998 rules Sole community HSP rate FY1998 impact Provider type FY1998 impact Capital federal rate percentage HCRIS or PSF Eligibility for temporary relief(3) HCRIS or PSF We used these data to determine both Medicare DSH payments and other payments under the prospective payment system (e.g., indirect teaching and outlier) that, while not needed to estimate DSH payments, are need to define classes of hospitals and establish total Medicare payments.
Methodology for Estimating Hospital-specific Medicaid DSH Payments
Data Limitations
There are several problems with the Medicaid DSH reports that make it difficult to use them effectively. Although the BBA requires that states submit these reports, compliance with this requirement appears lax and federal enforcement is limited. As a result, CMS does not have a complete set of reports for any fiscal year. The reports that have been submitted contain varying levels of information because CMS gives states considerable latitude in completing them. In a Federal Register Notice dated October 8, 1998, CMS recommended that states file reports that include the name of hospital, type of hospital, ownership (e.g., public or private) and annual payment. However, when states submit reports, they often do not include this minimal level of information. Among the most significant problems are lack of information to adequately identify hospitals, unreliable or missing identification by hospital type, inconsistent identification of mental health or psychiatric DSH payments, and differing payment amounts compared to reporting on Form HCFA-64.
One problem for researchers that want to use the DSH reports is that the only identifier that most states provide for hospitals are their names. In many cases, they use abbreviations or initials. Some reports contain duplicate names with no other identifiers. Others do not clearly identify out-of-state hospitals. Some states include Medicaid numbers or other numerical identification; others provide no numerical identifiers. Poor identification of hospitals makes it difficult to properly group them into hospital types or to conduct more extensive analyses by linking these data with other hospital specific data.
A second problem is that DSH expenditures reported on Form HCFA-64 and the state reports often do not match. In some cases, these differences are attributable to inconsistent time frames--Form HCFA-64 data represent federal fiscal years and several states submitted reports for state fiscal years or calendar years. In other cases, states reported only the state share of DSH expenditures. There are also several instances in which total DSH expenditures reported on Form HCFA-64 differ from those reported on hospital specific reports for the same time period. For example, Pennsylvania's hospital specific report for FY 1998 showed a total of $41 million in DSH payments whereas the state claimed $546 million in DSH payments on Form HCFA-64. Without standardized reporting by federal fiscal year and method of accounting between the hospital specific reports and Form HCFA-64, it is difficult to determine the accuracy of the information reported on the hospital specific reports.
A third problem is that information concerning ownership and type of hospital is not uniform and is sometimes inconsistent with other sources. Many states do not identify whether hospitals are state-owned, other public, or private. When reported, this information is sometimes at odds with other available sources. For example, New Hampshire's DSH reports identify several hospitals as public that the American Hospital Association (AHA) indicates are private, non-profit. Information on the type of hospital (e.g., acute, children's, psychiatric, rehabilitation) is also often missing or inconsistent. For example, several hospitals in Iowa are identified as both acute and psychiatric in the Medicaid DSH report.
A fourth problem is that identification of DSH payments to psychiatric facilities is not consistent. For example, California, Iowa, Mississippi, and New Mexico all had limits of $0 on DSH payments to institutions for mental diseases (IMD) in FY 1998, yet all four states report payments to hospitals that are identified as psychiatric facilities by the state's DSH report, the AHA, or Medicare files. Several states' reported expenditures to psychiatric hospitals from hospital specific reports are also not consistent with what they report on Form HCFA-64 as IMD DSH payments.
Methodology
CMS staff have compiled states' DSH reports into spreadsheets that include each hospital's name, the total annual DSH payments paid to that hospital by the state, and information about the hospital including ownership (public or private) and type (acute, children's, teaching, or psychiatric). We combined the data for each of the states into a single spreadsheet for the nation. To be consistent with the Medicare DSH estimates, and to take advantage of the largest group of available Medicaid reports, we used FY 1998 as the benchmark year.
In order to merge the Medicaid DSH payment data with our estimated Medicare DSH payments, we had to identify hospitals in the Medicaid reports using their Medicare provider numbers. Only two states, Michigan and North Carolina, put Medicare provider numbers on their hospital specific Medicaid DSH reports. Project staff used the CMS On-line Survey and Certification Reporting System (OSCAR) and Provider of Service (POS) files, as well as AHA data from the on-line American Hospital Directory (www.ahd.com) to match hospital names in the Medicaid reports with Medicare provider numbers. This task had to be done by hand, and was further complicated because of the lack of detailed information about the hospitals. In general, discrepancies in hospital ownership or type were resolved by retaining the classifications from the Medicare or AHA data.
Several states included a few individual hospitals in their Medicaid DSH reports that we could not identify with sufficient confidence to match them with their Medicare provider numbers. We created dummy Medicare provider numbers for these hospitals to keep them in the data set, but they could not be linked up with Medicare DSH payment information. In addition, eight states lacked hospital specific payment information for a much larger share of their Medicaid DSH payments; they were Alabama, Colorado, Georgia, Illinois, Indiana, Minnesota, New Jersey, and Pennsylvania. For these states, we created one dummy variable to account for the missing DSH payments to acute care facilities and a separate dummy variable to account for missing IMD DSH payments. Unidentified hospitals account for 12 percent of total Medicaid DSH expenditures in the completed analysis, although they account for a very small share of reported expenditures in all but a few states.
In a few cases, we could not get hospital specific reports for FY 1998 but received reports for other time periods. We did not get FY 1998 reports for Louisiana, Minnesota, New York, or South Carolina. In Louisiana, total payments in the state fiscal year 1998 report that we received were virtually identical to total payments in federal fiscal year 1998, so we used the state fiscal year report. The adjustments to the other three states are noted in the state specific notes, below.
Once all 49 states with DSH programs were part of the data set, we compared the total amounts of Medicaid DSH payments reported on the state's hospital specific reports with aggregate totals reported on Form HCFA-64 for FY 1998. The HCFA-64 is widely considered the most accurate record of Medicaid expenditures available. In general, most states reported total expenditures on their hospital specific reports that were extremely close if not identical to total DSH expenditures reported on Form HCFA-64. Based on this comparison, we made changes to Alaska, Delaware, and Wyoming as noted below.
Total expenditures for inpatient DSH and IMD DSH from the hospital specific reports were also compared to FY 1998 DSH limits from the BBA. Based on these comparisons, we feel that the hospital specific Medicaid DSH payments used in our analyses are a good reflection of actual payments made in FY 1998.
State-Specific Notes
Alabama
Most hospitals in Alabama take part in a managed care initiative called the Partnership Hospital Program (PHP). No hospital-specific data are reported for the 112 hospitals that participate in the PHP, so we created a single dummy variable to account for the $346 million in acute care DSH payments paid to these hospitals.
Alaska
We increased Alaska's payment to its single DSH hospital from the $12.7 million figure reported on the hospital specific report to $13.8 million to match the HCFA-64.
Delaware
Delaware reported only the state's share of total payments to its single DSH hospital. The state's FMAP is 50%, so we doubled the reported amount.
Georgia
The data we received from Georgia were for state fiscal year 2001 and state officials noted that the amounts paid to specific hospitals may have been significantly different from those paid in FFY 1998 due to recent program changes. We created a single dummy variable to account for the $413 million in DSH payments that Georgia made to acute care facilities.
Indiana
The state reported $123 million in DSH payments on the HCFA-64, but included only $116 million in total payments on its hospital specific report. The total IMD DSH payments claimed on both reports were identical, so we added a dummy acute care DSH payment of $6.8 million to make up the difference.
Illinois
The state reported $235 million in DSH payments on the HCFA-64, but included only $154 million in total payments on its hospital specific report. All of the missing payments appeared to be IMD DSH payments, so we added a dummy IMD DSH payment of $81 million to make up the difference.
Minnesota
The lone hospital specific report submitted by Minnesota was for calendar year 1997. The total payments in this report were comparable to the total payments claimed on Form HCFA-64 for FY 1998, but the distribution among acute care and IMD facilities from the hospital specific report was inconsistent with the reported distribution from Form HCFA-64 and the state's IMD DSH limit from the BBA. We replaced the hospital specific data with separate dummy values for the total acute care DSH payments and total IMD DSH payments reported on the HCFA-64.
New Hampshire
New Hampshire's hospital specific report for FY 1998 did not include New Hampshire Hospital, a psychiatric facility that received an IMD DSH payment of $25 million. We added this hospital to our data set to make the state's total DSH payments match what was reported on the HCFA-64.
New Jersey
The state reported $1.058 billion in DSH payments on Form HCFA-64, but included only $876 million in total payments on its hospital specific report. The total IMD DSH payments claimed on both reports were identical, so we added a dummy acute care DSH payment of $182 million to make up the difference.
New York
New York did not submit a hospital specific report to HCFA for FY 1998. We started with the distribution of payments to specific hospitals from the state's FY 1999 report, then adjusted the payments to all the hospitals so that total DSH payments equaled the FY 1998 amount (statewide). Payments to acute care facilities were multiplied by 0.9043; payments to IMD facilities were multiplied by 1.0237 (The 1999 report included only the federal share).
Pennsylvania
The hospital specific report submitted by Pennsylvania for FY 1998 included only $41 million in total DSH payments, while the state claimed $546 million in total DSH payments on Form HCFA-64. We replaced the hospital specific data with separate dummy values that match the total acute care DSH payments ($216 million) and total IMD DSH payments ($330 million) reported on the HCFA-64.
South Carolina
South Carolina did not submit a hospital specific report to HCFA for FY 1998. We started with payments to specific hospitals from the state's FY 1999 report, then adjusted the payments to all the hospitals so that total DSH payments equaled the FY 1998 amount (statewide). Payments to acute care facilities were multiplied by 1.0285; payments to IMD facilities were multiplied by 1.0162.
Wyoming
Wyoming reported only the federal share of total payments to its DSH hospitals in its hospital specific report. The state's FMAP is 63.02%, so we multiplied the reported payments by 1.5868 (=1.0/0.6302) to get the combined federal and state total payments of $106,315.
Endnotes
1. Unlike the cost report, the CMI and discharges are adjusted for short-stay transfer cases.
2. The DSH patient percentage is based on the percentage of Medicare patients who are entitled to SSI and the percentage of all patients who are eligible for Medicaid (and not Medicare). The SSI percentage is based on FY1998 claims. The Medicaid percentage is from the most recently settled cost report.
3. During FY1998 and FY1999, certain hospitals qualified for a higher update than other hospitals ("temporary relief" hospitals). To qualify, the hospital could not receive DSH or IME payments and needed to be located in a state where such hospitals had a Medicare negative operating margin in FY1995. The provision provided eligible hospitals with negative operating margins with a .5 percent higher update in FY1998 and .3 percent higher update in FY1999.
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Appendix B. Additional Tables on the Current Distribution of DSH Payments
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Table B.2
Total Estimated "New" DSH by Category ($ millions)
Estimated Medicare Payments Using FY2003 Rules and Federal Share of Medicaid PaymentsMedicare SSI Days and Medicaid Days as Percent of Total Inpatient Days 5638 305.6 100.0% 5,183 100.0% 7,559 100.0% 12,742 100.0% 100.0% <.10 1510 73.3 24.0% 36 0.7% 246 3.3% 282 2.2% 26.3% = >.10 and <.20 1715 101.0 33.1% 998 19.2% 696 9.2% 1,694 13.3% 36.6% = >.20 and < .30 947 59.4 19.4% 1,579 30.5% 1,033 13.7% 2,611 20.5% 20.6% =>.30 and <.40 474 29.5 9.7% 1,216 23.5% 1,413 18.7% 2,630 20.6% 9.4% =>.40 and <.50 211 12.8 4.2% 674 13.0% 983 13.0% 1,657 13.0% 3.7% =>.50 and <.60 96 5.8 1.9% 311 6.0% 570 7.5% 880 6.9% 1.6% =>.60 and <.70 55 3.9 1.3% 233 4.5% 545 7.2% 778 6.1% 1.0% =>.70 and <.80 21 1.3 0.4% 88 1.7% 61 0.8% 149 1.2% 0.4% =>.80 9 0.3 0.1% 8 0.2% 5 0.1% 14 0.1% 0.1% Missing 600 18.2 6.0% 41 0.8% 2,007 26.5% 2,047 16.1% 0.2% Medicare Inpatient Days As Percent of Total Inpatient Days 5638 305.6 100.0% 5,183 100.0% 7,559 100.0% 12,742 100.0% 100.0% 0-24 275 18.2 6.0% 521 10.0% 2,663 35.2% 3,184 25.0% 4.0% 25-49 1314 98.3 32.2% 2,734 52.8% 1,447 19.1% 4,181 32.8% 32.7% 50-64 2029 119.7 39.2% 1,568 30.3% 957 12.7% 2,525 19.8% 45.3% 65-79 1247 44.1 14.4% 220 4.3% 206 2.7% 426 3.3% 16.0% 80 and over 166 3.7 1.2% 8 0.1% 14 0.2% 22 0.2% 1.0% Missing 607 21.5 7.0% 132 2.5% 2,272 30.1% 2,403 18.9% 0.9% Medicare SSI Days As Percent of Total Medicare Days 5638 305.6 100.0% 5,183 100.0% 7,559 100.0% 12,742 100.0% 100.0% <.10 3153 183.5 60.1% 1,453 28.0% 1,203 15.9% 2,656 20.8% 65.3% = >.10 and <.20 1216 73.9 24.2% 2,380 45.9% 1,615 21.4% 3,995 31.4% 25.8% = >.20 and < .30 436 21.6 7.1% 825 15.9% 1,986 26.3% 2,811 22.1% 6.0% =>.30 and <.40 162 6.2 2.0% 308 5.9% 707 9.4% 1,015 8.0% 1.7% =>.40 and <.50 45 1.3 0.4% 90 1.7% 26 0.3% 116 0.9% 0.5% =>.50 and <.60 17 0.4 0.1% 40 0.8% 6 0.1% 45 0.4% 0.2% =>.60 and <.70 9 0.4 0.1% 48 0.9% 9 0.1% 57 0.4% 0.2% =>.70 0 0.0 0.0% 0 0.0% 0 0.0% 0 0.0% 0.0% Missing 600 18.2 6.0% 41 0.8% 2,007 26.5% 2,047 16.1% 0.2% Medicaid Inpatient Days As a Percent of Total Non-Medicare Days 5638 305.6 100.0% 5,183 100.0% 7,559 100.0% 12,742 100.0% 100.0% <.10 858 39.4 12.9% 31 0.6% 80 1.1% 112 0.9% 13.8% = >.10 and <.20 972 54.0 17.7% 194 3.7% 290 3.8% 484 3.8% 19.2% = >.20 and < .30 1073 70.0 22.9% 942 18.2% 865 11.4% 1,807 14.2% 25.3% =>.30 and <.40 867 54.1 17.7% 1,297 25.0% 1,109 14.7% 2,406 18.9% 19.0% =>.40 and <.50 518 29.2 9.6% 953 18.4% 1,095 14.5% 2,048 16.1% 9.6% =>.50 and <.60 317 20.3 6.7% 786 15.2% 955 12.6% 1,741 13.7% 6.6% =>.60 and <.70 150 7.0 2.3% 328 6.3% 584 7.7% 912 7.2% 2.2% =>.70 and <.80 86 5.9 1.9% 314 6.1% 216 2.9% 530 4.2% 2.0% =>.80 86 3.3 1.1% 169 3.3% 86 1.1% 255 2.0% 1.1% Missing 711 22.3 7.3% 169 3.3% 2,280 30.2% 2,448 19.2% 1.1% Medicaid Inpatient Days As Percent of Total Inpatient Days 5638 305.6 100.0% 5,183 100.0% 7,559 100.0% 12,742 100.0% 100.0% 1st state quartile 1223 57.2 18.7% 103 2.0% 176 2.3% 279 2.2% 1223 2nd state quartile 1274 65.7 21.5% 566 10.9% 318 4.2% 884 6.9% 1274 3rd state quartile 1257 74.2 24.3% 1,316 25.4% 925 12.2% 2,241 17.6% 1257 4th state quartile 1283 90.2 29.5% 3,157 60.9% 4,121 54.5% 7,278 57.1% 1283 1 s.d. Above State Average 1120 67.6 22.1% 1,987 38.3% 3,387 44.8% 5,374 42.2% 1120 Missing 601 18.3 6.0% 41 0.8% 2,019 26.7% 2,060 16.2% 111 Teaching Status 5638 305.6 100.0% 5,183 100.0% 7,559 100.0% 12,742 100.0% 5148 Non- teaching 3994 157.8 51.6% 1,859 35.9% 973 12.9% 2,832 22.2% 3993 Fewer than 10 residents 369 26.6 8.7% 468 9.0% 193 2.6% 661 5.2% 369 Residents >10 and <100 509 56.1 18.4% 1,138 22.0% 1,254 16.6% 2,393 18.8% 509 Residents => 100 and < 250 149 25.3 8.3% 919 17.7% 1,382 18.3% 2,300 18.1% 149 Residents => 250 88 22.0 7.2% 782 15.1% 1,755 23.2% 2,537 19.9% 88 Missing 529 17.7 5.8% 18 0.3% 2,002 26.5% 2,020 15.8% 40
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Appendix D. Simulation Results from Three State Analysis
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Table D.1A
California Hospitals DSH Payments Based on Percent Low-income UtilizationN
Receiving DSHDSH Funds $ % of DSH Funds DSH to Fin Risk DSH Per Adjusted Day ($) Margin w/ DSH All Hospitals 204 1,880,769,299 100% 0.78 104 6.7% By Geographic Area Urban 176 1,847,252,818 98% 0.79 107 6.7% Large Urban 128 1,564,749,624 83% 0.81 118 6.9% Other Urban 48 282,503,194 15% 0.66 73 5.9% Rural 28 33,516,481 2% 0.48 37 7.3% Urban By Bedsize 0-49 beds 11 15,078,245 1% 0.95 41 7.8% 50-99 beds 22 43,405,547 2% 0.39 44 6.7% 100-199 beds 55 266,523,501 14% 0.63 82 3.4% 200-299 beds 36 339,716,788 18% 0.81 99 4.8% 300-499 beds 35 561,402,713 30% 0.90 97 8.6% 500 or more beds 17 621,126,025 33% 0.82 182 7.3% Rural By Bedsize 0-49 beds 14 10,188,910 1% 0.41 26 6.8% 50-99 beds 11 15,419,380 1% 0.51 55 7.1% 100-149 beds 3 7,908,191 0% 0.52 35 8.2% 150 or more beds Type of Ownership State government 2 73,685,230 4% 1.42 302 14.6% County or local government 24 931,648,833 50% 1.16 418 14.7% Gov. - hosp. dist. 35 82,333,881 4% 0.49 39 4.7% Not-for-profit 100 614,447,732 33% 0.52 56 4.2% For-profit 43 178,653,623 9% 0.79 70 8.4% Teaching Status Non- teaching 149 541,979,783 29% 0.54 47 5.2% Fewer than 10 residents 19 153,104,556 8% 0.93 100 6.7% Residents >10 and <100 24 437,571,870 23% 0.79 169 4.7% Residents => 100 and < 250 6 311,449,927 17% 1.24 282 7.9% Residents => 250 6 436,663,164 23% 0.97 319 13.6% Low-Income Patient Gross Days as % of Total Days More than 60% 39 1,211,818,333 64% 1.25 395 14.4% 50-60 % 16 122,722,215 7% 1.42 202 9.0% 40-50 % 24 211,266,806 11% 1.19 143 4.2% 30-40 % 41 166,492,927 9% 0.66 79 4.7% 20-30 % 70 161,164,585 9% 0.28 34 3.4% 10-20 % 14 7,304,434 0% 0.03 2 2.3% 10 % and less 0 0 0% 0.00 0 10.3% Low-Income Patient Gross Revenues as % of Total Patient Revenues More than 60% 21 903,669,835 48% 1.18 449 15.4% 50-60 % 10 112,971,280 6% 1.54 196 14.1% 40-50 % 23 237,396,523 13% 1.36 199 7.6% 30-40 % 27 199,262,419 11% 0.96 130 8.1% 20-30 % 62 284,263,242 15% 0.70 74 4.2% 10-20 % 55 134,926,526 7% 0.23 25 3.0% 10 % and less 6 8,279,475 0% 0.04 2 6.0% Financial Risk More than 25 % 19 441,924,754 23% 0.81 367 5.0% 20-25 % 14 313,981,418 17% 1.10 352 16.9% 15-20 % 18 256,857,318 14% 1.33 259 15.0% 10-15 % 60 384,735,409 20% 0.64 104 4.7% 5-10 % 64 296,955,865 16% 0.49 52 4.6% 0-5 % 23 149,274,304 8% 0.71 30 6.3% None 6 37,040,231 2% -1.98 70 17.3% Safety Net Hospitals: Margin Net of DSH Less than -25% 23 289,976,723 15% 0.92 276 -11.3% -15 to -25% 19 174,513,026 9% 0.86 195 -1.6% -5% to -15% 45 449,934,183 24% 0.97 147 3.1% -5% to 5% 60 514,819,510 27% 0.77 116 7.7% 5% to 15% 37 410,566,958 22% 1.05 182 16.6% From 15% to25% 4 29,142,775 2% 0.92 97 22.5% 25% and higher 2 4,511,690 0% -1.12 190 35.5% All Safety Net Hospitals 190 1,873,464,865 100% 0.91 156 7.5% Table D.1B
California Hospitals DSH Payments Based on Percent Low-income RevenuesN
Receiving DSHDSH Funds
$% of DSH
FundsDSH to
Fin RiskDSH Per
Adjusted
Day ($)Margin
w/ DSHAll Hospitals 199 1,880,769,299 100% 0.78 104 6.7% By Geographic Area Urban 163 1,804,632,340 96% 0.77 105 6.5% Large Urban 113 1,480,819,153 79% 0.77 111 6.5% Other Urban 50 323,813,187 17% 0.75 84 6.6% Rural 36 76,136,959 4% 1.08 85 11.6% Urban By Bedsize 0-49 beds 17 58,268,341 3% 3.67 159 21.7% 50-99 beds 20 75,631,172 4% 0.67 77 9.0% 100-199 beds 54 274,858,478 15% 0.65 85 3.6% 200-299 beds 27 298,129,617 16% 0.71 87 3.9% 300-499 beds 30 479,095,696 25% 0.77 83 7.7% 500 or more beds 15 618,649,036 33% 0.82 181 7.2% Rural By Bedsize 0-49 beds 22 48,891,109 3% 1.97 124 17.8% 50-99 beds 11 19,773,636 1% 0.65 71 8.3% 100-149 beds 3 7,472,214 0% 0.50 33 8.1% 150 or more beds Type of Ownership State government 2 48,283,967 3% 0.93 198 10.5% County or local government 27 987,312,918 52% 1.23 443 15.8% Gov. - hosp. dist. 43 133,130,826 7% 0.79 63 6.9% Not-for-profit 84 519,152,473 28% 0.44 48 3.6% For-profit 43 192,889,115 10% 0.85 75 8.8% Teaching Status Non- teaching 151 568,877,200 30% 0.57 50 5.4% Fewer than 10 residents 15 146,821,582 8% 0.89 96 6.4% Residents >10 and <100 21 440,056,345 23% 0.80 170 4.8% Residents => 100 and < 250 6 334,588,026 18% 1.33 303 8.8% Residents => 250 6 390,426,147 21% 0.87 285 12.5% Low-Income Patient Gross Days as % of Total Days More than 60% 39 1,202,795,032 64% 1.24 392 14.3% 50-60 % 15 92,842,619 5% 1.08 153 5.8% 40-50 % 24 145,103,314 8% 0.82 98 0.9% 30-40 % 37 133,617,566 7% 0.53 63 3.6% 20-30 % 52 178,875,040 10% 0.31 38 3.7% 10-20 % 24 103,352,701 5% 0.36 24 4.0% 10 % and less 8 24,183,028 1% 0.35 13 11.1% Low-Income Patient Gross Revenues as % of Total Patient Revenues More than 60% 24 980,221,632 52% 1.28 487 17.0% 50-60 % 13 163,466,901 9% 2.23 283 20.1% 40-50 % 27 248,079,032 13% 1.42 208 8.3% 30-40 % 31 197,005,282 10% 0.95 129 8.0% 20-30 % 71 255,237,147 14% 0.63 67 3.6% 10-20 % 33 36,759,306 2% 0.06 7 1.8% 10 % and less 0 0.00 0 5.9% Financial Risk More than 25 % 20 509,899,638 27% 0.94 424 8.0% 20-25 % 16 328,966,091 17% 1.16 369 17.7% 15-20 % 20 235,533,153 13% 1.22 238 13.8% 10-15 % 60 318,403,827 17% 0.53 86 3.5% 5-10 % 51 244,677,509 13% 0.40 42 4.0% 0-5 % 22 184,313,984 10% 0.87 37 6.7% None 10 58,975,096 3% -3.15 111 19.7% Safety Net Hospitals: Margin Net of DSH Less than -25% 22 334,724,098 18% 1.07 318 -7.5% -15 to -25% 17 154,638,937 8% 0.76 173 -3.4% -5% to -15% 42 373,648,499 20% 0.80 122 1.3% -5% to 5% 51 499,176,672 27% 0.75 112 7.5% 5% to 15% 30 350,680,113 19% 0.90 155 15.5% From 15% to25% 4 35,362,993 2% 1.11 118 23.5% 25% and higher 1 5,002,258 0% -1.25 211 36.0% All Safety Net Hospitals 167 1,753,233,570 93% 0.85 146 6.9% Table D.1C
California Hospitals DSH Payments Based on Financial Risk as % Operating CostN
Receiving
DSHDSH Funds
$% of DSH
FundsDSH to
Fin RiskDSH Per
Adjusted
Day ($)Margin
w/ DSHAll Hospitals 221 1,880,769,299 100% 0.78 104 6.7% By Geographic Area Urban 188 1,822,939,093 97% 0.77 106 6.6% Large Urban 131 1,453,674,718 77% 0.76 109 6.4% Other Urban 57 369,264,375 20% 0.86 95 7.4% Rural 33 57,830,207 3% 0.82 64 9.8% Urban By Bedsize 0-49 beds 13 31,579,303 2% 1.99 86 13.7% 50-99 beds 30 98,754,944 5% 0.88 101 10.5% 100-199 beds 57 419,777,706 22% 0.99 129 7.0% 200-299 beds 31 352,389,005 19% 0.84 103 5.0% 300-499 beds 40 390,384,776 21% 0.62 68 6.8% 500 or more beds 17 530,053,358 28% 0.70 155 6.0% Rural By Bedsize 0-49 beds 19 25,942,870 1% 1.04 66 11.6% 50-99 beds 11 24,269,131 1% 0.80 87 9.5% 100-149 beds 3 7,618,205 0% 0.51 34 8.1% 150 or more beds Type of Ownership State government 2 27,052,042 1% 0.52 111 6.8% County or local government 27 774,144,256 41% 0.96 348 11.5% Gov. - hosp. dist. 38 154,106,674 8% 0.92 72 7.8% Not-for-profit 109 707,175,043 38% 0.60 65 4.7% For-profit 45 218,291,284 12% 0.96 85 9.5% Teaching Status Non- teaching 164 792,773,178 42% 0.79 69 6.8% Fewer than 10 residents 19 115,486,497 6% 0.70 75 5.1% Residents >10 and <100 27 482,953,399 26% 0.88 186 5.8% Residents => 100 and < 250 5 224,820,357 12% 0.90 204 4.3% Residents => 250 6 264,735,868 14% 0.59 194 9.6% Low-Income Patient Gross Days as % of Total Days More than 60% 35 910,083,780 48% 0.94 297 9.9% 50-60 % 14 75,570,672 4% 0.88 124 3.8% 40-50 % 22 144,709,079 8% 0.81 98 0.9% 30-40 % 36 234,164,879 12% 0.93 110 7.0% 20-30 % 65 387,763,999 21% 0.67 81 6.5% 10-20 % 42 113,006,088 6% 0.39 27 4.1% 10 % and less 7 15,470,802 1% 0.22 9 10.8% Low-Income Patient Gross Revenues as % of Total Patient Revenues More than 60% 21 749,628,494 40% 0.98 372 12.0% 50-60 % 12 104,562,272 6% 1.43 181 13.1% 40-50 % 23 166,653,435 9% 0.95 140 3.0% 30-40 % 23 138,057,719 7% 0.67 90 5.7% 20-30 % 59 385,781,937 21% 0.95 101 6.3% 10-20 % 67 312,988,957 17% 0.52 58 5.1% 10 % and less 16 23,096,484 1% 0.11 7 6.2% Financial Risk More than 25 % 20 604,832,852 32% 1.11 503 12.0% 20-25 % 16 290,821,854 15% 1.02 326 15.6% 15-20 % 20 230,025,256 12% 1.19 232 13.4% 10-15 % 68 493,671,344 26% 0.82 133 6.6% 5-10 % 97 261,417,993 14% 0.43 45 4.2% 0-5 % 0 - - - - 4.3% None 0 - - - - 12.7% Safety Net Hospitals: Margin Net of DSH Less than -25% 23 379,612,621 20% 1.21 361 -4.0% -15 to -25% 18 207,164,833 11% 1.02 232 1.2% -5% to -15% 43 422,158,833 22% 0.91 138 2.5% -5% to 5% 57 453,490,349 24% 0.68 102 6.9% 5% to 15% 28 263,719,930 14% 0.68 117 13.9% From 15% to25% 3 26,145,843 1% 0.82 87 22.0% 25% and higher 0 - 0% 0.00 0 30.0% All Safety Net Hospitals 172 1,752,292,409 93% 0.85 146 6.9% TableD.1D
California Hospitals
Sliding Scale DSH Payments Based on Financial RiskN
Receiving
DSHDSH Funds
$% of DSH Funds DSH to Fin Risk DSH Per Adjusted Day ($) Margin w/ DSH All Hospitals 221 1,880,769,299 100% 0.78 104 6.7% By Geographic Area Urban 188 1,838,660,346 98% 0.78 107 6.6% Large Urban 131 1,448,347,145 77% 0.75 109 6.3% Other Urban 57 390,313,201 21% 0.91 101 7.8% Rural 33 42,108,953 2% 0.60 47 8.2% Urban By Bedsize 0-49 beds 13 30,788,348 2% 1.94 84 13.4% 50-99 beds 30 94,462,579 5% 0.84 97 10.3% 100-199 beds 57 454,666,710 24% 1.08 140 7.7% 200-299 beds 31 379,745,485 20% 0.91 111 5.6% 300-499 beds 40 317,950,971 17% 0.51 55 6.0% 500 or more beds 17 561,046,251 30% 0.74 164 6.4% Rural By Bedsize 0-49 beds 19 17,391,562 1% 0.70 44 9.1% 50-99 beds 11 19,888,011 1% 0.65 71 8.3% 100-149 beds 3 4,829,380 0% 0.32 22 7.1% 150 or more beds Type of Ownership State government 2 17,482,651 1% 0.34 72 5.0% County or local government 27 974,538,115 52% 1.21 438 15.5% Gov. - hosp. dist. 38 138,470,379 7% 0.83 65 7.1% Not-for-profit 109 552,514,992 29% 0.47 51 3.8% For-profit 45 197,763,163 11% 0.87 77 8.9% Teaching Status Non- teaching 164 674,128,236 36% 0.67 59 6.1% Fewer than 10 residents 19 113,080,929 6% 0.69 74 5.0% Residents >10 and <100 27 514,374,171 27% 0.93 199 6.5% Residents => 100 and < 250 5 283,384,527 15% 1.13 257 6.7% Residents => 250 6 295,801,436 16% 0.66 216 10.3% Low-Income Patient Gross Days as % of Total Days More than 60% 35 1,108,924,246 59% 1.14 361 12.9% 50-60 % 14 64,804,974 3% 0.75 107 2.6% 40-50 % 22 116,167,048 6% 0.65 79 -0.6% 30-40 % 36 194,346,428 10% 0.78 92 5.7% 20-30 % 65 295,506,794 16% 0.51 62 5.3% 10-20 % 42 90,513,618 5% 0.31 21 3.7% 10 % and less 7 10,506,192 1% 0.15 6 10.6% Low-Income Patient Gross Revenues as % of Total Patient Revenues More than 60% 21 960,980,171 51% 1.26 477 16.6% 50-60 % 12 121,176,845 6% 1.65 210 15.2% 40-50 % 23 152,532,170 8% 0.87 128 2.0% 30-40 % 23 104,537,633 6% 0.51 68 4.3% 20-30 % 59 318,224,376 17% 0.79 83 4.9% 10-20 % 67 209,320,617 11% 0.35 39 3.9% 10 % and less 16 13,997,489 1% 0.07 4 6.1% Financial Risk More than 25 % 20 819,189,624 44% 1.50 681 19.9% 20-25 % 16 373,537,123 20% 1.31 419 20.0% 15-20 % 20 191,906,250 10% 0.99 194 11.1% 10-15 % 68 339,199,428 18% 0.56 92 3.9% 5-10 % 97 156,936,874 8% 0.26 27 3.0% 0-5 % 0 - - - - 4.3% None 0 - - - - 12.7% Safety Net Hospitals: Margin Net of DSH Less than -25% 23 484,023,454 26% 1.54 460 3.3% -15 to -25% 18 225,626,736 12% 1.11 253 2.8% -5% to -15% 43 404,079,345 21% 0.87 132 2.0% -5% to 5% 57 388,358,074 21% 0.58 87 6.0% 5% to 15% 28 258,961,454 14% 0.66 115 13.8% From 15% to25% 3 18,700,426 1% 0.59 62 20.7% 25% and higher 0 0 0% 0.00 0 30.0% All Safety Net Hospitals 172 1,779,749,489 95% 0.86 148 7.1% Table D.2A
New York Hospitals
DSH Payments Based on Percent Low-income UtilizationN Receiving DSH DSH Funds $ % of DSH Funds DSH to Fin Risk DSH Per Adjusted Day ($) Margin w/ DSH All Hospitals 100 830,200,447 100% 0.46 37 -7.8% By Geographic Area Urban 79 806,647,385 97% 0.46 40 -8.4% Large Urban 60 770,336,074 93% 0.48 48 -9.3% Other Urban 19 36,311,311 4% 0.28 9 -3.4% Rural 21 23,553,062 3% 0.42 10 1.2% Urban By Bedsize 0-49 beds 3 490,590 0% 0.27 2 -7.8% 50-99 beds 2 4,272,521 0% 0.27 2 -7.3% 100-199 beds 16 76,422,657 1% 0.43 8 -5.2% 200-299 beds 18 72,260,688 9% 0.85 32 -5.5% 300-499 beds 18 146,532,270 9% 0.46 19 -9.6% 500 or more beds 22 506,668,660 18% 0.41 29 -9.2% Rural By Bedsize 0-49 beds 5 4,376,182 1% 0.56 12 -1.5% 50-99 beds 6 6,596,429 1% 0.83 9 -0.9% 100-149 beds 3 1,686,480 0% 0.05 5 1.7% 150 or more beds 7 10,893,971 1% 6.09 12 2.5% Type of Ownership State government 3 26,769,580 3% 0.26 59 -36.5% County or local government 7 95,443,292 11% 1.02 62 -3.8% Gov. - hosp. dist. 0 - - - - - Not-for-profit 87 695,744,108 84% 0.44 35 -7.1% For-profit 3 12,243,466 1% 0.75 16 -8.5% Teaching Status Non- teaching 45 93,689,659 11% 0.45 12 -3.7% Fewer than 10 residents 9 18,642,156 2% 0.36 11 -2.0% Residents >10 and <100 16 83,116,200 10% 0.42 22 -8.6% Residents => 100 and < 250 18 338,964,606 41% 0.60 73 -9.2% Residents => 250 12 295,787,826 36% 0.38 64 -10.4% Low-Income Patient Gross Days as % of Total Days More than 60% 5 113,298,297 14% 3.35 202 6.0% 50-60 % 9 162,884,405 20% 0.53 138 -22.6% 40-50 % 11 248,427,182 30% 0.70 94 -9.8% 30-40 % 22 204,527,958 25% 0.45 58 -10.2% 20-30 % 42 98,045,394 12% 0.28 19 -7.8% 10-20 % 11 3,017,210 0% 0.02 0 -2.4% 10 % and less 0 0 0% 0.00 0 -7.7% Low-Income Patient Gross Revenues as % of Total Patient Revenues More than 60% 1 45,634,579 5% 1.42 248 4.1% 50-60 % 5 83,462,839 10% 0.93 149 -5.0% 40-50 % 15 311,578,022 38% 0.62 97 -12.0% 30-40 % 18 247,822,381 30% 0.45 60 -12.4% 20-30 % 28 85,040,737 10% 0.45 20 -5.9% 10-20 % 32 56,534,849 7% 0.16 8 -5.8% 10 % and less 1 127,041 0% 0.00 0 -3.9% Financial Risk More than 25 % 1 15,947,743 2% 0.29 81 -38.4% 20-25 % 8 146,890,863 18% 0.42 113 -20.2% 15-20 % 5 155,706,021 19% 0.66 105 -6.4% 10-15 % 12 216,684,603 26% 0.62 81 -13.9% 5-10 % 44 199,133,297 24% 0.30 23 -7.1% 0-5 % 23 42,469,722 5% 0.24 6 -3.8% None 7 53,368,198 6% -1.96 37 -0.3% Safety Net Hospitals:Margin Net of DSH Less than -25% 21 374,233,546 45% 0.53 95 -24.0% -15 to -25% 14 163,123,554 20% 0.67 77 -11.0% -5% to -15% 32 211,097,758 25% 0.54 44 -4.3% -5% to 5% 22 78,728,378 9% 0.54 33 2.7% 5% to 15% - - - - - From 15% to25% - - - - - 25% and higher - - - - - All Safety Net Hospitals 89 827,183,237 100% 0.55 63 -9.8% TableD.2B
New York Hospitals
DSH Payments Based on Percent Low-income RevenuesN Receiving DSH DSH Funds $ % of DSH Funds DSH to Fin Risk DSH Per Adjusted Day ($) Margin w/ DSH All Hospitals 106 830,200,447 100% 0.46 37 -7.8% By Geographic Area Urban 79 791,090,467 95% 0.45 39 -8.5% Large Urban 63 765,821,307 92% 0.47 48 -9.3% Other Urban 16 25,269,160 3% 0.19 6 -3.8% Rural 27 39,109,980 5% 0.70 16 2.5% Urban By Bedsize 0-49 beds 3 5,997,362 1% 3.35 30 -0.9% 50-99 beds 4 5,886,145 1% 0.59 12 -6.6% 100-199 beds 16 64,529,695 8% 0.72 27 -6.0% 200-299 beds 19 90,043,076 11% 0.58 23 -4.9% 300-499 beds 16 148,184,649 18% 0.41 30 -9.6% 500 or more beds 21 476,449,540 57% 0.42 58 -9.6% Rural By Bedsize 0-49 beds 8 6,873,409 1% 0.88 19 0.3% 50-99 beds 10 19,903,949 2% 2.51 28 4.8% 100-149 beds 3 4,127,901 0% 0.13 11 2.9% 150 or more beds 6 8,204,721 1% 4.59 9 2.0% Type of Ownership State government 3 15,176,932 2% 0.15 34 -39.4% County or local government 9 90,705,455 11% 0.96 59 -4.6% Gov. - hosp. dist. 0 - - - - - Not-for-profit 90 714,286,894 86% 0.45 36 -7.0% For-profit 4 10,031,165 1% 0.61 13 -9.0% Teaching Status Non- teaching 53 109,052,793 13% 0.52 14 -3.3% Fewer than 10 residents 8 14,470,474 2% 0.28 8 -2.3% Residents >10 and <100 15 102,172,368 12% 0.52 27 -8.0% Residents => 100 and < 250 18 326,825,661 39% 0.58 70 -9.5% Residents => 250 12 277,679,151 33% 0.35 60 -10.7% Low-Income Patient Gross Days as % of Total Days More than 60% 5 81,200,732 10% 2.40 145 0.4% 50-60 % 9 129,319,867 16% 0.42 110 -26.0% 40-50 % 11 240,197,914 29% 0.68 90 -10.2% 30-40 % 21 204,296,193 25% 0.45 58 -10.2% 20-30 % 32 119,278,339 14% 0.35 23 -7.3% 10-20 % 27 55,174,433 7% 0.28 8 -1.3% 10 % and less 1 732,969 0% 0.01 0 -7.7% Low-Income Patient Gross Revenues as % of Total Patient Revenues More than 60% 1 34,369,958 4% 1.07 187 -2.2% 50-60 % 5 77,412,846 9% 0.86 138 -6.1% 40-50 % 15 322,756,368 39% 0.64 101 -11.5% 30-40 % 20 273,163,031 33% 0.50 67 -11.8% 20-30 % 38 104,575,369 13% 0.55 24 -5.3% 10-20 % 27 17,922,875 2% 0.05 2 -6.5% 10 % and less 0 - - - - -3.9% Financial Risk More than 25 % 1 21,398,241 3% 0.39 108 -33.3% 20-25 % 8 134,352,525 16% 0.39 104 -21.4% 15-20 % 5 153,387,370 18% 0.65 103 -6.5% 10-15 % 13 206,259,824 25% 0.59 77 -14.4% 5-10 % 42 192,186,070 23% 0.29 22 -7.2% 0-5 % 28 79,032,272 10% 0.45 11 -3.1% None 9 43,584,144 5% -1.60 30 -1.4% Safety Net Hospitals:Margin Net of DSH Less than -25% 19 357,474,269 43% 0.50 91 -24.6% -15 to -25% 12 120,826,112 15% 0.50 57 -13.3% -5% to -15% 31 232,717,221 28% 0.59 48 -3.9% -5% to 5% 16 63,275,443 8% 0.44 27 2.0% 5% to 15% - - - - - From 15% to25% - - - - - 25% and higher - - - - - All Safety Net Hospitals 78 774,293,044 93% 0.52 59 -10.2% Table D.2C
New York Hospitals
DSH Payments Based on Financial Risk as % Operating CostN Receiving DSH DSH Funds $ % of DSH Funds DSH to Fin Risk DSH Per Adjusted Day ($) Margin w/ DSH All Hospitals 102 830,200,447 100% 0.46 37 -7.8% By Geographic Area Urban 84 807,707,326 97% 0.46 40 -8.4% Large Urban 66 784,235,150 94% 0.48 49 -9.2% Other Urban 18 23,472,176 3% 0.18 6 -3.8% Rural 18 22,493,120 3% 0.40 9 1.1% Urban By Bedsize 0-49 beds 1 19,922 0% 0.01 0 -8.4% 50-99 beds 7 2,631,671 0% 0.27 5 -8.0% 100-199 beds 19 32,094,128 4% 0.36 13 -8.3% 200-299 beds 14 58,839,631 7% 0.38 15 -6.0% 300-499 beds 21 166,814,595 20% 0.46 34 -9.1% 500 or more beds 22 547,307,379 66% 0.48 67 -8.8% Rural By Bedsize 0-49 beds 50-99 beds 100-149 beds 6 5,351,540 1% 0.69 15 -0.8% 150 or more beds 4 5,203,052 1% 2.91 6 -1.5% Type of Ownership State government 3 39,345,039 5% 0.38 87 -33.5% County or local government 7 112,376,421 14% 1.20 74 -1.2% Gov. - hosp. dist. 0 - - - - - Not-for-profit 89 674,123,720 81% 0.42 34 -7.2% For-profit 3 4,355,267 1% 0.27 6 -10.3% Teaching Status Non- teaching 0 - - - - - Fewer than 10 residents 50 58,133,939 7% 0.28 8 -4.6% Residents >10 and <100 6 18,596,540 2% 0.36 11 -2.0% Residents => 100 and < 250 17 75,558,051 9% 0.38 20 -8.9% Residents => 250 16 338,111,334 41% 0.60 73 -9.2% Low-Income Patient Gross Days as % of Total Days More than 60% 4 38,250,746 5% 1.13 68 -8.1% 50-60 % 8 183,617,459 22% 0.60 156 -20.5% 40-50 % 10 269,807,707 32% 0.76 102 -8.8% 30-40 % 16 143,264,817 17% 0.32 40 -11.7% 20-30 % 27 122,811,630 15% 0.36 23 -7.2% 10-20 % 26 45,430,725 5% 0.23 7 -1.5% 10 % and less 11 27,017,363 3% 0.22 11 -6.6% Low-Income Patient Gross Revenues as % of Total Patient Revenues More than 60% 1 26,567,283 3% 0.83 144 -7.0% 50-60 % 5 56,165,123 7% 0.63 100 -10.3% 40-50 % 12 368,494,554 44% 0.73 115 -9.7% 30-40 % 15 238,126,558 29% 0.43 58 -12.7% 20-30 % 19 46,043,492 6% 0.24 11 -7.2% 10-20 % 42 89,092,876 11% 0.26 12 -5.2% 10 % and less 8 5,710,561 1% 0.06 2 -3.7% Financial Risk More than 25 % 1 48,487,196 6% 0.88 246 -12.9% 20-25 % 8 229,503,146 28% 0.66 177 -13.1% 15-20 % 5 180,564,053 22% 0.76 121 -4.3% 10-15 % 13 196,200,318 24% 0.56 73 -14.9% 5-10 % 75 175,445,734 21% 0.26 21 -7.4% 0-5 % 0 - 0% 0.00 0 -4.6% None 0 - 0% 0.00 0 -6.6% Safety Net Hospitals:Margin Net of DSH Less than -25% 20 450,185,725 54% 0.63 115 -21.5% -15 to -25% 13 120,205,726 14% 0.49 57 -13.3% -5% to -15% 19 138,341,804 17% 0.35 29 -5.8% -5% to 5% 13 49,019,103 6% 0.34 21 1.4% 5% to 15% - - - - - From 15% to25% - - - - - 25% and higher - - - - - All Safety Net Hospitals 65 757,752,359 91% 0.51 57 -10.4% Table D.2D
New York Hospitals
Sliding Scale DSH Payments Based on Financial RiskN Receiving DSH DSH Funds $ % of DSH Funds DSH to Fin Risk Adjusted Day ($) Margin w/ DSH All Hospitals 102 830,200,447 100% 0.46 37 -7.8% By Geographic Area Urban 84 813,785,241 98% 0.46 40 -8.3% Large Urban 66 797,704,343 96% 0.49 50 -9.1% Other Urban 18 16,080,898 2% 0.12 4 -4.1% Rural 18 16,415,206 2% 0.29 7 0.6% Urban By Bedsize 0-49 beds 1 13,275 0% 0.01 0 -8.4% 50-99 beds 7 1,753,609 0% 0.18 3 -8.4% 100-199 beds 19 25,181,223 3% 0.28 10 -8.8% 200-299 beds 14 52,203,597 6% 0.15 14 -6.2% 300-499 beds 21 182,717,779 22% 0.16 37 -8.7% 500 or more beds 22 551,915,758 66% 0.49 67 -8.7% Rural By Bedsize 0-49 beds 0.6% 50-99 beds 0 -7.8% 100-149 beds 6 3,884,666 0% 0.50 10 -1.9% 150 or more beds 4 4,575,324 1% 2.56 5 -1.8% Type of Ownership State government 3 41,674,833 5% 0.41 92 -32.9% County or local government 7 130,589,383 16% 1.39 85 1.6% Gov. - hosp. dist. 0 - - - - Not-for-profit 89 654,956,661 79% 0.41 33 -7.3% For-profit 3 2,979,570 0% 0.18 4 -10.7% Teaching Status Non- teaching 0 - - - - - Fewer than 10 residents 50 40,682,103 5% 0.20 24 -5.0% Residents >10 and <100 6 15,663,200 2% 0.30 4 -2.2% Residents => 100 and < 250 17 61,592,795 7% 0.31 13 -9.4% Residents => 250 16 355,706,165 43% 0.63 76 -8.8% Low-Income Patient Gross Days as % of Total Days More than 60% 4 36,962,270 4% 1.09 66 -8.4% 50-60 % 8 250,883,191 30% 0.82 213 -14.4% 40-50 % 10 260,183,065 31% 0.73 98 -9.3% 30-40 % 16 117,185,150 14% 0.26 33 -12.4% 20-30 % 27 116,392,446 14% 0.34 22 -7.4% 10-20 % 26 30,591,356 4% 0.16 5 -1.8% 10 % and less 11 18,002,969 2% 0.15 7 -6.9% Low-Income Patient Gross Revenues as % of Total Patient Revenues More than 60% 1 25,459,103 3% 0.79 138 -7.8% 50-60 % 5 58,755,720 7% 0.66 105 -9.8% 40-50 % 12 438,534,103 53% 0.87 137 -7.0% 30-40 % 20 4,097,775.00 18% 548,956,584 15 211,149,290 20-30 % 38 4,358,125.00 19% 190,041,988 19 30,999,673 10-20 % 73 7,228,675.00 32% 348,071,669 42 61,497,337 10 % and less 36 2,903,713.00 13% 95,621,757 8 3,805,221 Financial Risk More than 25 % 1 197,289.00 1% 55,413,272 1 71,890,843 20-25 % 8 1,297,053.00 6% 347,381,295 8 325,150,036 15-20 % 5 1,486,924.00 7% 236,278,852 5 167,913,905 10-15 % 13 2,684,243.00 12% 351,032,344 13 148,337,726 5-10 % 75 8,545,262.00 38% 670,811,230 75 116,907,937 0-5 % 72 6,885,625.00 31% 174,630,253 0 0 None 14 1,436,744.00 6% -27,201,393 0 0 Safety Net Hospitals:Margin Net of DSH Less than -25% 21 3,927,171.00 17% 709,022,141 20 513,005,145 -15 to -25% 15 2,122,513.00 9% 243,472,749 13 96,754,035 -5% to -15% 32 4,817,718.00 21% 392,877,367 19 129,944,493 -5% to 5% 22 2,357,507.00 10% 145,436,925 13 41,902,449 5% to 15% 0 - - - - From 15% to25% 0 - - - - 25% and higher 0 - - - - All Safety Net Hospitals 90 13,224,909.00 59% 1,490,809,181 65 781,606,121 Table D.3A
Wisconsin Hospitals
DSH Payments Based on Percent Low-income UtilizationN Receiving DSH DSH Funds $ % of DSH Funds DSH to Fin Risk DSH Per Adjusted Day ($) Margin w/ DSH All Hospitals 13 36,983,376 100% 0.09 7 6.4% By Geographic Area Urban 7 27,104,556 73% 0.08 9 6.1% Large Urban 4 23,009,488 62% 0.15 18 4.6% Other Urban 3 4,095,068 11% 0.02 2 7.1% Rural 6 9,878,819 27% 0.13 5 7.6% Urban By Bedsize 0-49 beds 0 - - - - 6.2% 50-99 beds 0 - - - - 7.1% 100-199 beds 2 4,404,863 12% 0.23 14 9.4% 200-299 beds 1 3,234,284 9% 0.05 6 5.2% 300-499 beds 2 2,950,770 8% 0.03 3 6.6% 500 or more beds 2 16,514,640 45% 0.13 23 4.5% Rural By Bedsize 0-49 beds 4 6,038,653 16% 0.31 6 5.2% 50-99 beds 1 3,420,859 9% 0.12 6 7.3% 100-149 beds 1 419,307 1% 0.04 2 8.8% 150 or more beds Type of Ownership State government 0 - - - - 3.8% County or local government 0 - - - - 9.5% Gov. - hosp. dist. 0 - - - - - Not-for-profit 13 36,983,376 100% 0.10 8 6.5% For-profit 0 - - - - - Teaching Status Non- teaching 7 11,023,118 30% 0.08 4 6.6% Fewer than 10 residents 3 6,211,334 17% 0.13 12 10.5% Residents >10 and <100 1 3,234,284 9% 0.03 3 5.9% Residents => 100 and < 250 2 16,514,640 45% 0.19 60 3.1% Residents => 250 0 - - - - 3.8% Low-Income Patient Gross Days as % of Total Days More than 60% 1 3,260,565 9% 1.24 187 18.3% 50-60 % 0 0 0% - - - 40-50 % 1 3,420,859 9% 2.28 97 13.0% 30-40 % 6 24,782,789 67% 0.25 51 3.8% 20-30 % 5 5,519,163 15% 0.17 13 2.0% 10-20 % 0 - - - - 6.3% 10 % and less 0 - - - - 8.0% Low-Income Patient Gross Revenues as % of Total Patient Revenues More than 60% 0 - - - - - 50-60 % 0 - - - - - 40-50 % 2 9,056,474 24% 0.16 80 -3.2% 30-40 % 1 2,316,574 6% 0.33 32 -0.5% 20-30 % 1 10,718,731 29% 0.32 42 7.2% 10-20 % 9 14,891,598 40% 0.16 11 3.2% 10 % and less 0 - - - - 7.8% Financial Risk More than 25 % 0 - - - - - 20-25 % 0 - - - - - 15-20 % 1 5,795,909 16% 0.11 61 -5.3% 10-15 % 3 5,601,177 15% 0.53 37 3.9% 5-10 % 8 22,165,431 60% 0.13 12 6.2% 0-5 % 1 3,420,859 9% 0.02 1 7.2% None 0 - - - - - Safety Net Hospitals:Margin Net of DSH Less than -25% 0 - - - - - -15 to -25% 0 - - - - - -5% to -15% 2 8,112,483 22% 0.13 49 -4.4% -5% to 5% 9 27,244,248 74% 0.41 43 5.5% 5% to 15% 2 1,626,645 4% 0.21 9 10.6% From 15% to25% 0 - - - - - 25% and higher 0 - - - - - All Safety Net Hospitals 13 36,983,376 100% 0.27 38 3.7% Table D.3B
Wisconsin Hospitals
DSH Payments Based on Percent Low-income RevenuesN Receiving DSH DSH Funds $ % of DSH Funds DSH to Fin Risk DSH Per Adjusted Day ($) Margin w/ DSH All Hospitals 14 36,983,199 100% 0.09 7 6.4% By Geographic Area Urban 7 32,450,940 88% 0.10 11 6.2% Large Urban 4 25,294,087 68% 0.16 20 4.7% Other Urban 3 7,156,854 19% 0.04 4 7.3% Rural 7 4,532,258 12% 0.06 2 7.2% Urban By Bedsize 0-49 beds 0 0 0% 0.00 0 6.2% 50-99 beds 0 0 0% 0.00 0 7.1% 100-199 beds 2 3,524,409 10% 0.18 12 9.2% 200-299 beds 0 0 0% 0.00 0 4.8% 300-499 beds 3 6,619,973 18% 0.07 6 6.9% 500 or more beds 2 22,306,558 60% 0.18 31 5.0% Rural By Bedsize 0-49 beds 6 4,528,472 12% 0.23 4 4.7% 50-99 beds 0 0 0% 0.00 0 6.5% 100-149 beds 1 3,786 0% 0.00 0 8.5% 150 or more beds Type of Ownership State government 0 - - - - 3.8% County or local government 0 - - - - 9.5% Gov. - hosp. dist. 0 - - - - - Not-for-profit 14 36,983,199 100% 0.10 8 6.5% For-profit 0 0 - - - - Teaching Status Non- teaching 8 5,286,765 14% 0.04 2 6.4% Fewer than 10 residents 3 9,172,248 25% 0.19 17 10.9% Residents >10 and <100 1 217,626 1% 0.00 0 5.7% Residents => 100 and < 250 2 22,306,558 60% 0.26 81 4.2% Residents => 250 0 - - - - 3.8% Low-Income Patient Gross Days as % of Total Days More than 60% 1 2,769,902 7% 1.05 159 15.8% 50-60 % 0 0 - - - - 40-50 % 0 0 0% 0.00 0 1.0% 30-40 % 6 30,773,653 83% 0.32 63 4.8% 20-30 % 5 1,978,447 5% 0.06 5 0.9% 10-20 % 2 1,461,197 4% 0.01 1 6.4% 10 % and less 0 - - - - 8.0% Low-Income Patient Gross Revenues as % of Total Patient Revenues More than 60% 0 - - - - - 50-60 % 0 - - - - - 40-50 % 2 15,837,168 43% 0.28 141 0.3% 30-40 % 1 6,282,418 17% 0.89 88 7.9% 20-30 % 3 11,360,609 31% 0.34 45 7.4% 10-20 % 8 3,503,003 9% 0.04 3 2.3% 10 % and less 0 - - - - 7.8% Financial Risk More than 25 % 0 0 - - - - 20-25 % 0 0 - - - - 15-20 % 1 13,067,266 35% 0.25 137 -1.1% 10-15 % 3 9,816,878 27% 0.93 66 9.5% 5-10 % 8 12,637,857 34% 0.07 7 5.8% 0-5 % 2 1,461,197 4% 0.01 0 7.1% None 0 - - - - - Safety Net Hospitals:Margin Net of DSH Less than -25% 0 - - - - - -15 to -25% 0 - - - - - -5% to -15% 2 19,349,685 52% 0.32 116 0.8% -5% to 5% 8 15,956,103 43% 0.24 25 3.9% 5% to 15% 2 216,215 1% 0.03 1 9.1% From 15% to25% 0 - - - - - 25% and higher 0 - - - - - All Safety Net Hospitals 12 35,522,002 96% 0.26 37 3.6% Table D.3C
Wisconsin Hospitals
DSH Payments Based on Financial Risk as % Operating CostN Receiving DSH DSH Funds $ % of DSH Funds DSH to Fin Risk DSH Per Adjusted Day ($) Margin w/ DSH All Hospitals 46 36,983,199 100% 0.09 7 6.4% By Geographic Area Urban 19 27,394,826 74% 0.08 9 6.1% Large Urban 8 16,667,393 45% 0.11 13 4.3% Other Urban 11 10,727,434 29% 0.06 6 7.4% Rural 27 9,588,372 26% 0.12 4 7.5% Urban By Bedsize 0-49 beds 2 468,415 1% 0.14 3 7.0% 50-99 beds 2 25,538 0% 0.00 0 7.1% 100-199 beds 2 1,823,764 5% 0.10 6 8.8% 200-299 beds 4 5,163,204 14% 0.08 9 5.4% 300-499 beds 5 5,867,949 16% 0.06 5 6.8% 500 or more beds 4 14,045,956 38% 0.11 20 4.3% Rural By Bedsize 0-49 beds 16 7,359,904 20% 0.37 7 5.7% 50-99 beds 8 1,596,116 4% 0.06 3 6.8% 100-149 beds 2 595,705 2% 0.06 3 8.9% 150 or more beds Type of Ownership State government 0 - - - - 3.8% County or local government 1 19,220 - - - 9.5% Gov. - hosp. dist. 0 - - - - - Not-for-profit 45 36,963,979 100% 0.10 8 6.5% For-profit 0 - - - - - Teaching Status Non- teaching 34 12,119,230 33% 0.09 4 6.6% Fewer than 10 residents 5 6,789,195 18% 0.14 13 10.6% Residents >10 and <100 5 4,910,662 13% 0.05 5 6.0% Residents => 100 and < 250 2 13,164,111 36% 0.15 48 2.4% Residents => 250 0 - 0% 0.00 0 3.8% Low-Income Patient Gross Days as % of Total Days More than 60% 1 1,083,196 3% 0.41 62 6.2% 50-60 % 0 - - - - - 40-50 % 0 - 0% 0.00 0 1.0% 30-40 % 6 17,937,949 49% 0.18 37 2.7% 20-30 % 9 8,310,985 22% 0.25 19 2.8% 10-20 % 27 9,601,824 26% 0.05 3 6.6% 10 % and less 3 49,246 - - - 8.0% Low-Income Patient Gross Revenues as % of Total Patient Revenues More than 60% 0 - - - - - 50-60 % 0 - - - - - 40-50 % 2 11,843,642 32% 0.21 105 -1.8% 30-40 % 1 3,657,925 10% 0.52 51 2.5% 20-30 % 2 2,778,255 8% 0.08 11 4.9% 10-20 % 24 14,750,042 40% 0.16 11 3.2% 10 % and less 17 3,953,335 11% 0.02 1 7.9% Financial Risk More than 25 % 0 - - - - - 20-25 % 0 - - - - - 15-20 % 1 10,760,446 29% 0.20 113 -2.4% 10-15 % 3 7,817,236 21% 0.74 52 6.9% 5-10 % 42 18,405,516 50% 0.11 10 6.1% 0-5 % 0 - - - - 7.1% None 0 - - - - - Safety Net Hospitals:Margin Net of DSH Less than -25% 0 - - - - - -15 to -25% 0 - - - - - -5% to -15% 2 14,418,371 39% 0.24 86 -1.4% -5% to 5% 9 11,006,044 30% 0.16 18 3.1% 5% to 15% 5 1,907,714 5% 0.25 11 10.9% From 15% to25% 0 - - - - - 25% and higher 0 - - - - - All Safety Net Hospitals 16 27,332,129 74% 0.20 28 2.8% TableD.3D
Wisconsin Hospitals
Sliding Scale DSH Payments Based on Financial RiskN Receiving DSH DSH Funds $ % of DSH Funds DSH to Fin Risk DSH Per Adjusted Day ($) Margin w/ DSH All Hospitals 46 36,983,199 100% 0.09 7 6.4% By Geographic Area Urban 19 28,229,325 76% 0.09 9 6.1% Large Urban 8 18,460,779 50% 0.12 14 4.4% Other Urban 11 9,768,546 26% 0.06 6 7.4% Rural 27 8,753,874 24% 0.11 4 7.5% Urban By Bedsize 0-49 beds 2 418,333 1% 0.12 3 6.9% 50-99 beds 2 22,808 0% 0.00 0 7.1% 100-199 beds 2 1,738,454 5% 0.09 6 8.8% 200-299 beds 4 4,611,165 12% 0.07 8 5.3% 300-499 beds 5 5,428,627 15% 0.05 5 6.8% 500 or more beds 4 16,009,938 43% 0.13 22 4.5% Rural By Bedsize 0-49 beds 16 6,763,668 18% 0.34 7 5.5% 50-99 beds 8 1,425,463 4% 0.05 2 6.8% 100-149 beds 2 532,014 1% 0.05 2 8.9% 150 or more beds Type of Ownership State government 0 0 0% 0.00 0 3.8% County or local government 1 17,165 0% 0.00 0 9.5% Gov. - hosp. dist. 0 0 - - - - Not-for-profit 45 36,966,034 100% 0.10 8 6.5% For-profit 0 0 - - - - Teaching Status Non- teaching 34 11,014,138 30% 0.08 4 6.6% Fewer than 10 residents 5 6,361,059 17% 0.13 12 10.5% Residents >10 and <100 5 4,385,624 12% 0.04 4 5.9% Residents => 100 and < 250 2 15,222,378 41% 0.18 55 2.8% Residents => 250 0 - - - - 3.8% Low-Income Patient Gross Days as % of Total Days More than 60% 1 1,077,066 3% 0.41 62 6.1% 50-60 % 0 0 - - - - 40-50 % 0 0 0% 0.00 0 1.0% 30-40 % 6 19,673,874 53% 0.20 41 3.0% 20-30 % 9 7,613,062 21% 0.23 18 2.6% 10-20 % 27 8,575,216 23% 0.04 3 6.6% 10 % and less 3 43,980 0% 0.00 0 8.0% Low-Income Patient Gross Revenues as % of Total Patient Revenues More than 60% 0 - - - - - 50-60 % 0 - - - - - 40-50 % 2 14,152,775 38% 0.25 126 -0.5% 30-40 % 1 3,454,894 9% 0.49 48 2.1% 20-30 % 2 2,481,210 7% 0.07 10 4.8% 10-20 % 24 13,363,668 36% 0.14 10 3.1% 10 % and less 17 3,530,652 10% 0.02 1 7.9% Financial Risk More than 25 % 0 - - - - - 20-25 % 0 - - - - - 15-20 % 1 13,075,709 35% 0.25 137 -1.1% 10-15 % 3 7,469,854 20% 0.71 50 6.5% 5-10 % 42 16,437,636 44% 0.09 9 6.0% 0-5 % 0 - - - - 7.1% None 0 - - - - - Safety Net Hospitals:Margin Net of DSH Less than -25% - - - - - -15 to -25% 0 - - - - - -5% to -15% 2 16,530,603 45% 0.27 99 -0.5% -5% to 5% 9 10,129,654 27% 0.15 16 3.0% 5% to 15% 5 1,703,745 5% 0.22 10 10.6% From 15% to25% 0 - - - - - 25% and higher 0 - - - - - All Safety Net Hospitals 16 28,364,002 77% 0.21 29 2.9%
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Appendix E. Federal Support for Uncompensated Care Costs Incurred by Ambulatory Care Providers
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Overview
The focus of our project is on federal support to financially vulnerable safety net hospitals. Public hospitals provided about 30 million ambulatory visits in 2000, about half of which were for primary care (NAPH, 2001). Uncompensated care costs associated with these visits as well as those for ambulatory care provided by other hospitals were taken into account in our evaluation of alternative DSH funding policies. However, one of the project's task was also to consider the role of non-hospital ambulatory care providers also play an important role in the safety net for low-income populations. The IOM report, America's Health Care Safety Net: Intact but Endangered, identifies the following classes of ambulatory care providers as core safety net providers(1):
- Community health centers
- Local health departments
- School-based health clinics
- Private practitioners
Support for services furnished by these providers comes from federal, state and local sources. In the first section that follows, we briefly summarize the contribution of these non-hospital ambulatory care providers to the safety net and their sources of funding. Where available, we include an estimate of current federal support for their services and/or uncompensated care costs. We follow with a discussion of our findings related to a review of initiatives to improve the access of the uninsured to ambulatory care. We conclude with a summary of issues related to funding the uncompensated care costs of community safety net providers.
What Role Do Community Safety Net Providers Play in Caring for the Uninsured?
Community Health Centers
Community health centers are private, non-profit organizations that receive public funding to furnish primary and preventive services to medically underserved populations (Dievler, 1998). Federally qualified health centers (FQHCs) must offer a sliding fee scale and provide services regardless of ability to pay (IOM, 2000). In 1998, they served approximately 9 percent of Medicaid beneficiaries, 8 percent of the uninsured, and 19 percent of the population living in medically underserved areas lacking access to primary care physicians (BPHC, 2000). Section 330 of the Public Health Service Act authorizes grant funding to four categories of health centers: community health centers, migrant health programs, organizations providing healthcare for the homeless, and centers providing primary care to residents of public housing. In 2000, 730 centers received Section 330 grants. Of the 9.6 million persons that were served in by these organizations, 33.6 % were covered by Medicaid and 40.2 % were uninsured (Table E.1).
Table E.1
Source of Third-Party Insurance Coverage: CY2000 HRSA Grantees (N= 730)Principal Insurance Source N Users % Users % of Collected Patient Fees None 3,859,036 40.2 11.0 Medicaid 3,221,673 33.6 62.4 Medicare 695,339 7.2 10.4 Other public insurance 338,688 3.5 4.3 Private Insurance 1,485,422 15.5 11.9 TOTAL 9,600,158 100.0 100.0 Source: HRSA Uniform Data System, 2001. Table E.2
Total CY2000 Revenues Received by HRSA Grantees By Source (N=730):Amount ($millions) Percent of Total Federal grant revenue 975.0 24.79 Migrant health center 68.1 1.73 Community health center 720.3 18.31 Health care for the homeless 66.4 1.69 Homeless Children 2.1 .05 Public housing primary care 8.9 .23 Healthy Schools, Healthy Communities 8.2 .21 Ryan White 38.3 .97 Other federal grants 62.6 1.59 Non-Federal Grants or Contracts 547.0 13.91 State grants and contracts 262.2 6.67 Local government grants and contracts 166.9 4.24 Foundation/private grants and contracts 117.9 3.00 Other Non-Patient Care Related Revenue 125.3 3.19 Patient Care Revenues 2,152.6 54.73 Self-pay 236.5 6.01 Medicaid 1,343.8 34.17 Medicare 222.8 5.66 Other Public 92.7 2.36 Private third party 256.7 6.53 Revenue from Indigent Care Programs 133.3 3.39 Total Revenue 3,933.1 100.0 The average user had 4.0 encounters for an average total cost of $406.14. Total costs for the 730 grantees under Section 330 were $3.9 billion. Collections on patient fees
totaled $2.15 billion, of which $1.3 billion was collected from Medicaid (62.4% of total collected fees). Based on the average total cost of $406.14 and 3,859,036 visits, total costs of providing care to the uninsured is estimated at $1.567 billion. Collections from self-pay users totaled $236.5 million, for a net cost of $1.331 billion prior to consideration of revenues from indigent care programs and grants.
Table E.2 summarizes the funding sources to support the 730 grantees. The FQHCs rely on a patch-work of federal grants to provide about 25% of their support (with the bulk coming from CHC funding). The diversity of funding streams has been seen as both administratively burdensome to the FQHCs and protection if funding is cut in one or more programs (IOM, 2000). Medicaid provided 34% of funding in 2000. Effective January 1, 2001, Medicaid reasonable cost reimbursement to FQHCs was repealed and replaced by a new prospective payment system based on historical Medicaid costs adjusted for changes in scope of services.(2) The new payment system will reduce the stability of Medicaid support for FQHC care.
There are also 111 FQHC "look-alikes" that meet the requirements of the Section 330 grant program but do not receive grants. The "look alikes" operate in 182 sites and provide primary care services to over 1,120,000 users (BPHC, 2001a). In addition, there are community-based primary care clinics funded with state and local grants that provide care to the uninsured and low-income populations but do not meet Section 330 requirements. National estimates are not available regarding the uninsured population served by these clinics.
Local Health Departments
Table E.3
Direct Care Services Provided by Local Health Departments: 1998Service % Providing Immunizations 96 Well-child clinic 79 WIC 78 Medicaid EPDST 72 STD testing 71 Family planning 68 School-based clinics 25 Source: IOM, 2000. The core public health functions that local health departments are responsible for include linking people to needed personal health services and ensuring the provision of health care when it is otherwise unavailable. Many departments provide direct care to vulnerable populations and specialize in providing free care to populations with special needs (e.g. HIV, drug dependence) (IOM, 2000). Table E.3 summarizes the services and percentage of local health departments providing them in 1998. Funding for local health departments comes from state (40%) and local (37%) government, Medicaid (7%) and categorical federal funding (6%). There is some evidence that direct care services are declining with the growth of Medicaid managed care and less reliance on local health departments as Medicaid providers (IOM, 2000).
School-Based Health Centers
School-based health center (SBHC) programs have grew rapidly during the last decade from about 150 centers in 1990 to an estimated 1300 in 2000 (Morone, 2001). While the centers differ in scope of services, staffing, and funding, they generally consist of a multi-disciplinary team providing a comprehensive range of services that specifically meet the health care needs of young people in the community (CHHCS, 2001).
Initial growth in SBHCs was supported by funding from the Robert Wood Johnson Foundation's "Making the Grade: State and Local Partnerships to Establish School-Based Health Centers " and has been spurred more recently by increased funding from government sources. For the 1997-1998 school year, total funding from state, federal and third party collections totaled $53.5 million (Table E.4). The two main sources of federal funds were state-directed Maternal and Child Health grants and direct grants under the Health Schools/Healthy Communities program. Support from local communities is substantial but has not been estimated at the national level.(3) In addition, foundations continue to provide support (CHHCS, 2001a).
Table E.4
Federal, State and Third Party Support for School-based Health Centers, 1997-1998
In Millions $State Funds $46.1 State General Fund $29.6 Other State support 7.2 Third Party Collections 9.4 ` Est. Medicaid FFS 8.2 Est. Medicaid MCO 0.7 Est. Commercial 0.5 Federal Funds 17.3 MCH Block Grant 9.3 Healthy Schools/ Healthy Communities 8.0 Total $53.5 Source: National Survey of School-Based Health Centers A qualified health care provider is responsible for the clinical services furnished by SBHCs. The sponsors of the staff are:
- Hospitals -- 29%
- Health depts. -- 22%
- CHCs -- 18%
- Non-profit health organizations -- 11%
- School systems -- 9%
- Medical and nursing schools -- 6%
- All other -- 4%
(National Assembly, 1999)
National estimates of the care furnished to the uninsured by the school-based clinics have not been made. The estimates are hindered by the policy of many SBHCs to furnish services free of charge to all students seeking care. However, the Centers for Medicare and Medicaid Services policies on "free care" and third-party liability have made it problematic to obtain Medicaid payment without charging other third-party payers (Morone, 2001; National Assembly, 2001; Schneider, 2001). Many states are now encouraging SBHCs to pursue third-party collections (including Medicaid) and to use federal and state grants for the uninsured. There is, however, considerable burden associated with obtaining valid insurance information and establishing billing and collection procedures (National Assembly, 2001).
SBHCs may participate in Medicaid in all but three states: Arizona, Hawaii, and Oklahoma. (CHHCS, 2001). Within the context of the current project, state policies regarding how the school-based health centers are viewed by Medicaid are most pertinent.
- In some states, the school-based health centers are defined as non-institutional Medicaid providers. For example, the Illinois Department of Public Aid has established standards and an application process for school-based health centers seeking enrollment as a medical provider.
- A different model is used in New York. The school-based health center is treated as a sub-provider of the sponsoring institution, which can then bill for the school-based health center's services at the Medicaid all-inclusive rate (National Assembly, 2001).
Either model provides a potential mechanism for obtaining information on the center's volume of uncompensated care and for providing funding for that care. Other models, which require managed care plans to contract with SBHCs do not have the same potential.
Private Practitioners
Eighty percent of ambulatory care delivered by non-Federal physicians is provided in office-based practices (Cherry et al., 2001). The expected source of payment for the office visits in 1999 were:
- Private insurance: 55%
- Medicare: 20%
- Medicaid: 7.5%
- Self-pay: 5.4%
- No-charge: 1.0%
- Other: 10.3%
Although community health centers and hospital outpatient departments are traditionally seen as the major medical providers for vulnerable populations, physician offices provide substantial ambulatory care to low-income populations. Data from the 1996 Medical Expenditure Panel Survey indicates that 86.4 % of ambulatory visits made by the uninsured (71.4 million visits) were to office-based practices compared to 7.6% in outpatient departments and 6.0% in emergency rooms (Kirby, 2001). There is some evidence, however, that physicians in private practice tend to treat patients who are temporarily uninsured and who have income levels above 300 percent of poverty (IOM, 2000). In 1994, 78 percent of the primary care visits by patients with Medicaid or no insurance coverage were to physician offices compared to 10.6 % to community health centers and 11.5% to hospital outpatient departments. The pattern was similar in 1998 (Forrest, 2000).
Data from the 1998-1999 Community Tracking Study (CTS)(Reed, 2001) shows about 72 percent of physicians provide an average of 10.6 hours per month of charity care. Physicians who own their practice are more likely provide charity care than those who do not (81% vs. 61%). Among those least likely to provide charity care are physicians practicing in staff/group HMOs (46%) and hospital-owned settings (61%). While there is concern that the growth of managed care is reducing physician willingness to provide charity care, data from the American Medical Association's 1994 Socio-economic Monitoring Survey indicate that 67.7 percent of all physicians provided charity care, defined as care provided for free or at reduced fees due to financial need on the part of the patient. Of the physicians providing charity care, physicians spent, on average, 7.2 hours or 12.4 percent of their working hours providing charity care.
What Data Sources Are Available to Estimate Uncompensated Ambulatory Care?
National Ambulatory Medical Care Survey
The National Ambulatory Medical Care Survey (NAMCS) is a national probability sample survey related to visits to office-based physicians in the United States. The sample data are weighted to produce national estimates. The most recent survey data available are for 1999. The NAMCS collects information on the characteristics of the physician practice, the patient, and the visit. Of particular interest for purposes of this report is the series of questions related to expected source of payment and the policies of the physician practice related to treating poor patients. Some findings on office-based physician practices were discussed earlier in this. Other findings for 1999 include the following (Cherry et al., 2001):
- There were 756.7 million visits to office-based physician practices. In 95.7 percent, a physician saw the patient. The mean time spent with the physician was 19.3 minutes.
- One-third of physicians do not accept charity cases and 21.6 percent do not accept new Medicaid patients.
- Since 1985, self-pay declined from about 35 to 5% of visits.
There is no single category for uncompensated care on the survey. The self-pay category includes any patient without insurance who is expected to be ultimately responsible for the most of the bill, regardless of whether payment is actually made. Thus, it includes both those who are able to pay for the services and those who are not. The no-charge category includes visits for which no fee is charged, including not only charity care but also research and professional courtesy care.
As indicated earlier, self-pay was estimated as the source of payment for 5.4% of visits. Applying this percentage to the total number of visits to physician practices (756.7 million) yields an estimate of 40.9 million visits by the uninsured in 1999, considerably less that the estimate provided by the MEPS survey (see below). Using both the self-pay and no-charge categories raises the estimated visits to 48.4 million.
Medical Expenditure Panel Survey
The Medical Expenditure Panel Survey (MEPS) is a national survey funded by the Agency for Healthcare Research and Quality (AHRQ) to obtain a variety of measures on health care services, including sources of payment for health care expenditures (AHRQ, 2000). The survey consists of four components, two of which are particularly relevant to estimating the volume of care provided by private practitioners to the uninsured(4)
The household component collects information from a nationally representative sample of approximately 10,000 families and 24,000 individuals.
The medical care component covers approximately 17,000 physicians as well as hospitals and home health care providers. Its purpose is to supplement the information obtained from the household component.
The expenditure data on the file is developed from both the household and medical components. Pre-imputed and imputed versions of expenditure and sources of payment data are provided. Expenditures are defined as the sum of payments for care received, including out-of-pocket payments and payments by insurers and other parties. Charges associated with bad debt and charity care are not counted as health care expenditures because there are no payments associated with them. (Charges are collected in addition to expenditures, but it is not clear how they meaningful they are. Charges with no expenditures cannot be assumed to be charity care because of flat fees and bundled payments). Office-based visits are separately categorized and the payer categories include: self or family, Medicaid, and other state and local sources. The latter category includes community and neighborhood clinics, health departments, and local programs for low-income patients. Thus, MEPS does not contain direct information on charity care but does have indirect information on the expected sources of payment that can be used to make a national estimate the volume of office-based services provided to the uninsured.
As previously reported, the 1996 MEPS estimated the uninsured had 71.4 million visits to office-based practices. The estimate was based on 32.78 uninsured. For all patients, the average expense per ambulatory visit (to all categories) was $127 and the median expense was $50. The average payment by the uninsured for ambulatory care is not available from published data but could be determined from the survey data.
Community Tracking Study (CTS)
The Center for Studying Health System Change uses a set of national biennial surveys and site visits to track changes in health care systems over time and the effects of those changes on patients and providers. The Community Tracking System (CTS) collects data in 60 randomly selected communities stratified by region, community size and type (metropolitan/non-metropolitan) to provide a representative profile of change across the United States. Twelve metropolitan areas with more than 200,000 people are studied in depth, including site visits as well as larger sampling. CTS survey and site visit data for Round I spans 1996-1997, Round II from 1998-1999 and Round III from 2000-2001. The results are available from Round I and II.
The household telephone survey collects information on 60,000 individuals in 33,000 families. The questions involving insurance coverage and health care utilization could be used to estimate the volume of physician services furnished to the uninsured. In particular, the survey asks for information on insurance coverage (and changes within the past year) and use of ambulatory services within the past 12 months, including the number of physician visits. There are also questions related to income and total family out-of-pocket expenses over the past 12 months.
The physician telephone survey collects information from a nationally representative survey of 12,000 non-federal physicians who spend at least 20 hours per week in patient care. The questions are directed to the nature of the practice and its revenues. The only question that is directly related to charity care has limited utility in estimating uncompensated care costs associated with physician services. The question asks the physician to estimate the number of hours spent in the last month providing charity care. The survey defines charity care as meaning that either no fee or a reduced fee was charged because of the patient's financial need. Time spent in providing care that resulted in bad debt (payment expected but not received) or contractual allowances from Medicare and Medicaid are not to be included in the time estimate. There is no distinction between services for which no or token payment was received versus those where the fee was discounted to a level comparable to that received from third party payers such as Medicare.
The uninsured in the CTS Household Survey reported an average of two physician visits per year. Assuming 42.1 million uninsured (Kaiser, 2000) would produce an estimated 84.2 million visits to physician offices in 1999.
Public Programs Providing The Uninsured Access to Community Providers
An earlier Urban Institute study examined programs using DSH funds to provide health care services to the uninsured in five locations: Denver, CO; Indianapolis, IN; Lansing, MI; Detroit, MI; and, San Antonio, TX. These programs are viewed as innovative efforts to increase the access of the uninsured to primary care services. While the design of the programs varied substantially, the primary objective of each program was to provide a health care structure to the uninsured population by offering a service package to uninsured individuals with an established network of providers (Urban, 2001). Eligible individuals enrolled in the program. Some programs assigned participants to a primary care provider while others developed a list of specified providers that participants could use.
- Denver Health provides care through a hospital, FQHCs, school-based clinics, and the local health department. Community physicians in office-based practices are not part of the provider network. (The Colorado Indigent Care Program contracts with licensed community clinics that provide a minimum of three percent charity care).
- Wishard Memorial Hospital has historically been the safety net provider in Indianapolis. Under Wishard Advantage, the Indiana University Medical Group (IUMG), a physician group sponsored by the medical school and the Health and Hospital Corporation, provides primary and specialty care for uninsured patients and managed Wishard Health Services' community health centers. The IUMG primary care physicians provide primary care and act as gatekeepers in exchange got a capitated per member per month (PMPM) payment; payment for specialty care is made separately though the medical school. While most care is furnished at the community centers, some is also provided in the IUMG offices. Recently, Wishard Advantage was opened to other community physicians (Rollins, 2001a).
- The Ingram Health Plan provides low-income uninsured patients with access to ambulatory care. With the exception of one private office, the primary care sites are operated by the health department, University of Michigan, and Ingram Regional Medical Center. Primary care and specialty providers receive PMPM payments.
- The Carelink Program that provides financial assistance to uninsured residents of Bexar County (San Antonio), Texas is sponsored by the University Health System (UHS). The University of Texas physicians staff the hospital and its five clinics. Prior to Carelink, UHS made a pre-determined lump sum payment to the medical school that was unrelated to the patients or volume of care provided by an individual physician. Under Carelink, the physicians are paid on a fee-for-service basis.
- Both programs designed to improve access for low-income uninsured persons in Detroit use managed care approaches and contract with provider networks on a capitated basis.(5)
DSH payments to hospitals are unrelated to the care provided specific uninsured individuals; in contrast, the ambulatory programs discussed above limit payment to services provided to individuals who are enrolled in a program targeted to the uninsured. The model evolving in Los Angeles using 1115 waiver funds is somewhat different in that uninsured patients are not enrolled into a program but complete certificates of indigency attesting to their financial status at the treatment site. The LACDHS allocates the total pool of waiver funds to local service areas based on projected need. Individual providers are paid on a fee-for-services basis (with case management fees available for certain patients with special needs). Under the program, the Los Angeles County Department of Health Services (LACDHS) has extended its provider network from county-owned clinics to include community partners: 17 FQHCs, 25 state-licensed community clinics, and 25 private physician practices (Rollins, 2001b).
Issues Related to Supporting Uncompensated Care Costs of Community Providers
Currently, ambulatory care services provided to the uninsured in community-based settings are supported through charity care and a patchwork of federal, state, and local government programs. The way care is provided at the local level varies substantially across communities. In some, care is concentrated in hospital outpatient departments and to some extent is supported through DSH funding. Other communities have a strong tradition of community health centers that receive federal funding through section 330 grants. Community physicians in office-based practices provide substantial services to the uninsured but for the most part received no public funding for these services. The differences in support have implications for where care is provided and the relative proportion of uncompensated care costs that are borne by the federal government, state and local communities, and the health care provider.
While rationalizing federal subsidies for ambulatory care provided to low-income uninsured populations is an attractive policy objective, the mechanism for doing so in the absence of national health insurance is not clear. Support for uncompensated care provided by hospitals and by community health centers is not tied to care provided specific individuals. However, our limited review of innovative programs funded by 1115 waivers or Community Access Program grants indicate that most programs providing financial assistance for community-based ambulatory care involve enrollment by both the patient and the provider. Enrollment by the patient in a program that qualifies for federal funding would be tantamount to national health insurance. Without patient enrollment, a system of provider enrollment and reporting would be required. A mechanism is already in place for community health centers to subsidize for the difference between operating expenses and revenues. Since these facilities are required by law to treat all patients regardless of ability to pay and to establish a sliding fee schedule, there has not been an issue regarding whether the uncompensated care is attributable to indigent low-income patients. Extending a subsidy to other community-based ambulatory care providers would raise a number of issues:
- Which providers should qualify for subsidies? Should only providers who have a demonstrated commitment to serving low-income populations qualify? How would they be identified? Should there be an enrollment mechanism?
- What services should be subsidized? Is it realistic to limit subsidies to services provided to low-income uninsured populations in the absence of enrolling eligible patients? What reporting and verification system is reasonable? Should the subsidies be limited to services that must be required by law by the Emergency Medical Treatment and Labor Act?
- What level of uncompensated care costs should be subsidized? To what extent should the costs of care to the uninsured be covered by patient fees, absorbed by the provider, supported by state and local government, and subsidized by the federal government? Is there rationale for providing varying levels of support for the different components of the safety net for ambulatory care?
Questions such as these would need to be addressed before an estimate could be made of the projected cost of extending DSH federal subsidies to community ambulatory care providers.
Even with these issues resolved, it will not be easy to estimate the cost of the program based on existing data for the four major types of community-based safety net providers. Our findings in this regard from available published data are detailed below.
- Community health centers. Comprehensive data are available for BPHC grantees. The 730 grantees incurred net costs of $1.331 billion for uninsured users. Comparable financial data are not available for FQHC look-alikes. If we assume they had comparable costs and utilization, their net costs for uninsured users is about $0.62 billion. Data are not available for other community clinics that serve a safety net function.
- Local health departments. We were unable to identify a data source that would allow us to estimate the cost of direct care services provided to the uninsured. There is no uniform reporting of local health department costs or services that could be used for such an estimate.
- School-based health clinics. The no-charge policy of many school-based health clinics hinders an estimate of the uncompensated care costs for uninsured children.
- Private practitioners. National survey data can be used to estimate the volume of physician visits made by the uninsured. Estimates based on earlier data would need to be adjusted for growth in the uninsured and inflation. Assuming 41.2 million uninsured and 2-2.5 ambulatory visits to physician offices per uninsured (based on the CTS and MEPS findings), results in an estimated 82- 103 million visits by the uninsured. The average Medicare physician fee schedule payment for an extended office visit, new patient in 2002 is $130.68. Using this payment as an estimate of the cost of ambulatory visits, results in total estimated costs of $10.7 -13.5 billion before collections are taken into account. While not within the scope of this project, MEPS data could also be used to develop an estimate of the uncompensated care costs associated with these visits since the survey collects information on health care expenses by source of payment.
Additional research is needed to understand how much of the ambulatory care provided to the uninsured population is uncompensated, and how the uncompensated care burden varies across communities and types of providers within the communities. A policy that concentrates funding solely on hospital outpatient departments and clinics may serve to discourage community providers from providing substantial amounts of care to the indigent populations. Survey data could be used to define the characteristics of private physician practices that have a demonstrated commitment to serving the poor that could be used to establish potential criteria for identifying eligible providers for funding support. Case studies of the localities studied in depth by the CTS could also be used to understand differences across communities in the relative share of uncompensated ambulatory care costs borne by physicians relative to hospital-owned systems of care. Findings on this issue have implications for the equity of a policy that concentrates federal subsidies for uncompensated care on hospitals. Case studies of programs that have extended to safety net to include community providers could provide information on whether it is feasible to operationalize a non-enrollment program for the uninsured.
We did not identify a body of literature that examined issues related to financing uncompensated care costs incurred by ambulatory providers. One reason may be the diversity of the arrangements for providing care to the uninsured. An alternative to establishing national policies related to funding charity care provided by non-hospital community providers would be to expand the Community Access Program. This program provides the flexibility to take the structure of the local health care delivery system into account that may be lost in a national allocation policy for uncompensated care costs incurred by community safety-net providers. In the absence of national health insurance, grants to local communities targeted toward expanding and strengthening the role of community safety-net providers that are not current recipients of federal funds would be more appropriate use of DSH-like funds than a program that tries to allocate funding directly to those providers based on national policies and criteria. The challenge will be to devise coordinated policies between DSH funding to hospitals and grant programs for community providers that create appropriate incentives for the expansion of community-based ambulatory care access for the uninsured.
1. The IOM report also notes the important role played by the Veterans Health Administration and Indian Health Service.
2. Section 702 of the Medicare, Medicaid and SCHIP Benefits Improvement and Protection Act effective January 1, 2001.
3. For example, local funds covered 46% of the budgets for school-based health centers in 11 communities.
4. The other two components are a nursing home component and an insurance component that collects information on coverage and premiums from the household component and business establishments.
5. Health Choice targets low-income workers while Plus Care targets the non-elderly adult population.
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