Insuring the Uninsured:
The Gains From Reducing Waste

 By Dean Baker1

September 23, 2004

The United States spends more than twice as much per person on health care as the other rich nations, on average2. However, this additional spending does not lead to better health outcomes in the form of life expectancies, infant mortality rates, or self-reported quality of health. The United States does not rank highly in these categories, in fact it ranks it near the bottom among rich countries in both life expectancy and infant mortality rates. In addition, people in the United States have a great deal of insecurity about their access to health care, since alone among wealthy nations, it does not guarantee health insurance for its citizens. Over 70 million people go without health insurance at some point in the year, and in 2003 45 million people went the whole year without insurance3.

This paper examines the extent to which it would be possible to pay for covering the uninsured, by eliminating waste within the system. Specifically, it calculates the amount of money that could be saved by replacing the current system, that relies largely on private for profit insurers, with a centralized government run system similar to the traditional Medicare program. It also calculates the potential savings that would result from a national system of bulk drug purchasing or a system of negotiated drug prices, comparable to what exists in Canada and other rich countries. It uses these calculations of savings to determine how many of the uninsured could be covered by the elimination of waste. These calculations are done both for the country as a whole, and for each state.

Before describing the calculations in greater detail, it is worth noting that the calculations in this paper are almost certainly a substantial understatement of the waste in the health care system in the United States. In examining the unnecessary expenses of the for profit health insurance system, this paper only calculates the additional costs associated with running the insurance companies themselves, compared with a Medicare type system. It does not factor in the additional expenses incurred by health care providers - hospitals, physicians' offices, and nursing homes - due to the paperwork necessary to deal with a system of decentralized third party payers. The current system requires many layers of record keeping to determine financial liability that would be largely unnecessary in a centralized system.

The resulting waste in the form of additional administrative personnel at health care providers is substantial. An earlier study placed the size of these unnecessary administrative expenses at between 9.4 percent and 12.2 percent of total health care spending, or between $157.3 billion and $203.5 billion annually, using 2003 health care spending levels4. These savings are between $540 and $700 per year for every man, woman, and child in the United States. While the calculations in this earlier paper may somewhat overstate the potential administrative savings at providers, even if the gains from a centralized system are only half as large as this estimate, they would still be enormous5. Since it does not include any of the administrative savings incurred by heath care providers, the calculations paper are almost certainly a substantial understatement of the gains from a universal government run health insurance system.

I. Insuring the Uninsured - Gains From a Medicare Type System

This section calculates the number of uninsured who could be insured from the savings that would result from replacing the current system of decentralized private insurers with a centralized Medicare type system. The calculations assume that the only gain from this switch is the difference in the administrative expenses for a Medicare type system compared with the administrative expenses for the current system. Based on data from the Medicare trustees report, the calculations assume that administrative expenses for a universal Medicare type system would be 1.65 percent of health care spending. By contrast, the administrative expenses for the current for profit insurance system are calculated as 15.4 percent of the health care expenses paid out through this system. (See the appendix for a more detailed discussion of the methodology).

Table 1 shows the potential savings from adopting a universal Medicare type system for the country as a whole and in each of the states using data for 2003. The first column of table 1 shows total medical expenditures in 2003 for the country as a whole and in each state. Medicare expenses for the country as whole were $1,673.6 billion in 2003. California spent $181.2 billion on medical care, by far the highest for any individual state.

Table 1

Administrative Savings from Universal Medicare and the Uninsured

 

 

 

Currently

 

Additional Coverage

 

 

Method I

Method II

Uninsured

Method I

Method II

Method I

Method II

 

(billions of 2003 dollars)

(thousands)

 

 

 

United States

$1,673.6

$94.7

$155.6

81,834

54,912

90,251

67.1%

110.3%

Alabama 

26.4

1.5 

2.5

1,167

1,071

1,760

91.8

150.8

Alaska

3.8

0.2

0.4

208

127

208

61.0

100.2

Arizona

24.3

1.4

2.2

1,707

923

1,517

54.1

88.8

Arkansas

13.9

0.7

1.2

801

563

925

70.3

115.5

California

181.2

10.1

16.6

11,945

5,504

9,046

46.1

75.7

Colorado

22.5

1.4

2.3

1,309

764

1,256

58.4

96.0

Connecticut

25.1

1.4

2.4

767

616

1,012

80.3

132.0

Delaware

5.1

0.3

0.5

185

177

291

95.7

157.3

District of Columbia

7.0

0.4

0.7

163

157

257

96.0

157.8

Florida

98.3

5.5

9.0

4,793

3,286

5,401

68.6

112.7

Georgia

44.8

2.6

4.4

2,499

1,649

2,710

66.0

108.5

Hawaii

7.7

0.5

0.9

346

308

505

88.9

146.1

Idaho

5.6

0.3

0.5

395

234

385 

59.3

97.4

Illinois 

73.0

4.4

7.3

3,492

2,406

3,955

68.9

113.3

Indiana   

35.0

2.1

3.4

1,534

1,317

2,164

85.8

141.1

Iowa    

16.8

1.0

1.6

637

621

1,021

97.6

160.4

Kansas   

15.5

0.9

1.6

624

580

954

93.0

152.8

Kentucky   

23.7

1.3

2.2

1,059

924

1,519

87.3

143.5

Louisiana   

27.2

1.3

2.2

1,426

945

1,553

66.3

108.9

Maine    

8.1

0.4

0.7

290

282

464

97.3

159.9

Maryland   

32.3

1.9

3.2

1,354

957

1,572

70.6

116.1

Massachusetts   

49.5

2.7

4.5

1,443

1,265

2,080

87.7

144.1

Michigan   

58.7

3.4

5.6

2,538

2,040

3,353

80.4

132.1

Minnesota    

33.4

2.1

3.4

1,020

1,117

1,837

109.6

180.1

Mississippi   

14.6

0.7

1.2

875

558

916

63.7

104.7

Missouri    

34.4

1.9

3.1

1,354

1,181

1,942

87.2

143.4

Montana   

4.7

0.3

0.5

246

199

327

81.0

133.1

Nebraska   

10.0

0.6

1.0

400

359

591

89.8

147.7

Nevada   

9.2

0.5

0.9

700

321

527

45.8

75.3

New Hampshire   

7.7

0.5

0.8

259

249

409

96.2

158.1

New Jersey   

53.8

3.1

5.1

2,199

1,399

2,299

63.6

104.6

New Mexico   

8.8

0.5

0.8

685

340

558

49.6

81.5

New York   

141.3

6.7

11.0

5,646

3,348

5,502

59.3

97.5

North Carolina   

45.0

2.5

4.2

2,439

1,652

2,716

67.8

111.4

North Dakota   

4.4

0.3

0.5

144

175

288

121.7

200.1

Ohio   

70.1

4.1

6.7

2,755

2,483

4,080

90.1

148.1

Oklahoma    

18.1

1.0

1.7

1,066

703

1,156

66.0

108.5

Oregon   

17.8

1.0

1.7

968

654

1,075

67.6

111.0

Pennsylvania   

84.5

4.6

7.6

2,804

2,646

4,348

94.4

155.1

Rhode Island    

7.4

0.4

0.6

249

224

368

89.9

147.7

South Carolina   

21.7

1.2

2.0

1,055

859

1,412

81.4

133.8

South Dakota   

4.7

0.3

0.5

180

182

298

100.8

165.7

Tennessee   

36.3

2.0

3.3

1,447

1,284

2,110

88.7

145.8

Texas   

111.6

6.5

10.7

8,536

4,049

6,655

47.4

78.0

Utah   

9.8

0.6

1.0

651

464

762

71.2

117.1

Vermont   

3.4

0.2

0.3

136

112

184

82.3

135.3

Virginia   

36.7

2.3

3.8

1,836

1,248

2,052

68.0

111.7

Washington   

31.8

1.8

3.0

1,639

1,009

1,658

61.6

101.2

West Virginia   

11.6

0.7

1.1

465

497

817

106.9

175.8

Wisconsin   

32.8

2.0

3.3

1,253

1,202

1,976

95.9

157.7

Wyoming   

2.3

0.1

0.2

143

82

134

57.1

93.9

Source: Author's calculations, see appendix. 



The second column shows a calculation of the administrative savings for the country as a whole, and for each state, under a universal Medicare type system of health insurance. The calculation shown in this column (identified as "Method 1") focuses narrowly on difference in the administrative costs between the current health insurance system and the administrative costs of the Medicare system. It assumes that this difference would be the only savings that would result from the adoption of a universal Medicare type system. This shows that the country as whole would have saved $94.7 billion in 2003 with a universal Medicare type system. California alone would have saved $10.1 billion with a universal system. Column 3 shows a calculation of the savings, which is derived from a study produced by the Lewin Group, a well respected economics consulting firm. This study estimated the administrative savings to California that would result from the adoption of a universal type Medicare plan. (It also examined the costs of other health care reforms.)6 This estimate provides a useful check for the calculation developed in this study, and supports the view that it is genuinely a low-end estimate of the potential savings from a universal Medicare type system. The calculation derived from the Lewin analysis indicates that the United States as whole would have saved $155.6 billion in administrative expenses in 2003, with a universal Medicare type system, while California alone would have saved $16.6 billion.

The fourth column shows the number of people who are without insurance at some point in the year. These data are taken from an analysis of Census Data (Families USA, 2004) for 2002, the most recent data available. The data show that nationwide, 81,834,000 people were without insurance at some point in the year. In California, 11,945,000 were without insurance at some point in the year.

Columns 4 and 5 show the number of uninsured who could be insured with the savings from the adoption of a universal Medicare type system. Using the first method of calculating waste, Column 4 shows that 54,921,000 people could be insured nationwide with the savings. In California, the savings could insure 5,504 million people. Column 5 shows the number of people that could be insured using the calculations of savings from Method II. This shows that 90,251,000 could be insured nationwide with these savings, and 9,046,000 could be insured in California alone.

Columns 5 and 6 show the percentage of the currently uninsured population that could be insured with the savings using the two methods of calculation. Column 5 shows that 67.1 percent of the uninsured nationwide could be insured with the administrative savings as calculated using Method I. It shows that 46.1 percent of the uninsured in California could be covered by the savings calculated with Method I. Column 6 shows that the savings, as calculated with Method II would be large enough to pay for the coverage of the entire uninsured population - 110.3 percent of the uninsured. While this would not necessarily be the case in every state, the savings would go quite far towards this goal. In California, for example, the administrative savings as calculated using Method II would be large enough to insure 75.7 percent of the uninsured population.

In short, this analysis shows that even under extremely conservative assumptions, the savings from adopting a universal Medicare type system would be large enough to pay for insurance for the vast majority of the uninsured. If the efficiencies areas large as those assumed by the Lewin Group in its analysis, then the savings would be large enough nationwide to insure all of the currently uninsured population. This would be the case in the vast majority of states as well.

II. Insuring the Uninsured - The Gains from Bulk Purchases of Prescription Drugs

Consumers in the United States pay far higher prices for prescription drugs than they do anywhere else in the world7. The reason is that the United States is the only country that grants drug firms an unrestricted patent monopoly for selling their drugs. In every other country, the government imposes some sort of check on this patent monopoly, usually in the form of price controls or agreeing to a negotiated price with the industry.

In principle, the United States could implement a similar policy where it limits the price that companies charge for their drugs during the period in which they are granted a patent monopoly. There clearly is considerable room for prices to fall, since in most cases the cost of manufacturing and distributing drugs is just a small share of the price. A recent study calculated that the manufacturing and distribution costs accounted for between 5 percent and 15 percent of the standard retail price (Sager and Socolar, 2003)8. The rest of the price goes to research expenditures, marketing costs, and profits.

The main objection that the pharmaceutical industry has raised to restrictions on it patent monopolies is that lower prices would prevent it from raising the money it needs to finance future research. While the link between current profits and research spending is not as tight as the industry lobbyists imply, they do raise a legitimate point. If the government sets prices through a negotiation process or outright controls, it will effectively be determining the course of future research spending. The industry will steer its research dollars towards areas in which government negotiators/price setters have allowed large profit margins.

In recognition of this fact, Congressman Dennis Kucinich has proposed a bill, "The Free Market Drug Act," which eliminates the need to rely on patent monopolies to finance drug research. This bill would effectively double the current amount of public funding for drug research, with the funded agencies taking over responsibility for developing and testing drugs. Under the provisions of this bill, patents for the drugs developed with public funding would be placed in the public domain, so that these drugs could be sold in a competitive market, just as generics are presently9.

The system of negotiated prices or price controls, along the lines of the Canadian model, and the Kucinich system of direct public funding of prescription drug research with the drugs then sold in a competitive market, provide alternative mechanisms for reducing drug prices. In both cases there would be substantial savings, which could be devoted to other purposes, such as insuring the uninsured.

For purposes of this analysis, it is assumed that adopting a Canadian type system would lead to a reduction in drug prices that averages 50 percent of current prices. This is based loosely on the evidence in the Australian Productivity Commission's report (2???). It is assumed that the Kucinich Free Market Drug would lead to a reduction in drug prices of 70 percent from their current levels - effectively the price that consumers would pay if patented drugs lost their monopolies and they were sold in a competitive market. However, $20 billion of the savings under the Kucinich system would have to be used to finance new drug research, since the industry would no longer have the incentive to finance such research itself.

Table 2 shows the number of people who could be insured with the savings on the cost of prescription drugs in these two scenarios. The first column shows the CMS projections for drug spending for 2005. It is assumed that each state's spending on prescription drugs is proportional to its total spending on health care. The table shows that the country as a whole will spend $233.6 billion on drugs in 2005. California's share of this spending is projected to be $25.3 billion. The second column shows the projected savings assuming that bulk buying allows the government to cut the cost of prescription drugs by 50 percent. The savings for the country as a whole is projected to be $116.8 billion, with the savings for California projected to be $12.6 billion in this scenario.

The third column shows projected savings with the Kucinich Free Market Drug Act. In this case, it is assumed that prices will fall by approximately 70 percent if drugs were sold in a competitive market, although the government would have to increase its spending on bio-medical research by approximately $20 billion annually to replace the drug industry's spending. In this scenario, the net saving to the country is $143.5 billion, with California receiving $15.5 billion of these savings.

The fourth column shows the number of people currently uninsured nationwide and in each state, the same data shown in the fourth column of table 1. Column 5 shows the number of the uninsured who could be covered with the savings from bulk purchases of prescription drugs. For the country as a whole, these savings would be sufficient to insure 58,384,000 people. In the state of California, these savings would be able to ensure 5,925,000 people.

The sixth column shows the number of people who could be insured with the savings from the Free Market Drug Act. In the country as a whole the savings would be sufficient to insure 71,740,000 people. In California, the savings from having drugs sold in a competitive market would be sufficient to insure 7,281,000 people.

Columns six and seven show the percent of the uninsured that could be covered by the saving from buying drugs in bulk and from selling drugs in a competitive market, respectively. In the country as a whole, 71.3 percent of the uninsured could be covered by these savings. In California, the savings would be sufficient to cover 49.6 percent of the uninsured. The savings under the Free Market Drug Act would be sufficient to cover 87.7 percent of the uninsured nationwide, and 61.0 percent of the uninsured in California.

Table 2

Savings from Bulk Drug Purchases and Competitive Market Pricing

   

    

Savings

   

   

   

   

Current

 Bulk  

Free   

Currently  

   

Additional Coverage   

   

Spending

Buying

Market

Uninsured

BB

FM

BB

FM

   

(billions of current dollars)

(thousands)

United States

233.6

116.8

143.5

81,834

58,384

71,740

71.3%

87.7%

Alabama

3.7

1.8

2.3

1,167

1,108

1,361

94.9

116.6

Alaska

0.5

0.3

0.3

208

124

153

59.8

73.5

Arizona

3.4

1.7

2.1

1,707

1,001

1,230

58.6

72.0

Arkansas

1.9

1.0

1.2

801

633

778

79.0

97.1

California

25.3

12.6

15.5

11,945

5,925

7,281

49.6

61.0

Colorado

3.1

1.6

1.9

1,309

724

890

55.3

68.0

Connecticut

3.5

1.7

2.1

767

641

787

83.5

102.6

Delaware

0.7

0.4

0.4

185

172

211

93.0

114.3

District of Columbia

1.0

0.5

0.6

163

160

197

98.2

120.6

Florida

13.7

6.9

8.4

4,793

3,564

4,380

74.4

91.4

Georgia

6.3

3.1

3.8

2,499

1,680

2,064

67.2

82.6

Hawaii

1.1

0.5

0.7

346

274

336

79.1

97.2

Idaho

0.8

0.4

0.5

395

238

293

60.3

74.1

Illinois

10.2

5.1

6.3

3,492

2,390

2,936

68.4

84.1

Indiana

4.9

2.4

3.0

1,534

1,342

1,649

87.5

107.5

Iowa

2.3

1.2

1.4

637

638

784

100.2

123.1

Kansas

2.2

1.1

1.3

624

570

701

91.4

112.3

Kentucky

3.3

1.7

2.0

1,059

998

1,226

94.2

115.8

Louisiana

3.8

1.9

2.3

1,426

1,149

1,411

80.6

99.0

Maine

1.1

0.6

0.7

290

310

381

107.0

131.5

Maryland

4.5

2.3

2.8

1,354

956

1,175

70.6

86.8

Massachusetts

6.9

3.5

4.2

1,443

1,371

1,685

95.0

116.7

Michigan

8.2

4.1

5.0

2,538

2,128

2,615

83.8

103.0

Minnesota

4.7

2.3

2.9

1,020

1,072

1,317

105.1

129.1

Mississippi

2.0

1.0

1.3

875

688

846

78.7

96.7

Missouri

4.8

2.4

3.0

1,354

1,299

1,596

95.9

117.9

Montana

0.7

0.3

0.4

246

199

244

80.9

99.4

Nebraska

1.4

0.7

0.9

400

360

442

90.0

110.6

Nevada

1.3

0.6

0.8

700

326

400

46.5

57.2

New Hampshire

7.5

3.8

4.6

259

1,712

2,104

661.0

812.2

New Jersey

1.1

0.5

0.7

2,199

209

257

9.5

11.7

New Mexico

1.2

0.6

0.8

685

380

467

55.5

68.2

New York

19.7

9.9

12.1

5,646

4,262

5,237

75.5

92.8

North Carolina

6.3

3.1

3.9

2,439

1,759

2,161

72.1

88.6

North Dakota

0.6

0.3

0.4

144

167

205

115.8

142.3

Ohio

9.8

4.9

6.0

2,755

2,584

3,175

93.8

115.2

Oklahoma

2.5

1.3

1.6

1,066

749

920

70.3

86.3

Oregon

2.5

1.2

1.5

968

671

825

69.4

85.2

Pennsylvania

11.8

5.9

7.2

2,804

2,914

3,581

103.9

127.7

Rhode Island

1.0

0.5

0.6

249

257

316

103.2

126.8

South Carolina

3.0

1.5

1.9

1,055

918

1,128

87.0

106.9

South Dakota

0.7

.3

0.4

180

177

217

98.1

120.6

Tennessee

5.1

2.5

3.1

1,447

1,406

1,728

97.2

119.4

Texas

15.6

7.8

9.6

8,536

4,191

5,150

49.1

60.3

Utah

1.4

0.7

0.8

651

432

531

66.4

81.6

Vermont

0.5

0.2

0.3

136

122

150

89.8

110.3

Virginia

5.1

2.6

3.1

1,836

1,201

1,476

65.4

80.4

Washington

4.4

2.2

2.7

1,639

1,052

1,292

64.2

78.8

West Virginia

1.6

0.8

1.0

465

524

644

112.8

138.6

Wisconsin

4.6

2.3

2.8

1,253

1,173

1,441

93.6

115.0

Wyoming

0.3

0.2

0.2

143

78

96

54.5

67.0

Source: Author's calculations, see appendix.

Appendix

The first column in table shows national and state by state medical spending for 2003. The data for the national spending is taken from the CMS "National Health Expenditures; Aggregate and per Capita Amounts, Percent Distribution and Average Annual Percent Change by Source of Funds: Selected Calendar Years 1990-2013" (table 3). The spending data for individual states was derived from the CMS "Trends in State Health Care Expenditures and Funding, 1980-1998." Table 2, Personal Health Care Expenditures and Average Annual Percent Growth, by Regional and State: United States, Selected Calendar Years 1980-1998. The state data for 1998 were multiplied by the ratio of national spending in 2003 to national spending in 1998, effectively assuming that each state's share of health care spending did not change in this five-year period.

The second column shows an estimate of savings based on the assumption that spending that is currently paid through private insurers is instead paid through a universal Medicare type system. The estimate of total payments by private insurers and other third party payers for 2003, $687.6 billion, is taken from, CMS "2004, National Health Expenditures Projections", Table 3 National Health Expenditures; Aggregate and per Capita Amounts, Percent Distribution and Average Annual Percent Change by Source of Funds: Selected Calendar Years 1990-2013. The estimate of the administrative costs incurred by these insurers and third parties ($106.0 billion) is taken from Bureau of Economic Analysis' National Income and Product Accounts (NIPA, table 2.5.5 line 56). These data give a ratio of administrative expenses to payments of 15.4 percent. By comparison, the administrative expenses of Medicare are equal to 1.65 percent of benefits, this is the ratio of total administrative costs to total expenditures in the 2004 Annual Report of the Board of Trustees of the Federal Hospital Insurance and Federal Supplementary Medical Insurance Trust Funds, table II.B.1.

The second column assumes that the amount of potential savings from introducing a universal Medicare type system is proportional to each state's spending on medical care, after Medicare and Medicaid spending were deducted. State spending on Medicare is assumed to be proportionate to its share of enrollees multiplied by each state's ratio of per capita personal income to the national average. Data on 2003 Medicare enrollees was taken from CMS. Medicaid spending by state from The Kaiser Commission on Medicaid and the Uninsured, "2002 State and National Medicaid Spending Data, CMS-64" Table 1.

The third column uses an alternate procedure to calculate the waste eliminated from switching to universal Medicare type system. It relies on an estimate produced by Lewin Group, that the administrative savings in California that would result from the adoption of a universal Medicare type system would be equal to 9.3 percent of total health care spending (Lewin Group's analysis of the Cal Care single payer proposal for California, 2002, Figure 17 []). National savings from the adoption of a universal Medicare type system are assumed to be equal to the 9.3 percent savings in administrative costs that the Lewin Group estimated for California, with each state's savings assumed to be proportional to its share of non-Medicare, non-Medicaid health care spending.

Column 4 shows the number of people who are uninsured at some point in the year for 2003. This data is taken from Families USA analysis of Census Bureau data, "One in Three: Non-Elderly Families Without Health Insurance 2002-2003." 

Column 5 shows the number of uninsured that could be covered nationally and each state by dividing the savings as estimated in column 2, by the cost of providing insurance. The latter is assumed to average $3,000 per person. This is based on an estimate of $3,383 for single employee based coverage and $1,786 for single individually purchased insurance. "Update on Individual Health Insurance" Kaiser Family Foundation/ eHealth Insurance P5, August 2004. This number was multiplied by 0.8623 based on the fact that 13.77 percent of insurance premiums go to unnecessary administrative costs. Furthermore, it is assumed that the average uninsured person is without insurance for two thirds of the year, so that the cost of insuring a person for the whole year is equal to two-thirds of the full-year premium. Each state's insurance cost is assumed be proportional to the ratio of per capita personal income in that state to the national average.

Column 6 does the same exercise based on the estimates of savings from column 3, which are derived from the Lewin Group's estimate. Column 7 is the percentage of the uninsured who could be covered using the projections shown in column 5. Column 8 is the percentage of the uninsured who could be covered using the projections shown in column 6.

The first column in table 2 shows projected national and state by state spending for prescription drugs for 2005. The national figure is taken from , CMS 2004, National Health Expenditures Projections, Table 3; Aggregate and per Capita Amounts, Percent Distribution and Average Annual Percent Change by Source of Funds: Selected Calendar Years 1990-2013. State spending figures are assumed to be proportional to state spending on healthcare, which is taken from CMS "Trends in State Health Care Expenditures and Funding, 1980-1998." Table 2, Personal Health Care Expenditures and Average Annual Percent Growth, by Regional and State: United States, Selected Calendar Years 1980-1998. Column 2 shows projected savings assuming that bulk buying of prescription drugs reduces the cost nationally, and in each state, by 50 percent. Column 3 shows projections that assume that allowing drugs to be sold in a competitive market (without patent monopolies) will reduce the cost of buying drugs by 70 percent. The projection for national savings deducts $20 billion from this estimate to cover the cost of additional publicly supported drug research (see Baker and Chatani 2002, "Promoting Good Ideas on Drugs: Are Patents the Best Way?", Center for Economic and Policy Research. The state level savings are assumed to be proportional to each state's share of national health care spending.

The number of uninsured who could be covered shown in columns five and six are calculated in the same way as in columns five and six of table one. Similarly, the percentage of the uninsured who can be covered with the savings from lower cost drugs, shown in columns seven and eight, are calculated in the same way as in columns seven and eight of table 1.


Footnotes:

1. Dean Baker is economist and Co-Director, at the Center for Economic and Policy Research.

2. This discussion is based on health care statistics from the Organization for Economic Cooperation and Development. This data can be found in the tables in "OECD Health Care Data 2004 - Frequently Requested Data".

3. See H. Boushey, 2004, "Analysis of the Upcoming Release of 2003 Data on Income, Poverty, and Health Insurance." Center for Economic and Policy Research.

4. See D. Himmelstein and S. Woolhandler, 1991. "The Deteriorating Administrative Efficiency of the U.S. Health Care System," New England Journal of Medicine, 324: 1253-1258.

5.  The calculations in the study implicitly assume that the only reason for the difference in administrative costs between the United States and Canada is the difference in the system of providing health insurance. While this undoubtedly the most important factor explaining the differences in costs, there are other factors that could have an impact, most obviously differences in the system of legal liability.

6.  This analysis can be found at www.healthcareoptions.ca.gov

7.  The Australian Productivity Commission did an excellent analysis of cross-country spending on prescription drugs which can be found at http://www.pc.gov.au/research/commres/pbsprices/finalreport/pbsprices.pdf. While the purpose of this study was to compare Australian prices with those in other countries, it also provides some basis for comparing the prices paid in other countries. In nearly every comparison, the prices paid in the United States were by far the highest, often being more than twice as much as the average price in paid in other rich countries.

8.  See A. Sager and D. Socolar, 2003. "61 Percent of Medicare's New Prescription Drug Subsidy is Windfall Profit to Drug Makers," Health Reform Program, Boston University School of Public Health.

9. An outline of this bill can be found at http://www.house.gov/kucinich/issues/freemarketdrugact.htm