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Table 2 Costs and Benefits of Certificate of Need Regulation (millions of 2008 dollars)

From: Certificate of need laws: a systematic review and cost-effectiveness analysis

COST CATEGORY

COSTS

BENEFITS

NOTES

Expected

Lower bound

Upper bound

Expected

Lower bound

Upper bound

Government Regulatory Costs

20

9

31

–

–

–

 

 Federal

–

–

–

–

–

–

 

 State

20

9

31

–

–

–

[A]

Compliance Costs

146

109

182

–

–

–

 

 Administrative costs

146

109

182

–

–

–

[B]

Key Impacts

3272

677

7836

2786

1291

4418

 

 Health expenditures

2023

104

6044

2023

848

3229

 

  Reduction in CABG facilities

–

–

–

456

233

711

[C]

  Medicare spending

–

–

–

1566

416

2748

[D]

  All other health spending

2023

104

6044

–

  

[E]

 Patient time losses

2

1

3

   

[F]

 Health status

1247

314

3746

764

(1)

1974

 

  Morbidity losses

–

–

–

–

–

–

 

  Mortality losses

1247

132

3541

764

(1)

1974

 

   General elderly hospital mortality

1027

44

3303

–

  

[G]

   CABG mortality, all patients

   

463

(199)

1455

[H]

   CABG mortality, Medicare patients, stringent CON states

   

300

(4)

807

[I]

   CABG mortality rates, Medicare patients non-stringent CON states

220

(97)

701

   

[J]

Social Welfare Losses

512

66

1453

861

295

1511

 

 Efficiency losses from tax collection

8

4

13

755

192

1400

[K]

 Efficiency losses from regulatory costs

504

58

1446

106

54

168

[L]

GRAND TOTAL

3949

932

9380

3647

1658

5821

 

NET BURDEN (COSTS MINUS BENEFITS)

302

(3556)

5987

Probability that benefits exceed costs:

54%

  1. Update: 5/16/2015
  2. Note: All lower and upper bounds are calculated using Latin Hypercube simulations in @RISK. Therefore, sub-totals generally are smaller than the sum of their components. All reported simulation results are based on 100,000 iterations. For simplicity, both costs and benefits are shown as positive numbers. However, costs are equivalent to negative benefits and vice-versa. Cases in which negative numbers appear under either costs or benefits illustrate instances in which an impact is not statistically significant using conventional standards: that is we are not 95% certain that the estimated impact does not fall above or below zero.