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International Journal of
eISSN: 2577-8269

Family & Community Medicine

Research Article Volume 2 Issue 4

Public health ramifications of regional variation of DSH by congressional districts and state

Howard C Mandel, Carl Nunziato

Century City Women?s health, USA

Correspondence: Howard C Mandel, Century City Women?s Health, USA

Received: July 27, 2017 | Published: August 17, 2018

Citation: Mandel HC, Nunziato C. Public health ramifications of regional variation of DSH by congressional districts and state. Int J Fam Commun Med. 2018;2(4):229-236. DOI: 10.15406/ijfcm.2018.02.00085

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Abstract

Hospitals in communities with a significant percentage of indigent patients have, since 1981, received a federal adjustment to allow them to receive some compensation for treating these patients. The PPACA severely restricted these Disproportionate Share Hospital (DSH) payments as a cost saving measure. However, the law does not account for the potentially devastating impact of the lack of revenue caused in some localities with large populations of undocumented Americans ineligible to obtain insurance under the act. We created two easily identifiable quotients based on U.S. Census Bureau estimates of foreign-born population and Medicaid DSH payments aggregated by congressional district. These quotients allowed us to predict which congressional districts are at risk for continued high demand of their services by indigent patients in the face of severe DSH reductions. Our data can be used to predict which municipalities may be hardest hit by the impending DSH reductions, spurring legislators to offset the spending shortfall and the public health ramifications of inadequate hospital funding.

Main text

The Omnibus Budget Reconciliation Act of 1981 created Medicaid DSH payments.1 This was necessary because hospitals serving a larger proportion of low income patients are particularly dependent on the poorer than private-payor revenue stream associated with Medicaid reimbursement as well as the reality that many low income populations including the undocumented are uninsured.2 The architects of the Patient Protection and Affordable Care Act (ACA, P.L. 111-148 as amended) expected its health insurance provisions to reduce the number of uninsured individuals in the United States to the point that there would be less need for Medicaid DSH payments.2  The law directs the Secretary of Health and Human Services to make aggregate reductions of DSH from 2014 through 2020, however Congress extended this reduction through 2022.24 Congress planned to reduce DSH payments by $17.1 billion by 2020.5 DSH payments are not evenly distributed with the Middle Atlantic States, Southern Atlantic and Pacific Regions receiving 60% of payments, yet only 46% of Medicare discharges.6 Five states, NY, CA, TX, NJ and PA alone get the majority of these payments.2 Undocumented Americans are also unevenly distributed throughout the United States.79 As the Emergency Treatment and Labor Act (EMTALA) requires care and treatment of this population, DSH has secured the safety net, especially in localities with large numbers of these immigrants. Additionally, as new citizens are not eligible for most forms of federal programs for 5 years, these individuals who are low income will not be capable of getting Medicaid and also will remain uninsured despite ACA. In FY2012, the federal DSH payments totaled $11.3 billion.210 Given the significant variation in DSH payments and the concentrated populations of both the new citizens as well as the undocumented Americans, we hypothesized that some localities and their hospitals would be significantly impacted by the DSH reduction and that this dramatic reduction in revenue could not be cost shifted onto other payor classes. This adverse economic situation would result in public health devastation if not addressed. We also postulated that as the ACA was so highly politicized that this impending public health emergency would not be addressed unless congressional representatives recognized the significance in their home districts or states.

Method

The DSH Audit and Reporting Rule require states to submit annual independent audits describing payments to DSH hospitals. Publically available reports from Medicaid State Plan Rate Year 2008, provided by the Centers for Medicare & Medicaid Services, were used to compile a list of DSH hospitals that received one million dollars or more in DSH funding in 2008. Coordinate data from these hospitals was used in conjunction with Sunlight Foundation’s Congress API database to assign a congressional district based on the 112th and 113th congressional boundaries. The aggregation of payments by congressional district and state resulted in the estimated 2008 DSH Payments values. Next, an estimate for the fraction of a congressional district’s non-naturalized, foreign-born population was calculated from the ethnicity data available in the U.S. Census Bureau’s 2010 American Community Survey (ACS) 3-Year estimates. Due to the lack of accurate estimates of undocumented immigrants by congressional districts, we relied on the Census Bureau’s estimations for all foreign-born populations, and expect the number of undocumented is proportionate to the total number of immigrants in a region. We also analyzed the data and looked for correlation with the congressional district and state analysis of an Immigration Policy Center data set that was created in association with Rob Paral & Associates.8 These estimates were cross-referenced with the congressional and state level estimates for DSH payments and used to calculate the Mandel-Nunziato Quotient (MNQ) -- a function of a given region’s total DSH payments multiplied by the percentage of non-naturalized, foreign-born persons (NN). The Mandel-Nunziato Indigent Quotient (MNIQ) was similarly calculated first by deriving the percentage of people in a congressional district or state population receiving Medicaid or other mean’s tested public coverage using data from the 2010 ACS table “Types of Health Insurance Coverage by Age”. This data, once combined with the DSH and ethnicity dataset, was used to calculate the MNIQ as a function of total DSH payments multiplied by the percentage of a region’s population that is either non-naturalized or receiving mean’s tested public health insurance coverage (MTC). To enhance readability, all MNQ and MNIQ values were divided by a factor of one million and ranked from highest to lowest.

Mandel nunziato quotient:

DSH x % NN =MNQ

Mandel nunziato indigent quotient

DSH x (%NN + %MTC)= MNIQ

As Tennessee operates their Medicaid programs under a Section 1115 waiver they were not included in our data collection.2

Results

MNQs and MNIQs were calculated and the 20 highest values organized into Table 1 & Table 2. Similarly, Table 3 shows the top 20 states receiving the largest DSH payments with their corresponding MNQs and MNIQs. Table 4A– Table 4G, containing the entire list of the 293 Congressional Districts with at least one hospital that received DSH payments of more than $1 million, ranked from largest to smallest MNIQ, is available to supplement our report. Organized by Mandel-Nunziato Quotient (MNQ)-a function of a given region’s total DSH payments multiplied by the percentage of non-naturalized, foreign-born persons.

Congressional District (112th)

MNQ

MNIQ

2008 DSH Payments

CA#34

130.556

216.106

436,035,424

NY#11

55.148

135.136

304,229,492

TX#9

54.763

76.917

210,336,081

NY#16

44.153

134.461

191,165,186

NJ#13

44.114

67.598

167,078,413

NY#7

37.656

78.841

173,951,223

NY#15

36.972

96.049

193,419,395

CA#15

31.921

50.071

184,917,676

NY#14

31.802

52.389

211,736,810

TX#30

31.085

54.621

186,632,226

NJ#10

30.426

67.671

216,601,845

NY#5

28.126

48.091

119,478,124

AZ#4

26.559

52.843

120,365,411

CA#43

25.799

48.308

133,775,811

NY#17

25.708

60.221

174,057,134

CA#27

23.394

39.581

124,852,462

CA#36

23.141

37.893

163,291,882

CA#8

19.416

40.024

127,342,073

CA#20

17.808

36.791

73,907,877

CA#9

17.582

34.217

120,248,108

Table 1 Top 20 Congressional districts at risk of significant financial stress due to DSH reductions

Congressional Districts (112th)

MNIQ

MNQ

2008 DSH Payments

CA#34

216.106

130.556

436,035,424

NY#11

135.136

55.148

304,229,492

NY#16

134.461

44.153

191,165,186

NY#15

96.049

36.972

193,419,395

NY#7

78.841

37.656

173,951,223

TX#9

76.917

54.763

210,336,081

NJ#10

67.671

30.426

216,601,845

NJ#13

67.598

44.114

167,078,413

NY#17

60.221

25.708

174,057,134

NY#10

58.775

16.799

140,723,119

TX#30

54.621

31.085

186,632,226

AZ#4

52.843

26.559

120,365,411

NY#14

52.389

31.802

211,736,810

CA#15

50.071

31.921

184,917,676

CA#43

48.308

25.799

133,775,811

NY#5

48.091

28.126

119,478,124

LA#2

40.272

8.268

193,327,198

CA#8

40.024

19.416

127,342,073

CA#27

39.581

23.394

124,852,462

CA#36

37.893

23.141

163,291,882

Table 2 Top 20 Congressional districts at risk of stress due to DSH reductions organized by Mandel-Nunziato Indigent Quotient (MNIQ). The MNIQ is a function of total DSH payments multiplied by the percentage of a region’s population that is either non-naturalized or receiving mean’s tested public health insurance coverage (MTC). To enhance readability, all MNQ and MNIQ values were divided by a factor of one million and ranked from highest to lowest

State

2008 DSH Payments

MNQ

MNIQ

NY

2,619,221,027

262.8

554.9

CA

2,061,345,386

263.7

465.1

TX

1,394,048,286

68.2

291.1

NJ

1,203,622,474

129.5

249.4

LA

937,607,647

13

127.7

MO

677,878,646

10.1

74.9

OH

595,008,973

12.9

95.3

PA

578,869,424

19.3

80.9

SC

432,791,995

6

59.3

NC

420,918,230

7.5

42.8

AL

388,509,120

3.8

38.8

GA

374,470,631

9.5

54.9

CT

308,842,114

20

64.6

MI

255,110,779

5.3

52.6

IN

250,301,219

3.5

22.2

IL

219,130,021

7.4

33.4

NH

218,697,472

6.2

33.1

NM

216,404,518

7.9

31.4

MS

174,695,408

1.3

17.7

CO

169,732,576

4.8

24.8

Table 3 The top 20 states receiving the largest DSH payments with their corresponding MNQs and MNIQs

Congressional District (112)

MNIQ

MNQ

2008 DSH Payments Received

CA-34

216.106

130.556

436,035,424

NY-11

135.136

55.148

304,229,492

NY-16

134.461

44.153

191,165,186

NY-15

96.049

36.972

193,419,395

NY-7

78.841

37.656

173,951,223

TX-9

76.917

54.763

210,336,081

NJ-10

67.671

30.426

216,601,845

NJ-13

67.598

44.114

167,078,413

NY-17

60.221

25.708

174,057,134

NY-10

58.775

16.799

140,723,119

TX-30

54.621

31.085

186,632,226

AZ-4

52.843

26.559

120,365,411

NY-14

52.389

31.802

211,736,810

CA-15

50.071

31.921

184,917,676

CA-43

48.308

25.799

133,775,811

NY-5

48.091

28.126

119,478,124

LA-2

40.272

8.268

193,327,198

CA-8

40.024

19.416

127,342,073

CA-27

39.581

23.394

124,852,462

CA-36

37.893

23.141

163,291,882

PA-1

37.357

8.129

113,764,130

CA-20

36.791

17.808

73,907,877

CA-9

34.217

17.582

120,248,108

CA-45

33.559

17.009

123,286,229

NJ-1

31.414

7.319

191,834,652

NJ-8

31.36

17.148

110,020,834

AL-7

31.284

2.872

162,808,593

MI-13

29.501

4.265

90,048,395

NM-1

29.136

10.696

140,209,339

NY-12

28.016

12.976

53,337,737

IL-7

27.723

7.727

130,165,516

CT-3

27.716

9.275

144,095,511

CA-40

27.164

16.672

105,343,430

OH-11

26.68

3.542

131,727,319

SC-6

26.454

2.031

149,875,473

NY-4

25.309

13.652

118,667,059

GA-5

25.061

11.332

135,496,789

CA-5

24.574

8.69

81,179,071

LA-1

23.41

6.243

169,438,687

Table 4 Congressional District by MNIQ

Congressional District (112)

MN IQ

MNQ

2008 DM Payments Received

NY-9

23.15

9.959

69121307

IN-7

23.086

7.138

94249,639

NY-28

22.714

3.025

87936315

Tx-20

22.642

10.261

95779475

CO-1

22.576

10.466

94782584

CA-18

22.079

9.266

53127683

MO-5

22.071

6.383

1.74E+08

CA-53

21.463

12.642

83837141

NY-18

21.073

13.227

97036963

LA-4

21.016

2.201

1.45E+08

NY-2

20.364

10.552

106,317„888

VA-3

20.2.52

4.703

1.31E+08

NY-S

20.01

9.174

58383068

LA-5

19.854

1.332

1.18E+08

NV-1

19.186

12.605

73643353

NI-6

17.649

11.443

83335325

NC-S

 17.4.52

6.576

1.03E+08

NY-6

17.035

7.558

40004841

CT-1

17.026

5.687

80913834

NJ-9

16.416

10.786

62119027

NJ-12

16.08

9.856

104„911,771

RI-2

15.945

5.796

77674225

NC-13

15.79

7.541

87268856

NY-25

15.443

3.177

1.02E+08

MD-7

14.988

3.462

61003931

LA-6

14.818

2.797

118,240„957

TX-22

 14.6.32

8.726

48705495

M N-5

14.62

12907

60591737

MO-9

14.487

2.132

1.37E+08

NJ-11

14.474

9.46

122,971403

TX-12

14.338

8.262

87661503

CA-7

14.18

7.084

50292.96

LA-7

14.179

1.813

103..795,678

TX-16

14.139

7.385

49836213

OH-15

13.774

5295

102,477..284

NM-2

13.605

4.258

56,.557,858

CA-12

13.149

8.28

61,914)699

NH-2

13.019

3.495

139;449240

TX-5

12.94

6.121

85,809)782

Table 4A Congressional District by MNIQ

Congressional District1112)

M N IQ

IYINQ

2O DM Payments Received

TX-14

12.936

6.257

99025308

LA-3

12.725

1.703

86731018

PA-14

12.627

1.823

63335860

TX-23

12.201

5.827

59565094

5C.4

11.572

4.151

78,846436

M5-3

11.412

1.009

80821478

SC-1

11.096

 3.931.

92566427

MO-1

10.909

2.119

701623,661

TX-15

 10,74.5

5.402

361464.9

NY-1

10.34

4.295

83699384

TX-21

0.099

5.054

86269122

CA.17

9.894

6.29

31397303

NC-3

9376

2.457

69657554

TX-18

9.348

5.009

27061738

M5-4

9.305

1.205

72508940

PA-2

9.236

1.691

36186068

AL-5

9.139

2.293

81767381

PA-6

9.049

3.328

70534577

NC-1

9.023

1.051

41335,272

1L-12

8769

0.604

55564152

KY-1

8.68

0.628

64842072

C1-5

8557

2.984

40028290

TX-19

8.442

2.7

57894373

GA-2

8.349

1.052

45543086

NY-22

8333

2372

43,243,788

MO-7

7952

1.363

74604137

OR-1

7.628

3.877

47352282

NY-21

7.419

1.436

41981071

MI-15

7.384

1.611

44076741

TX .4

7.365

2.992

58268248

PA-10

7.316

0.68

60758805

AR-2

7.27

1829

54625617

fsJ I-1-1

7123

1.902

79248232

AL-1

 6.96?

1.236

52805121

VT-2

6.945

0.592

33511969

RI-1

6.875

2.189

36461389

CA-24

6.755

3.652

40712567

CT-4

6495

3.626

30553457

TX-29

6.48

4.047

15694240

Table 4B Congressional District by MNIQ

Congressional District (112)

MNIQ

M N Q

2008 DSH Payments Received

NY-19

6.444

2.494

42,028..050

CO-5

6.428

1.73

49280282

CA-37

6.334

2.968

16349374

OH-3

6.271

0.833

53,599..263

NY-27

6.168

0.788

33773339

TX-1.7

5.788

2.8

40205236

OH-12

5.784

1.924

38553809

MO-8

5.773

0.284

36101300

CA-30

5.77

3.354

36,786.232

NJ-7

5.613

3.552

40,676449

PA-18

5.612

0.957

54195512

OH-9

5.529

0.604

36981310

N.1-2

5.395

1.692

29,848.299

MO-3

5.375

1.821

47898830

M04

5.365

0.833

49681676

SC-3

5.347

1.011

40,070„770

NC-7

5.346

1.383

32,019..021

PA-15

5.224

1.271

39018225

OK-5

5.17

2.258

32762186

AL-3

5.047

0.858

35399870

I N-9

5.005

1.215

43,485,350

AL-2

4.993

0.575

37.246,879

$C-2

4.947

1.64.8

40260960

OH-1

4.841

0.97

33.728,163

PA-3

4.803

397

32980108

M 1-5

4.697

0.194

21.931,329

5C-5

4.683

600

31172229

PA-16

4.68

1.417

30898825

TX-1

4.666

1.85

29493207

NY-24

4.643

0.612

25122250

NC-4

4.549

2.575

32895523

MO-6

4.51

0.759

50668982

GA-10

4.413

1.149

34690084

KY-5

4.408

0.047

20801737

KY-2

4.339

0.668

33,422,663.

IN-6

4.245

0.42

40128570

NY-13

4.183

1.518

14355848

WV-3

4.111

0.106

24794068

OH-17

4.103

0.368

31,342,277

Table 4C Congressional District by MNIQ

Congressional District (112J

MNIQ

MNQ

2008 D51-1 Payments Received

NJ-4.

4.089.

1.62

26080371

M N-4

4.071

1.447

20833707

PA-9

4.068

0.269

32541560

OH-7

3.91

0.581

27923895

IA-3

3.749

0.9.36

23819261

GA-12

3.685

0.78

27313762

TX-22

3.634

2.372

23851010

NM-3

3.475

0.879

19637321

NY-23

3.387

296

19090013

NC-10

3.386

 0.7.55

25382475

NY-20

3.377

 0.4.57

26845115

GA-1

3.365

 0.7.58

25222037

MS-2

3.212

0.21

15134459

GA-4

3.167

19368

13200748

NJ-5

3.082

1.594

28085589

IN-S

3.005

0.257

26944628

GA-13

2.97

1.42

16824618

NE-2

2.96

1.11

23750315

GA-9

2.927

1.31

18806680

GA-S

2.901

0.55

19489590

M1-14

2.883

0.344

10322735

ME-2

2.855

0.172

11654331

OH-13

2.831

394

24940735

TX-10

2.792

1358

15070794

KY-6

2.753

0.836

20838816

MI-6

2.688

0.404

17504211

TX-7

2.678

2.057

13420909

GA-11

2.642

1.125

21082003

UT-2

2.565

0.902

21137387

FL-20

2.495

1317

10286832

AL-4

2.49

523

15713716

OH-4

2457

0.081

19275977

NY-3

2.446

1.137

18794345

TX-11

2.428

1.03

17588334

TX-32

2.383

1.868

8271053

M0-2

2.32

 0.9.50

37568441

VA-5

2.311

0.505

19821744

NY-29

2.304

0.233

16120786

NJ-3

2.235

0.664

20058796

Table 4D Congressional District by MNIQ

Congressional District (112)

MNIQ

MNQ

2008 D51-1 Payments Received

PA-17

2.229

0.35

18721618

ME-1 I

2.195

212

14023000

IA-2

2.185

0.493

15976087

WV-2

2.176

0.134

16609763

OH-10

2.168

0.461

13872589

HT-3

2.165

0.64

16093456

TX-13

2.092

0.88

14345792

CO-3

2.055

0.548

13057256

CA-21 I

2.021

839

6000646

OH-18

1.998

0.072

15043206

Uri

1.981

0.816

15535854

CT-2

1.96

0.507

13251022

MI-1

1.959

0.121

12688828

111.-16

1.944

0.55

12973153

AK-1

1.916

0.522

14268274

MD-1

1.868

0.349

16,420r800

MD-6

1.855

0.434

15842616

CO-4

1.786

0.683

12612454

1L-19

1.77

0.112

15,202451

M I-7

1.729

0.224

11143774

MI-8

1322

397

12328190

ID-2

1.718

0.605

13030292

NY-26

1.658

0.297

12320329

TX-27

1.646

0.77

7458,970

PA-7

1.581

0.676

13490825

WV-I

1.573

85

12856337

HI-1

1.545

0.765

7341025

IN-3

1.524

0.404

14537184

OH-16

1.52

0.149

13611668

M I-4

1.453

0.096

10584339

OH-2

1.451

0.291

12753360

M D-3

1.418

0.615

9122195

M 1-12

1.386

305

7783945

N C-9

1359

0.633

11452096

NC-2

1.314

0.448

7491359

OH-8

1.299

0.236

11056754

GA-3

1.249

0.313

10974328

TX-31

1.221

0.569

9589906

M D-4

1.203

0.702

5616807

Table 4E Congressional District by MNIQ

Congressional District (112)

MNIQ

MNQ

2008 DSH Payments Received

IL-5

1.169

0.763

5225049

IN-4

1.15

0.387

11858766

MI-3

1.141

0.25

7539227

IN-2

1.121

0.276

9051907

TX-3

1.042

0.758

5551301

CA-a

0.989

321

4548565

KS-4

0.985

304

7716222

M I-2

0.981

0.161

6674434

MS-1

0.97

0.084

6230531

GA-7

0.957

0.613

5826906

NV-2

0.845

0.404

5956577

MN-1

0.838

0.178

61078,997

NC-5

0.83

225

6076898

OH-6

0.787

0.035

5692315

K5-3

0.755

0.429

6691886

KS-Z

0.751

0.152

7354155

KY-4

0.743

0.089

6564694

IA-5

0.73

0.166

5400932

CA-52

0.729

375

2,1.98,173

AZ-7

0.714

0.264

2050404

IN-5

0.69

0.189

7837546

OH-14

0.643

0.132

7186796

01C-1

0.617

0.243

5114840

NC-11

399

0.139

4529948

N E-3

0393

(1137

5,302,536

MT-1

366

0.057

6811855

VA-4

0.533

0.109

4937799

DE-1

0.511

0.122

2814038

011-5

0.502

0.046

4,955421

ID-1

0.461

0.116

4173840

IA-1

0.452

0.055

3793596

PA-13

0.402

0.129

2427145

M N-8

0.392

0.015

2560922

MI-9

0.384

0.171

2484,631

NE-1

0.366

0.129

3629561

AZ-5

0.345

0.153

2230487

NT-21

339

0.066

1919583

PA-19

0.317

0.059

2907802

MN-3

0.311

0.137

2150763

Table 4F Congressional District by MNIQ

Congressional District (112)

MNIQ

MINQ

2008 D!11 Payments Received

VA-6

0.307

0.101

3060309

NC-4

0.3

0.17

2172210

OK -4

0.3

0.072

2892992

LA-1

0.293

0.06g

2!203,818

VA-9

0.28

0.037

2491A94

AL-6

0.279

0.096

2767560

IN-1

0.279

0.064

2,21)7,629

PA-12

0.276

0.012

1783964

MD-2

0.261

0.078

1412836

MN-6

0.251

0.044

2452676

PA-5

0.243

0.025

1736354

AZ-2

0.236

0.066

1346092

HI-2

0.233

0.07

1195509

PA-11

0.229

0.041

1415836

TX-25

0.226

0.128

1160131

MN-7

0.205

0.024

1374383

TX-6

0.191

0.11

1474,154

TX-26

0.165

0.095

1438,705

TX-8

0.142

0.06.3

1025034

WY-1

0.094

0.02

1153843

Table 4G Congressional District by MNIQ

Discussion

Presidents since Theodore Roosevelt have tried to provide health care security for the American population. The development of the public health hospitals as well as the creation of Medicare and Medicaid attempted to supplement the employer based health care system. Congress and health economists have long realized that there are significant differences in the kinds of insurance, as well as the rate of uninsured as well as variation across congressional districts.11,12 In their creation of DSH, Congress recognized that these variations could be extremely damaging to public health disproportionately across the country.1 The politics of creating legislation that would provide affordable universal health insurance for all Americans in what some authors would call the largest domestic reform in 80 years was not lost on the architects of the Affordable Care Act, nor was the importance of rapidly addressing their goal in the first legislative cycle.13 The death of Massachusetts Senator Edward Kennedy, and the election of Senator Scott Brown resulted in the House of Representatives accepting the Senate version of the bill without the planned conference committee that would have corrected significant flaws in the legislation. One major flaw in the bill is that the safety net providing health care access is extremely dependent on DSH---yet undocumented immigrants and new citizens who are impoverished often live in communities served by those hospitals. As both those populations would not be eligible for either Medicaid or the purchase of health insurance with subsidy through the health care exchanges, localities with significant percentages of those populations will not have the revenues to support their safety nets. We believe that we are the first researchers to analyze congressional districts by looking at both the variables of dependence on DSH revenue as well as proportion of population that will not be eligible to obtain health insurance and therefore will remain uninsured.

By creating two quotients, the MNQ and MNIQ, we have created a pragmatic tool that will allow health economists, safety net providers and public health officials to easily focus on those localities that we believe will have significant revenue shortfalls as ACA expands and unless rectified DSH levels decrease see Figures 1. As the Secretary of Health and Human Services was given some flexibility in applying the DSH decreases, it may allow planners in HHS another methodology in their analysis to lessen the potential public health harm created when those communities in greatest need of health care access are disproportionately affected. Peter Drucker analyzed in 1995 that (in Los Angeles) “immigration already exceeds what is socially and politically manageable”.14,15 Clearly, as our data indicates, districts like CA34 with $436,035,424 or NY11 with $304,22,492 in DSH per annum cannot cost shift $100 million decreases annually for the next several years. As the annual aggregate DSH reductions are back loaded, we believe that although there will be difficulties over the next few years, that unless rectified the safety net system in the high MNQ, as well as MNIQ districts will have serious financial difficulties starting in fiscal 2018.16

As the economics of the safety net are not specifically related to the immigrant populations, we did not analyze the CDs by population alone as did the Immigration Policy Center group, who looked at potential eligible recipients of the Dream Act. In cities of high population density, it is not uncommon for patients to travel significant distances to go to the safety net providers and hospitals, and therefore why we believe that DSH received must be a significant contributor to our quotients. Observationally, we noticed that states with large discrepancies between MNQ and MNIQ (TX and LA, for example) are also co-incidentally those that have refused to implement the Medicaid expansion. This will need to be explored by public health leaders in those states, as it possibly could become problematic as well. As the Secretary is mandated to decrease DSH, these states, and specific Congressional districts within those states like TX-9 - TX-30 that are currently dependent on DSH, will be under significant cost pressure. They will have to rely on lower DSH revenues to treat both indigent patients that were supposed to be shifted to Medicaid, as well as their high population of undocumented residents. We also believe this article is quite significant because it can offer members of Congress an easy to use new tool that could result in the avoidance of a public health nightmare. With the responsibilities to provide services mandated by EMTALA as well as PHA 330, if the ACA flaw is not corrected, our quotients can be used by state and county treasurers, bond insurers and underwriters to more accurately assess those localities that are at higher risk of default on their financial obligations. We also believe these communities will be hardest hit by increased waiting times to see primary care physicians and specialists and that our quotients will assist planners to focus on those communities to develop reasonable contingency plans.17

Figure 1 Total DSH Allotments before the Reductions, with the ACA Reductions, and under current Law.2

Acknowledgement

Comprehensive list of DSH payments were obtained from Medicaid State Plan Rate Year 2008 report. Hospitals were assigned to congressional districts with the help of the Sunlight Foundation and their publically available congressional district API. Demographic information was provided both by the US Census Bureau’s American Community Survey as well as the Immigration Policy Center in partnership with Rob Paral and Associates.

Conflict of interest

The author declares there is no conflict of interest.

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