REPORT TO THE CONGRESS 

Issues in a Modernized

Medicare Program

JUNE 2005
The Medicare Payment Advisory Commission (MedPAC) is an independent federal body

established by the Balanced Budget Act of 1997 (P.L. 105–33) to advise the U.S. Congress

on issues affecting the Medicare program. In addition to advising the Congress on payments

to health plans participating in the MedicareChoice program and providers in Medicare’s

traditional fee-for-service program, MedPAC is also tasked with analyzing access to care,

quality of care, and other issues affecting Medicare.

The Commission’s 17 members bring diverse expertise in the financing and delivery of

health care services. Commissioners are appointed to three-year terms (subject to renewal) by

the Comptroller General and serve part time. Appointments are staggered; the terms of five

or six Commissioners expire each year. The Commission is supported by an executive

director and a staff of analysts, who typically have backgrounds in economics, health policy,

and public health.

MedPAC meets publicly to discuss policy issues and formulate its recommendations to the

Congress. In the course of these meetings, Commissioners consider the results of staff

research, presentations by policy experts, and comments from interested parties. (Meeting

transcripts are available at www.medpac.gov.) Commission members and staff also seek

input on Medicare issues through frequent meetings with individuals interested in the

program, including staff from congressional committees and the Centers for Medicare &

Medicaid Services (CMS), health care researchers, health care providers, and beneficiary

advocates.

Two reports—issued in March and June each year—are the primary outlets for Commission

recommendations. In addition to annual reports and occasional reports on subjects requested

by the Congress, MedPAC advises the Congress through other avenues, including comments

on reports and proposed regulations issued by the Secretary of the Department of Health and

Human Services, testimony, and briefings for congressional staff. 
JUNE 2005

601 New Jersey Avenue, NW • Suite 9000 • Washington, DC 20001

(202) 220-3700 • Fax: (202) 220-3759 • www.medpac.gov

REPORT TO THE CONGRESS

Issues in a Modernized

Medicare Program

June 15, 2005

The Honorable Richard B. Cheney

President of the Senate

U.S. Capitol

Washington, DC 20510

Dear Mr. Vice President:

I am pleased to submit the Medicare Payment Advisory Commission’s June 2005 Report to the Congress:

Issues in a Modernized Medicare Program. This report fulfills MedPAC’s legislative mandate to examine

issues affecting the Medicare program and to make specific recommendations to the Congress.

In this report, we:

• examine issues related to the implementation of Part D, Medicare’s new outpatient prescription 

drug benefit;

• provide an overview of the Medicare Advantage program as well as recommendations regarding

payment policy;

• address payment system refinements for dialysis and post-acute care; and

• consider the use of clinical- and cost-effectiveness analysis to improve Medicare’s ability to be 

a value-based purchaser.

The report also fulfills three specific mandates from the Medicare Prescription Drug, Improvement, and

Modernization Act of 2003 (MMA) to:

• assess the method used for determining the adjusted average per capita cost (MMA Section 211(f))

(Chapter 2 of this report);

• report on adjustment of payment for ambulatory payment classifications for specified drugs to take

into account overhead and related expenses (MMA Section 621(a)(1)) (Chapter 6 of this report); and

• study the impact of legislated changes on critical access hospitals (MMA Section 433) (Chapter 7 

of this report).

The report concludes by fulfilling our statutory obligation to analyze the Secretary of HHS’s estimate of the

update for physician services (Chapter 9 of this report).

Sincerely,

Glenn Hackbarth, J.D.

Chairman

Enclosure

601 New Jersey Avenue, NW • Suite 9000

Washington, DC 20001

202-220-3700 • Fax: 202-220-3759

www.medpac.gov

Glenn M. Hackbarth, J.D., Chairman

Robert D. Reischauer, Ph.D., Vice Chairman

Mark E. Miller, Ph.D., Executive Director
June 15, 2005

The Honorable J. Dennis Hastert

Speaker of the House of Representatives

U.S. House of Representatives

H232 Capitol Building

Washington, DC 20515

Dear Mr. Speaker:

I am pleased to submit the Medicare Payment Advisory Commission’s June 2005 Report to the Congress:

Issues in a Modernized Medicare Program. This report fulfills MedPAC’s legislative mandate to examine

issues affecting the Medicare program and to make specific recommendations to the Congress.

In this report, we:

• examine issues related to the implementation of Part D, Medicare’s new outpatient prescription 

drug benefit;

• provide an overview of the Medicare Advantage program as well as recommendations regarding

payment policy;

• address payment system refinements for dialysis and post-acute care; and

• consider the use of clinical- and cost-effectiveness analysis to improve Medicare’s ability to be 

a value-based purchaser.

The report also fulfills three specific mandates from the Medicare Prescription Drug, Improvement, and

Modernization Act of 2003 (MMA) to:

• assess the method used for determining the adjusted average per capita cost (MMA Section 211(f))

(Chapter 2 of this report);

• report on adjustment of payment for ambulatory payment classifications for specified drugs to take

into account overhead and related expenses (MMA Section 621(a)(1)) (Chapter 6 of this report); and

• study the impact of legislated changes on critical access hospitals (MMA Section 433) (Chapter 7 

of this report).

The report concludes by fulfilling our statutory obligation to analyze the Secretary of HHS’s estimate of the

update for physician services (Chapter 9 of this report).

Sincerely,

Glenn Hackbarth, J.D.

Chairman

Enclosure

601 New Jersey Avenue, NW • Suite 9000

Washington, DC 20001

202-220-3700 • Fax: 202-220-3759

www.medpac.gov

Glenn M. Hackbarth, J.D., Chairman

Robert D. Reischauer, Ph.D., Vice Chairman

Mark E. Miller, Ph.D., Executive Director
Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 v

This report was prepared with the assistance of many

people. Their support was key as the Commission

considered policy issues and worked toward consensus on

its recommendations.

Despite a heavy workload, staff members of the Centers

for Medicare & Medicaid Services were particularly

helpful during preparation of the report. We thank Sabrina

Ahmed, Sharon Ahmed, Susanne Asplen, Sally Burner,

William Cymer, Anne Hornsby, Duane Hudson, Mel

Ingber, Tamara Syrek Jensen, Nora Kraemer, Herb Kuhn,

George Morey, Solomon Mussey, Paul Olenick, Stephen

Phillips, Steve Phurrough, Lana Price, Cynthia Read,

Cheri Rice, Carolyn Rimes, Edward Sekscenski, John

Shatto, Don Thompson, and Carlos Zarabozo.

The Commission also received valuable insights and

assistance from others in government, industry, and the

research community who generously offered their time

and knowledge. They include Douglas Armstrong, Bob

Berenson, Melinda Beeuwkes Buntin, Kevin Bozic, 

Judith Cahill, Ronald Callahan, Emily Costich, James

D’Antonio, Kathleen Dalton, Gestur Davidson, Diana

Dennett, Bob Doherty, Julia Doherty, William Dombi,

Laura Dummit, Brandon Durbin, Elizabeth Eaton, Jack

Ebeler, Walter Frontera, Bruce Gans, Daniel Gaylin, 

Kurt Gillis, George Greenberg, Tim Gronninger, Kris

Haltmeyer, Robert Haralson, Elizabeth Hargrave, Jeannie

Harvell, Jack Hoadley, Chris Hogan, Kurt Hoppe, Carrie

Hoverman, Carole McGeehan Johnson, Lisa Joldersma,

John D. Jones, Carol Kelly, Heidi Klingbeil, Korbin Liu,

David Lovett, Diane Makuc, Barbara Manard, Stephanie

Maxwell, Don May, Joseph McCarthy, Brian McGrory,

Sharon McIlrath, Kaycee Misiewicz, Robert Morrell, Tom

Morris, Ira Moscovice, Michael Munin, Ellen O’Brien,

Dennis Phelps, Parminder Phull, Jon Ratner, Denise

Remus, Rick Seagrist, John Sheehan, Eric Shell, Kathleen

Smith, Rick Smith, Neeja Sood, Rodney Spangler, Gary

Stein, Bruce Steinwald, Sharman Stephens, Myra

Tanamor, Anna Theisen-Olson, Cindy Thomas, Tim

Tyler, Howard Weiss, Sheldon Weisgrau, Alan White,

Richard White, and Steve Zuckerman. 

Once again, the programmers at Social and Scientific

Systems provided highly capable assistance to

Commission staff. In particular, we appreciate the hard

work of Valerie Aschenbach, Tom Bell, Daksha Damera,

Deborah Johnson, John May, Jeff McCartney, Scott

Roberts, Fred Rohde, Mary Beth Spittel, Charles

Thomson, Susan Tian, and Arlene Turner.

Finally, the Commission wishes to thank Mimi Cantwell

and Kathleen Halverson for their help editing and

producing this report. 

Acknowledgments

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v

Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix

Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi

Executive summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .xv

Chapters

1 Monitoring the implementation of Part D . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3

Description of the Part D benefit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5

Performance measures for evaluating Part D implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6

Paying plans, setting premiums, and enrollment in Part D . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .14

The Medicare discount drug card and beneficiary outreach for Part D . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23

Formulary exceptions and the appeals processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .27

Looking forward: Electronic prescribing and other areas of future research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .33

2 Medicare Advantage payment areas and risk adjustment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .41

AAPCCs vary widely . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .43

How can Medicare improve payment areas for MA local plans? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .44

Payment area recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .50

How accurately does the CMS–HCC model reflect cost differences? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .52

3 The Medicare Advantage program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .59

Overview of changes to the managed care program under the MMA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .61

What are the new types of plans? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .62

Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .69

Enrollment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .72

Benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .73

The MA bidding process for 2006 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .74

Financial neutrality under the 2006 bidding system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .78

4 Payment for dialysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .87

Improving the current payment system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .88

Modernizing the outpatient dialysis payment system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .98

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 vii

Table of contents
5 Payment for post-acute care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .105

Comparing outcomes and spending for beneficiaries who have had a hip or knee replaced . . . . . . . . . . . . . . . . . . . . . . . . . . . . .107

Comparing the patient assessment tools used in post-acute care settings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .114

Assessing the skilled nursing facility PPS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .120

Assessing the home health PPS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .126

6 Payment for pharmacy handling costs in hospital outpatient departments . . . . . . . . . . . . . . . . . . . . . . .137

Is a payment adjustment needed? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .139

How should a payment adjustment be structured? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .142

How should handling costs be measured? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .143

What are the options for collecting data? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .149

A longer term agenda: Broader payment bundles in the outpatient PPS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .150

7 Critical access hospitals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .159

Congressional mandate and background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .160

How does conversion to CAH status affect hospitals? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .162

Is quality of care at low-volume rural hospitals comparable to that of higher volume rural hospitals? . . . . . . . . . . . . . . . . . . . .169

MMA changes to the CAH program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .172

Summary of findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .174

8 Using clinical and cost effectiveness in Medicare . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .179

Medicare’s coverage and payment processes consider clinical effectiveness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .180

Understanding cost-effectiveness analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .182

Medicare’s coverage and payment processes do not explicitly use cost-effectiveness analysis . . . . . . . . . . . . . . . . . . . . . . . . . .187

The future of cost-effectiveness analysis in Medicare . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .188

9 Review of CMS’s preliminary estimate of the physician update for 2006 . . . . . . . . . . . . . . . . . . . . . . . . .197

Spending growth in 2004 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .198

Preliminary estimate of the physician update for 2006 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .200

Making the case for change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .202

Appendix

A Commissioners’ voting on recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .211

Acronyms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .217

More about MedPAC

Commission members . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223

Commissioners’ biographies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225

Commission staff . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229

viii Ta b le of contents
1 Monitoring the implementation of Part D . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3

1-1 Out-of-pocket spending under the low-income drug benefit, 2006 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6

1-2 Examples of performance measures purchasers use to evaluate drug benefit management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7

1-3 Example of how monthly enrollee premiums could vary for three prescription drug plans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .17

1-4 Variation in characteristics of PDP regions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .22

2 Medicare Advantage payment areas and risk adjustment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .41

2-1 Differences in price of inputs and special payments to hospitals account for about 15 percent of variation in AAPCCs . . . . . . . .44

2-2 How payment areas compare with market areas of Medicare Advantage and private-sector plans . . . . . . . . . . . . . . . . . . . . . . . .49

2-3 CMS–HCCs better predict beneficiaries’ costliness than a demographic model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .52

3 The Medicare Advantage program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .59

3-1 Medicare Advantage changes as a result of the MMA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .61

3-2 Plans improve, but rates are still low on some measures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .69

3-3 MA plans and the FFS program have similar patient experience scores . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .70

3-4 Selected quality requirements and measures vary by type of Medicare Advantage plan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .72

3-5 Example of calculating a regional benchmark . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .75

3-6 Example of premium calculations under 2006 bidding process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .75

4 Payment for dialysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .87

4-1 Staffing and productivity vary between freestanding and hospital-based providers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .89

4-2 AAP and ASP for dialysis injectables vary somewhat in 2005 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .94

4-3 Estimated impact of MedPAC’s recommendations to refine outpatient dialysis payment policies, 2006 . . . . . . . . . . . . . . . . . . . .96

5 Payment for post-acute care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .105

5-1 Selected characteristics of patients with hip or knee replacement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .109

5-2 Characteristics of discharging hospitals and proximity to facilities for patients with hip or knee replacement . . . . . . . . . . . . . .110

5-3 Functional status outcomes for patients with hip or knee replacement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .111

5-4 Outcomes for patients with hip or knee replacement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .112

5-5 Frequency, time period covered, and measurement scales differ across post-acute 

patient assessment tools required by Medicare . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .115

5-6 Patient assessment tools do not consistently use diagnosis codes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .116

5-7 Examples of the differences in functional status measures included in 

post-acute patient assessment tools required by Medicare . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .117

5-8 Wide range in cognitive status measures evaluated by patient assessment tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .118

5-9 The home health product changed between 1997 and 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .129

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 ix

Tables
6 Payment for pharmacy handling costs in hospital outpatient departments . . . . . . . . . . . . . . . . . . . . . . .137

6-1 Study drugs and biologicals with highest payments in 2002, ranked highest to lowest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .138

6-2 Study radiopharmaceuticals with highest payments in 2002, ranked highest to lowest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .139

6-3 Categories for drugs, biologicals, and radiopharmaceuticals and their relative handling costs . . . . . . . . . . . . . . . . . . . . . . . . . . .145

7 Critical access hospitals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .159

7-1 Legislation and changes in regulation make CAH conversions easier and increase payments . . . . . . . . . . . . . . . . . . . . . . . . . . .161

7-2 CAHs benefit from large increases in outpatient and swing-bed payments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .164

7-3 Changes in service volumes per hospital following conversion to CAH status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .166

7-4 Changes in service offerings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .167

8 Using clinical and cost effectiveness in Medicare . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .179

8-1 Cost effectiveness of selected services in the Medicare population . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .183

9 Review of CMS’s preliminary estimate of the physician update for 2006 . . . . . . . . . . . . . . . . . . . . . . . . .197

9-1 Spending growth varies by type of service, 2003–2004 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .198

9-2 Preliminary sustainable growth rate, 2006 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .200

9-3 Estimate of the update for physician services, 2006 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .201

9-4 Impact of the practice expense GPCI on the payment rate for an equipment-intensive service . . . . . . . . . . . . . . . . . . . . . . . . . .202

x Ta b les
1 Monitoring the implementation of Part D . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3

1-1 Standard drug benefit in 2006 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5

1-2 CMS established 34 PDP regions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .15

1-3 Percentage geographic variation in drug spending and simulated premiums for a sample of privately insured individuals . . . . . .18

1-4 Geographic patterns of per capita drug spending vary by data source . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .21

1-5 Notice required by Hernandez v. Meadows settlement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .31

2 Medicare Advantage payment areas and risk adjustment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .41

2-1 Three definitions of payment areas, southern Texas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .46

2-2 Larger payment areas result in more stable AAPCCs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .47

2-3 Larger payment areas smooth differences in AAPCCs among counties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .48

2-4 Larger payment areas have more Medicare beneficiaries and more stable AAPCCs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .48

2-5 Geographic differences in AAPCCs are greater in larger payment areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .50

3 The Medicare Advantage program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .59

3-1 Comparison of private plan versus FFS costs, by market area, 2004 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .62

3-2 Enrollment in Medicare private plans, by plan type . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .63

3-3 Medicare Advantage regions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .64

3-4 Risk corridors for regional PPOs under Medicare Advantage, 2006–2007 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .66

3-5 Example of payments to plans with different enrollment patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .77

4 Payment for dialysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .87

4-1 Dialysis adequacy and anemia status did not differ among providers in 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .90

5 Payment for post-acute care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .105

5-1 One-third of beneficiaries discharged from hospitals use post-acute care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .106

5-2 Distribution of SNF stays, by length of stay, in 2001 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .121

5-3 Determining case-mix adjusted SNF payment rate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .121

5-4 RUG–III classification scheme . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .122

5-5 Clinical, functional, and service information from OASIS determines patients’ home health case-mix classification . . . . . . . .127

6 Payment for pharmacy handling costs in hospital outpatient departments . . . . . . . . . . . . . . . . . . . . . . .137

6-1 Labor and supplies components of direct pharmacy expenses are stable . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .141

6-2 Pharmacy and nuclear medicine functions and handling costs covered by this study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .144

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 xi

Figures
7 Critical access hospitals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .159

7-1 The CAH program is growing rapidly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .161

7-2 Most CAHs are 15 to 35 miles from other hospitals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .162

7-3 CAH payments, by distance from the nearest hospital . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .168

7-4 CAH costs per inpatient day rose faster than those of comparison hospitals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .169

7-5 Patient-safety scores, other than death in low-mortality DRGs, are better in smaller rural hospitals . . . . . . . . . . . . . . . . . . . . . .170

7-6 Mortality rates are higher in smaller rural hospitals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .171

8 Using clinical and cost effectiveness in Medicare . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .179

8-1 The impact of services on outcomes and costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .183

8-2 Proposed criteria for making coverage decisions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .189

9 Review of CMS’s preliminary estimate of the physician update for 2006 . . . . . . . . . . . . . . . . . . . . . . . . .197

9-1 Volume grew more rapidly in 2004 than in previous years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .199

9-2 Through 2004, actual spending for physician services exceeded target . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .201

9-3 Direct expenses in practice expense RVUs, 2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .203

9-4 Physician fee schedule payment localities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .204

xii Figures
Executive summary

The Medicare Prescription Drug, Improvement, and

Modernization Act of 2003 (MMA) makes many changes

to the Medicare program. In its preparation to implement

the MMA, CMS has had to deal with complicated issues

balancing administrative complexity, burden on providers,

beneficiary protection, and protection of the Medicare

trust funds and taxpayers. In this report, the Commission

speaks to some of these key implementation issues. 

It also looks at the larger questions of how the Medicare

program can pay more accurately for services within and

across settings. We also report on three issues that the

Congress mandated in the MMA: (1) Medicare Advantage

(MA) program payment areas and risk adjustment, 

(2) pharmacy and nuclear medicine handling costs, and 

(3) critical access hospitals.

Monitoring the implementation of Part D

The MMA introduced a voluntary Medicare prescription

drug benefit, which begins in 2006. In this program,

private plans will deliver a drug benefit to their enrollees,

and Medicare will pay the plans based on a nationwide

average of bids. Beneficiaries who elect to participate in

Part D will pay a premium, which will vary to some extent

across the country. In Chapter 1, we examine several

aspects of Medicare’s new prescription drug coverage. 

We review measures that CMS could use to evaluate plan

performance and monitor Part D. CMS will collect a large

amount of data on Part D—including drug utilization, 

and measures such as enrollee satisfaction and claims

processing accuracy. The Commission recommends that

the Secretary develop a plan to assure the timely delivery

of Part D data to congressional support agencies so that

they can better inform the Congress about the drug

benefit’s impact on cost, quality, and access. 

Plans are likely to use techniques developed in the

commercial market both to help manage utilization

(formularies and varied cost sharing) and to ensure

members’ access to needed drugs (appeals processes). 

In established commercial plans, few members appeal

denied formulary exceptions—and when physicians

pursue appeals for members, plans report high approval

levels. However, as beneficiaries join plans for the first

time, the appeals process could be more important,

particularly for beneficiaries dually eligible for Medicare

and Medicaid because appeal rights under Part D 

may differ from those under Medicaid. Judging from

implementation of the discount drug card program, CMS

will face challenges in educating Medicare beneficiaries

about prescription drug plan choices. Federal, state, and

private outreach proved relatively ineffective in enrolling

large numbers of beneficiaries in the discount drug card

program. Automatic enrollment (with an option for the

beneficiary to decline) for beneficiaries in state-sponsored

and MA plans accounted for a large share of the 

overall enrollment. 

Medicare Advantage payment areas and risk

adjustment (mandated study)

The MMA directs MedPAC to study several issues related

to the payment system for MA local plans. Our findings,

discussed in Chapter 2, are: county-level adjusted average

per capita costs (AAPCCs) vary widely, many counties

have large annual changes in AAPCCs, and adjacent

counties often have very different AAPCCs.

To stabilize rates and approximate private-sector market

areas, the Commission recommends that the Congress

establish larger payment areas for MA local plans.

Specifically, among counties in metropolitan statistical

areas (MSAs), payment areas should consist of counties

that are located in the same state and the same MSA.

Among counties outside MSAs, payment areas should

consist of counties in the same state that accurately reflect

health care market areas—such as health service areas. 

We also recommend that the Secretary update the health

service areas. 

As requested, we also evaluated the predictive accuracy of

the CMS–hierarchical condition category risk-adjustment

model. We found that it performs significantly better than

a model similar to the demographic model that CMS has

used in the past.

The Medicare Advantage program

The Commission strongly supports giving Medicare

beneficiaries a choice to join private plans, because these

plans have greater flexibility to improve the efficiency and

quality of beneficiaries’ health care services. The

Commission recognizes that the Congress created the

Medicare Advantage program in the MMA in part to

encourage expansion of private plans. The MA program—

among other changes—introduces bidding by plans and

includes certain payment provisions that raise payment

rates. The Commission has long recommended that there

should be financial neutrality between private plans and

fee-for-service (FFS) Medicare. Neutrality 

will exert consistent financial pressure on FFS and private

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 xv

Executive summary
plans and encourage the entry of viable plans that will

remain in markets long term. In Chapter 3, the

Commission recommends that the Congress and CMS

maintain neutrality between private plans and FFS

Medicare, as well as among private plans, by:

• collecting quality measures for the FFS program that

would enable comparison with the MA program; 

• eliminating the preferred provider organization (PPO)

stabilization fund;

• clarifying that regional plans should submit bids 

that are standardized for the region’s Medicare

Advantage–eligible population; 

• putting in law the scheduled phase-out of the holdharmless policy;

• removing the effect of payments for indirect medical

education from the MA plan benchmarks; and 

• linking payment benchmarks for MA plans to 100

percent of FFS costs, while returning savings from

bidding to plans by rewarding quality performance.

The Commission also finds that since the bidding

process is underway and a sharp change in payments

could be disruptive, alternative methods could link

payments to 100 percent of FFS.

Payment for dialysis

The MMA improved payment for dialysis services—

for example, it added a case-mix adjuster to the payment

system. But under current law and regulations, Medicare

pays dialysis providers differently based on site of 

care and type of drug. In Chapter 4, the Commission

recommends a series of changes to rationalize payment

policies. Medicare should pay the same amount for

composite-rate services at hospital-based and at

freestanding dialysis facilities and should then combine

the composite rate with the add-on adjustment the MMA

created. In addition, Medicare should use the same

payment method—average sales price (ASP)—to pay 

for all dialysis drugs provided by both facility types.

Because of concerns about the accuracy of the ASP, we

also recommend that the Secretary collect acquisition cost

data from dialysis providers to determine whether ASP

accurately reflects the prices that dialysis providers pay.

However, rationalizing payment for composite-rate

services and dialysis injectables is only an interim

solution; Medicare should also broaden the payment

bundle and link payment to quality to modernize this

payment system. 

Payment for post-acute care

Doctors and discharge planners should help beneficiaries

choose their post-acute care setting based on patient

characteristics, their care needs, and the outcomes in

different settings. In Chapter 5—after comparing hip and

knee replacement patients in different settings—we find

that costs and outcomes differ by setting. However, we

found it difficult to evaluate the comparisons because 

the characteristics of patients differ across settings and

because there is no common assessment instrument. In

fact, each post-acute care setting uses a different patient

assessment tool; we describe the tools’ characteristics in

the chapter. Until a common instrument becomes

available, it may be useful to specify admission criteria 

for each setting, as we have recommended previously for

long-term care hospitals. 

We also examined the prospective payment systems

(PPSs) that CMS uses to pay for skilled nursing facility

and home health care. Refining the skilled nursing 

facility PPS to better distribute payment for nontherapy

ancillary costs and adjusting payments based on patient

characteristics would improve this system’s performance.

The home health PPS may fail to adequately account for

cost differences across patient categories and agencies.

Future work should examine how to correct problems with

payments in these settings to ensure that the payments

better track the resource needs of different patients. 

Payment for pharmacy handling costs in

hospital outpatient departments 

(mandated report)

The MMA mandated that MedPAC report on whether the

Secretary should adjust payments in the outpatient PPS 

to account for pharmacy and nuclear medicine handling

costs. The issue arises because Medicare will begin to pay

for certain drugs, biologicals, and radiopharmaceuticals

based on acquisition costs in 2006. Previously, Medicare’s

payment rates for these items were higher, providing

hospitals with sufficient resources to cover handling costs. 

In Chapter 6, we conclude that handling costs are

nontrivial and an adjustment is warranted. Any adjustment

should be budget neutral, because when CMS established

the outpatient PPS, it based payments on hospital charges

xvi Executive summary
that reflected these handling costs. The Secretary should

establish separate, budget-neutral payments to cover the

costs that hospitals incur for handling separately paid

drugs, biologicals, and radiopharmaceuticals. The

Secretary should also: define a set of handling fee

ambulatory payment classifications (APCs) that group 

the products based on their attributes that affect handling

costs; instruct hospitals to submit charges for those APCs;

and base payment rates for the handling fee APCs on

submitted charges, reduced to costs. However, although

warranted, creating handling fee APCs would continue the

trend toward further separating payments for individual

items and services in the outpatient PPS. Larger payment

bundles would create stronger incentives for efficiency in

the outpatient PPS, including incentives for efficiently

furnishing drugs.

Critical access hospitals (mandated report)

The Congress mandated that MedPAC study the effects 

of the critical access hospital (CAH) provisions in the

MMA. In Chapter 7, we find that the CAH program has

succeeded in protecting the financial viability of many

small rural hospitals and that closures of CAHs have

almost ceased. We estimate that about 1,300 hospitals 

will be in the program by the end of 2005. We expect 

cost-based payments for those CAHs to total about 

$5 billion in 2006—roughly $1.3 billion more than what

PPS payments would have been for those same services.

As a result of the CAH provisions in the MMA, a few

more hospitals will convert this year, but conversions 

will effectively end after 2005. 

Additionally, we found that some CAHs are located 

quite close to other providers. In 2003, approximately 

17 percent of cost-based Medicare payments to CAHs

went to CAHs that were 15 or fewer miles from another

hospital. This finding raises the issue of competition

between CAHs and providers paid under a Medicare PPS.

For example, Medicare payments to CAHs for post-acute

patients in swing beds (beds that CAHs can use for both

acute and post-acute patients) exceed rates paid to

competing SNFs. In addition, CMS does not require

CAHs to report on quality of care for SNF patients.

Payment modifications and other adjustments may 

need to be made to ensure fair competition.

Using clinical and cost effectiveness 

in Medicare

Policymakers are looking for ways to use Medicare’s

resources more efficiently. Using information about

clinical effectiveness is one way to do so. MedPAC

supports the evidence-based process that CMS uses to

make coverage decisions and, more recently, to link

coverage with a requirement for data collection. Costeffectiveness analysis has the potential to promote care

that is more cost efficient and higher quality. Medicare

does not explicitly consider cost-effectiveness information

in either the coverage or payment process. As we discuss

in Chapter 8, before Medicare can routinely use costeffectiveness analysis, valid concerns will need to be

addressed about its methods. The Secretary could play 

an important role in standardizing the methods in these

analyses. Opportunities for the program to begin

considering such information include collecting it from

manufacturers in the coverage process (when available),

sponsoring cost-effectiveness studies, providing highquality studies to beneficiaries and health professionals,

and using available high-quality studies to prioritize payfor-performance and disease management initiatives. 

Review of CMS’s preliminary estimate of the

physician update for 2006

Every year, CMS calculates a preliminary estimate of the

next payment update for physician services and MedPAC

reviews it in our June report to the Congress. For 2006,

CMS’s estimate is an update of –4.3 percent. In Chapter 9,

we find that CMS used estimates in calculating the update

that are consistent with recent trends. The primary factor

leading to this negative update is that the volume of

physician services has increased at a faster rate than the

economy has grown. As a result, the difference between

target and actual spending in the update equation has

grown, as well. Our review shows that the gap is now 

so large that likely changes in other parameters of the

equation will not be sufficient to change the calculated

update from –4.3 percent.

CMS reports a 15.2 percent one-year growth in spending

for physician services in 2004. This rapid growth in

spending raises questions about whether all the services

are appropriate and supports recommendations that

MedPAC has made on paying for performance, measuring

resource use, reforming the payment update for physician

services, and developing quality standards for imaging

providers. Additional recommendations could come from

work that the Commission is planning on laboratory

services, physical therapy, and possible mispricing of

payments under the physician fee schedule. 

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 xvii

Monitoring the 

implementation of Part D

CHAPTER 1
RECOMMENDATION

The Secretary should have a process in place for timely delivery of Part D data to

congressional support agencies to enable them to report to the Congress on the drug

benefit’s impact on cost, quality, and access.

COMMISSIONER VOTES: YES 15 • NO 0 • NOT VOTING 0 • ABSENT 2
Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 3

his chapter examines some of the issues that will arise 

as CMS implements the Medicare drug benefit. We 

examine performance measures, premium variation,

outreach and enrollment, and beneficiary grievance and

appeals protections. Building on the work of other purchasers, CMS

must determine how to measure the performance of plan sponsors and

the overall drug benefit. Part D enrollees will face different premiums

across the nation. Medicare will provide the same subsidy to plans on 

behalf of each enrollee, and enrollees will pay more if their plan’s benefit spending is higher. Plans may be able to reduce geographic variation

in premiums by managing enrollees’ use of drugs. Nevertheless, higher

premiums might lead to lower enrollment in some parts of the country.

CMS will auto-enroll beneficiaries dually eligible for Medicare and

Medicaid in Part D, but the agency may find it difficult to reach and enroll other low-income individuals.

1

In this chapter

• Description of the 

Part D benefit

• Performance measures for 

evaluating Part D 

implementation

• Paying plans, setting 

premiums, and enrollment 

in Part D

• The Medicare discount 

drug card and beneficiary 

outreach for Part D 

• Formulary exceptions and 

the appeals processes

• Looking forward: 

Electronic prescribing 

and other areas of 

future research 

CHAPTER

T

Monitoring the

implementation of Part D
On January 1, 2006, Medicare will begin a voluntary

outpatient drug benefit known as Part D. A combination of

stand-alone prescription drug plans (PDPs) and Medicare

Advantage (MA)–Prescription Drug plans (MA–PDs) will

deliver the benefit. In each of 34 geographic regions, 

plans will compete for enrollees on the basis of annual

premiums, benefit structures, degree of access to specific

drug therapies, and quality of services. Plans will bear

some risk for their enrollees’ drug spending. In order 

to encourage Medicare beneficiaries to enroll, the

government will subsidize premiums by nearly 

75 percent and will provide additional subsidies 

for beneficiaries who have low incomes and assets. 

In this chapter, we describe issues related to CMS’s

implementation of the Medicare Part D benefit and discuss

strategies for monitoring and evaluating this new benefit

in the future. Because the policy goals of appropriate

access, high quality, and reasonable cost sometimes

compete with one another, Medicare must strike a 

balance among them. 

Our research on drug benefit implementation issues

suggests the following key findings:

• In the commercial market, purchasers rank cost as a

top priority in evaluating the performance of their

plan’s drug benefit management. To evaluate drug

benefit quality, purchasers use measures that track

enrollees’ access to pharmacies, needed drugs, and

safe utilization. Purchasers also review measures on

member satisfaction and on benefit administration,

such as claims processing accuracy. For Part D, CMS

intends to construct and use performance measures,

but it has not yet selected or announced them for

either short- or long-term analysis.

• CMS will be collecting a large amount of data on Part

D, including drug use and plan benefit information.

Congressional agencies will need Part D data to 

report to the Congress about the impact of Medicare

payment policies on cost, quality, and access. 

• Premiums for Part D will, in percentage terms, vary

more across geographic regions than per capita drug

spending due to the method of calculating enrollee

premiums required by the Medicare Prescription

Drug, Improvement, and Modernization Act of 2003

(MMA). Plans may be able to reduce today’s

geographic variation in spending, somewhat, by

managing enrollees’ use of prescription drugs.

Nevertheless, higher Part D premiums might lead to

lower enrollment in some parts of the country. 

• Because CMS will automatically enroll beneficiaries

who are dually eligible for Medicare and Medicaid,

these individuals could represent a disproportionate

share of early enrollees in Part D plans. The share of

dual eligibles varies considerably among each region’s

Medicare population. An open question remains: 

How will differences in the proportion of each

region’s Medicare population that CMS auto-enrolls

affect geographic variation in Part D premiums?

• In the case of the Medicare discount drug card, CMS

and other state agencies experienced difficulty in

targeting outreach strategies to beneficiaries who are

disabled, low income, less educated, or living in longterm care facilities. Auto-enrollment proved far more

effective than voluntary enrollment and accounted for

a larger share of the overall enrollment in the discount

card program. 

• Health plans and pharmacy benefit managers (PBMs)

have well-established processes that involve the use 

of prior authorization and other techniques to manage

drug utilization. Most plan members do not appeal

denied formulary exceptions. Physicians frequently

decide, when told of the prescribed drug’s

nonformulary status, that the formulary drug is

acceptable. When physicians pursue requests, plans

report very high approval levels. However, given 

the increased level of drug utilization likely to occur 

in 2006, the volume of appeals may increase.

• Beneficiaries who are dually eligible for Medicare 

and Medicaid will have fewer appeal rights under 

Part D than they currently have under Medicaid. 

For example, Medicaid programs must continue to

provide ongoing drug treatment to beneficiaries 

while an appeal is underway. Part D plans will not

face this requirement, and beneficiaries may be

unfamiliar with new processes for appealing

formulary decisions. When dual eligibles begin

receiving their drug benefit from Part D plans, some

of these individuals may be taking drugs that are 

not on their plans’ formulary. Plans must develop

transition policies that are adequate to ensure that

beneficiaries continue to receive medications and 

do not delay or stop treatment because they face

unfamiliar formulary exceptions processes.

4 Monitoring the imp lementation of Part D
Description of the Part D benefit

The MMA defines a standard drug benefit under Part D

and describes the conditions under which private plans

may offer alternative benefit designs. In 2006, the standard

benefit will include: 

• a $250 deductible; 

• coverage for 75 percent of allowable drug expenses up

to a benefit limit of $2,250; 

• a $3,600 catastrophic limit on true out-of-pocket

spending1 (or $5,100 in total drug expenses for

enrollees without supplemental drug coverage); and

• about 5 percent coinsurance for drug spending above

the catastrophic limit (Figure 1-1).2

Enrollees with standard benefits will pay 100 percent

coinsurance for drug spending greater than $2,250 but less

than their catastrophic threshold. However, beneficiaries

will be able to obtain their plan’s discounted price for

prescription drugs for drug spending in this coverage gap.

They would also need to adhere to their plan’s formulary,

prior authorization, and formulary exceptions processes in

order to receive credit for their out-of-pocket spending

toward the $3,600 catastrophic limit. 

Although the MMA explicitly lays out the structure of this

standard Part D benefit, the law also permits plans to offer

alternative coverage. For example, a plan could use tiered

copayments rather than coinsurance, provided that cost

sharing averages 25 percent of allowable drug spending

above the deductible and below the benefit limit. The law

permits other variations from the standard benefit—such

as having a deductible lower than $250—provided that 

the alternative benefit meets certain tests of actuarial

equivalence. CMS expects that enrollee premiums for

these basic benefits will average $37 per month in 2006,

but each plan’s specific premium could vary. 

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 5

Standard drug benefit in 2006

FIGURE

1-1

5%* Catastrophic

coverage

No

coverage

Deductible

Premium

Partial coverage

up to limit 25%

Note: Benefit structure applies for an enrollee who has no supplementary drug coverage. 

 * Cost sharing above the catastrophic cap is the greater of either 5 percent coinsurance or a copay of $2 for generic drugs, or $5 for brand-name drugs.

 **Equivalent to $3,600 in out-of-pocket spending: $250 (deductible) + $500 (25% cost sharing on $2,000) + $2,850 (100% cost sharing in the “coverage gap”).

Source: MedPAC analysis. 

Out-of-pocket spending Medicare Part D benefit

Approximately $444 per year

$2,850 coverage gap

$5,100**

$2,250

$250
The law provides additional subsidies for low-income

beneficiaries. Medicare will begin providing primary 

drug coverage for individuals who are dually eligible for

Medicare and Medicaid. Dually eligible individuals who

earn incomes up to 100 percent of poverty will have no

deductibles and nominal copays. CMS will randomly

assign them to drug plans if they do not choose a plan by

January 1, 2006, and these beneficiaries will be able to

change plans at any time. Low-income beneficiaries who

do not qualify for Medicaid may also receive subsidies:

Individuals who earn incomes below 150 percent of

poverty and who meet an asset test will receive full or

partial coverage for premiums and cost-sharing and will

not face a coverage gap (Table 1-1). 

Medicare beneficiaries will likely see a variety of benefit

designs available in the market. MA–PDs may offer

broader coverage than the basic benefit (for example, 

by filling in the coverage gap) without charging an

additional premium.3 If a PDP or MA–PD meets the

requirement of offering basic Part D coverage, it may 

also offer supplemental coverage for an additional

unsubsidized premium. Even two competing plans—both

offering the standard benefit—may appear somewhat

different from one another because they can include

different mixes of preferred and nonpreferred drugs on

their formularies. 

Performance measures for evaluating

Part D implementation

Policymakers will need to monitor the implementation 

of the new Medicare drug benefit to evaluate plan

performance and to measure how well Part D meets cost,

quality, and access objectives for pharmaceutical care.

Employers and government agencies use performance

measures to evaluate how well health plans and PBMs

manage the drug benefits they purchase. 

MedPAC staff convened a panel of experts to discuss

performance measures and to identify ways in which

policymakers could use measures to monitor the Part D

program over time and evaluate participating plans’

performance. Under contract, Georgetown University

researchers organized the panel and facilitated the

meeting’s full-day discussion. The panelists represented

health plans, PBMs, employers, pharmacies, consumers,

quality assurance organizations, and researchers.

The panelists were unable to reach a consensus on a

specific set of performance measures that should be used

for Part D plans, or even for drug benefits in the

commercial market. However, they did discuss several

areas of performance that purchasers (e.g., employers)

consider when selecting and monitoring the health plan 

or PBM that manages their drug benefits. These areas 

of performance measures were: 

• cost control,

• access to needed medications and quality assurance,

• benefit administration and management, and

• enrollee satisfaction.

Table 1-2 lists these areas of performance and, for

illustrative purposes, provides an example of a measure 

in each area. Purchasers use many additional (and often

more detailed) measures to assess health plan or PBM

performance in managing drug benefits. Also, as we

6 Monitoring the imp lementation of Part D

Out-of-pocket spending under the low-income drug benefit, 2006 

Beneficiary income Premium Deductible Copayments* Coverage gap

Dual eligibles, up to100% FPL none none $1–3 none

Other dual eligibles and others, 100–135% FPL none none $2–5 none

135–150% FPL sliding scale $50 15% of drug cost none

Note: FPL (federal poverty level). Low-income beneficiaries must meet an asset test to qualify for low-income subsidies. In 2006, assets must be no greater than $10,000 

for an individual or $20,000 for a couple.

*Plans may not charge copayments to dual eligibles who live in long-term care facilities.

Source: CMS 2005g.

TABLE

1-1
discuss later in this chapter, results from these measures

can be interpreted in different ways, depending on other

plan variables. 

Under Part D regulations, CMS will collect data that 

CMS and other policymakers could use for performance

measurement in most of these areas. For example, CMS

will have information on beneficiaries’ drug utilization

and spending, plans’ pharmacy network breadth, claims

processing accuracy, and beneficiary satisfaction rates. 

In addition, CMS will have medical claims data for 

risk adjusting many of these measures. In its Part D

regulations, CMS states that it will develop plan

performance measures for the drug benefit, but the 

agency has not yet selected these measures or 

determined how they will be used. 

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 7

Examples of performance measures purchasers 

use to evaluate drug benefit management 

Measurement areas Examples

Cost control

Plans’ drug spending Average drug spending per member per month (risk-adjusted)

Out-of-pocket drug spending Average annual out-of-pocket spending on covered drugs (risk-adjusted)

Pharmacy discounts on drugs Average rate of discount on brand and generic drugs

Pharmacy dispensing fees Dispensing fees for brand and generic drugs

Manufacturer rebates Total aggregated rebates as a percentage of total drug spending, annually

Drug utilization Average number of prescriptions per member per year, by therapeutic category

Generic use Ratio of generic drugs to total drugs that have an available generic

Formulary adherence Ratio of preferred to nonpreferred brand-name drugs covered

Access and quality assurance

Pharmacy network Ratio of preferred network pharmacies to all pharmacies in service area

Enrollee refill adherence Percentage of members who refill chronic medications

Formulary review process Average time P&T committee takes for initial review of new drug

Prior authorization and nonformulary exceptions Average time for plan decision on prior authorization request

Appeals process and rates Percentage of appeals that are overturned

Point-of-sale electronic messaging to pharmacists Frequency of updates to clinical safety messaging software

Utilization of drugs contraindicated for the elderly Percentage of drugs contraindicated for the elderly on prior authorization

Adverse drug interactions, events Number of adverse drug interactions and/or adverse drug events per 1,000 members

Drug utilization review Presence of screening to identify drugs filled beyond maximum therapeutic duration

Electronic prescribing use Percentage of prescriptions submitted through e-prescribing per year

Benefit administration and management

Claims processing Percentage of claims processed accurately per year

Eligibility determination Percentage of claims processed for ineligible individuals per year

Data management for coordination of benefits Accuracy of benefit-spending calculations

Enrollee satisfaction

Enrollee survey results Member satisfaction rates

Call-center availability Hours per day that the call center is open

Call-center response times Abandonment rates (percentage of time caller hangs up while on hold)

Grievance reporting Average number of complaints reported per 100 members per year

Plan retention and disenrollment Percentage of enrollees who voluntarily disenrolled

Note: P&T (pharmacy and therapeutics). The measures included in the second column are examples meant for illustrative purposes. Drug benefit purchasers (e.g., 

employers) may use many other more detailed measures to assess health plan or pharmacy benefit manager (PBM) performance. In some cases, results from these 

measures can be interpreted differently, depending on other plan variables.

Source: MedPAC analysis.

TABLE

1-2
Considering the complexity of implementing a drug

benefit of this size, policymakers may expect some initial

challenges and difficulties that likely will be resolved 

over time. Therefore, both short- and long-term analyses

of Part D will be important. Indeed, evaluation at the start

of the benefit can help identify the most useful measures

to implement in the coming years. Once appropriate

measures are selected and constructed, CMS could 

release some publicly, use some to determine financial

awards in a pay-for-performance model, or factor some

into future plan contracting decisions. Ultimately, CMS

may use performance measures across the entire enrolled

population to evaluate the drug benefit’s implementation

and make operational adjustments, where needed.

Cost control

Most panelists agreed that purchasers rank cost as a top

priority in evaluating the performance of their health

plan’s or PBM’s drug benefit management. In general,

PBMs and health plans control drug benefit costs 

by negotiating with pharmacies and pharmaceutical

manufacturers and by managing members’ drug

utilization. Although purchasers can track overall drug

spending totals, their ability to evaluate plan performance

on specific cost-control activities—such as formulary

design—varies. 

Negotiations with pharmacies and

pharmaceutical manufacturers

PBMs and health plans establish retail pharmacy networks

with which they negotiate discounts on prices for brandname and generic drugs. Plans and PBMs also include

negotiated dispensing fees in their pharmacy contracts;

these fees can include incentives for substituting generic

for brand-name drugs, when available (Mercer 2003b).

Plans and PBMs provide purchasers with information on

their negotiated dispensing fees. Similarly, CMS will

require Part D plans to submit dispensing fee data. 

This information might serve as an indicator to CMS 

of how well plans negotiate with their pharmacy 

network to lower costs. 

Some expert panelists noted that because generic

substitution is an effective cost-control tool, purchasers

commonly examine plans’ generic dispensing rates—

the number of covered generics as a percentage of total

covered drugs or as a percentage of total covered drugs 

for which generics are available. CMS will collect generic

dispensing rate data by plan and could use this information

as one measure of plans’ ability to control costs. CMS will

also have drug claims data to allow calculation of generic

dispensing rates for the Medicare population.

In addition to contracts with pharmacies, the majority 

of PBMs and health plans that provide pharmacy 

benefit services establish contractual relationships with

pharmaceutical manufacturers to receive rebates. These

rebates are typically based on target volumes of drug 

sales. Plans and PBMs provide purchasers with some

information to show how much purchasers gain through

rebates. For example, measures may show total dollars

saved or the negotiated percent discount off the published

average wholesale price. Panelists agreed that PBMs 

and health plans may share some portion of their rebate

revenues with purchasers but do not always clearly

disclose actual numbers. Several panelists commented 

that purchasers devote considerable resources verifying

reported rebates, but they find this task difficult because

PBMs generally consider the data to be proprietary. 

Under Part D, Medicare will require plans to report

aggregate rebates confidentially in order to estimate

transaction prices. Plans will apportion a share of their

total rebates to Part D utilization and report that amount.

Previous lapses in government oversight of Medicaid drug

pricing and manufacturer rebates highlight the challenge

that Medicare will face in reviewing and auditing rebate

information (GAO 2005). A few panelists suggested 

that CMS will need to monitor fraud and abuse and 

assert its right to audit participating plans. They noted

previous legal actions filed against PBMs regarding

misrepresentation of their cost-saving methods 

and objectives.

Drug utilization management

A plan’s drug spending reflects the type and amount of

drugs that members take. Drug utilization measures focus

on both aspects. The National Committee for Quality

Assurance (NCQA) has developed a few performance

measures on drug utilization that employers can use when

evaluating health plan performance. For example, NCQA

collects data on plans’ total prescription drug costs, the

average cost of prescriptions per member per month, the

total number of prescriptions, and the average number of

prescriptions per member per year (NCQA 2005). Under

Part D, CMS will collect data on some of these same

measures. In combination with health claims data, these

metrics will allow CMS to calculate risk-adjusted

8 Monitoring the imp lementation of Part D
spending and utilization trends for Part D to determine

how well the drug benefit controls costs over time. These

measures will also allow for some general drug-spending

comparisons among Part D plan sponsors. 

Much of the panel discussion on cost control focused on

the broad set of activities that health plans and PBMs use

to manage the drugs that members take. Among other

goals (such as safety), these activities can steer enrollees

toward specific drugs that the plans and PBMs determine

are the most clinically appropriate and cost effective. For

example, formulary design features—including drug lists,

tiered cost sharing, step therapy, and prior authorization

policies—can influence members’ drug utilization. The

MMA states that Part D plans are expected to use a variety

of drug utilization management activities, some of which

they currently employ with their commercial clients.

Health plans and PBMs commonly use drug utilization

review (DUR) to manage the costs associated with

enrollees’ drug utilization. Such DUR activities may

include screening for overutilization of drugs. These

screens can help plans and PBMs achieve cost savings (in

addition to improving safety) by automatically reviewing

instances in which enrollees refill prescriptions beyond

their maximum therapeutic timeframe.

Several panel experts suggested performance measures

that assess the impact of utilization activities. For

example, formulary compliance measures examine rates 

at which members take preferred over nonpreferred brandname drugs. Physician prescribing and patient preferences

strongly influence these rates, but health plans and PBMs

have several tools to educate physicians and members on

the rationale for distinguishing drugs by preferred and

nonpreferred tiers. Generic dispensing rates also provide 

a measure of drug utilization management. Experts in 

our panel emphasized that physicians have considerably

more impact on members’ drug choices than do plans’

utilization management activities. Health plans,

particularly those in group staff models, typically

communicate more with their prescribing physicians 

and thus may have more opportunities to influence

prescribing patterns than do independent PBMs. 

Out-of-pocket spending

Many group health purchasers also monitor enrollees’ outof-pocket spending as it affects enrollee (employee)

satisfaction. In general, plans’ success at lowering some

drug prices will reduce their members’ out-of-pocket

spending on those drugs. However, depending on enrollee

utilization, some drug utilization tools—such as tiered cost

sharing—that lower purchaser costs may raise enrollee

out-of-pocket costs. In their reports to purchasers, PBMs

and health plans often separate out-of-pocket spending

from the benefit’s covered spending.4

Some experts on the panel stated that beneficiaries are

extremely interested in how Part D will affect their 

out-of-pocket spending, including premium payments.

Participating plans will submit data to CMS that will

enable the agency to compute beneficiaries’ average outof-pocket spending on covered drugs. These calculations

will be essential for policymakers’ evaluation of Part D

over time. CMS could also calculate and monitor average,

risk-adjusted, out-of-pocket spending by plan. When

making enrollment decisions, this kind of information

might help beneficiaries determine which plans can give

them the best value.

Access and quality assurance

The Congress established Part D to improve Medicare

beneficiaries’ access to needed medications, and included

provisions in the program to encourage safe utilization.

Panelists described a variety of measures that drug benefit

purchasers use to evaluate enrollee access to medications,

and whether the covered medications they take are

appropriate and safe. Because pharmaceuticals are so

central to effective medical treatment, some purchasers

also may consider access to prescription drugs a measure

of plan or PBM quality. Under Part D, plans will have

financial incentives to control costs, highlighting the need

for access and quality measures. CMS will be collecting

some relevant data that can be used to develop access 

and quality measures for plans and—for the Medicare

drug benefit, overall.

Pharmacy access

Some panelists noted that pharmacy access is a major

factor in plan and PBM selection—both for group health

plan purchasers and for individuals who are purchasing

their own drug coverage. Measures of pharmacy access

evaluate members’ ability to obtain their medications

conveniently. When making contracting decisions,

purchasers often request detailed reports on the locations

of the pharmacies in health plan and PBM networks. 

For example, employers may compare employee zip 

codes to the locations of plans’ pharmacies.

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 9
Under Part D, Medicare requires a minimum level of

pharmacy access based on standards set for the TRICARE

program—the program that insures members of the U.S.

military and their dependents. This standard specifies

maximum average distances to plans’ network pharmacies

within a state, based on the type of geographic area (rural,

urban, or suburban). In general, these minimum pharmacy

access standards are adequate for most beneficiaries, but

some beneficiaries who live in rural areas may have to

travel more than 15 miles to reach a network pharmacy.

Some panelists stated that Part D plans with broad

pharmacy networks will likely attract more consumers

because beneficiaries tend to focus heavily on the

convenience of a plan’s pharmacy network when 

selecting a plan. 

Although plans may have many pharmacies in their

network, and minimum access standards exist, 

Medicare may still need to monitor beneficiary access 

to pharmacies. In particular, plans can distinguish 

between preferred and nonpreferred pharmacies in their

overall networks by offering lower cost sharing for

preferred pharmacies. In such circumstances, access 

to preferred pharmacies may not meet TRICARE

standards in some areas. To identify access problems 

(if they exist), CMS could examine beneficiary distances

to preferred and nonpreferred pharmacies by zip code. 

Access to needed medications

To ensure that drug utilization management programs do

not prevent enrollees from obtaining needed medications,

purchasers can examine measures that show enrollees’

access to drugs. For example, purchasers may examine the

number of drugs plans list on their formulary. However,

several panelists cautioned that formulary designs do not

directly reveal drug access. In practice, enrollees may have

either greater or lesser access to drugs than a formulary’s

drug list suggests—that is, plans can cover drugs that are

off the formulary and, alternatively, can require prior

authorization for drugs that are on the formulary. 

The panelists considered other performance measures 

that could reflect access, but many again noted that the

data might be ambiguous. For example, the ratio of

formulary to nonformulary drugs covered might be a

useful measure, but it is difficult to interpret. A high 

share of nonformulary use could indicate that the plan

employs a flexible exceptions process to ensure that

members get the drugs they need. Alternatively, this high

share could indicate that the formulary is out of date or

that physicians do not find it acceptable. A low exception

ratio may mean that physicians consider the plan’s process

for granting a nonformulary exception too onerous—or,

alternatively, that the formulary is relatively unrestrictive

and well-accepted by physicians. A plan’s rate of

overturned appeals has similar caveats.

Panelists discussed some approaches that Medicare could

use to measure access to medications under Part D. Some

panelists suggested that CMS evaluate exception rates

within selected therapeutic categories. This measure could

show whether beneficiaries can obtain necessary drugs 

for a given condition. Others suggested access measures

on the frequency of claim denials at the point of sale, and

whether enrollees later obtained an alternative drug or got

their plan to cover the drug through a prior authorization

or formulary exception.

Some purchasers use other access measures to examine

member adherence to treatment regimens, particularly for

chronic conditions (Berman 2005). CMS could use claims

data to calculate the average number of times per year that

members refill their monthly prescriptions, by therapeutic

class. By carefully analyzing beneficiary access to

medications by therapeutic category, CMS could also

examine how differences in variables, such as formulary

design and cost sharing associate with differences in

adherence rates.

Part D addresses access concerns for people who have

expensive, chronic conditions by prohibiting plans from

excluding from their formulary whole classes of drugs

used to treat expensive conditions, such as AIDS. 

CMS will require Part D sponsors to submit for review

formularies and other drug management utilization

programs, such as step therapy rules that encourage the

use of low-cost medications before covering high-cost

medications for a given medical condition. During the

bidding process, CMS intends to review plans’ drug

utilization management requirements to ensure that

beneficiaries receive appropriate and timely access 

to medically necessary drugs. CMS’s review of drug

utilization programs, including formularies, is consistent

with that of group health purchasers; these purchasers

require their contracted PBM or health plan to demonstrate

their formulary’s cost effectiveness and clinical

appropriateness, thus ensuring that members can obtain

the drugs they need (Mercer 2003b). 

10 Monitoring the imp lementation of Part D
Quality assurance

By facilitating access to appropriate medications, health

plans and PBMs go a long way toward ensuring health

care quality. Many purchasers also look at measures that

evaluate the safety and appropriateness of medication

dispensing and prescribing. Integrated health plans are

usually accredited and have built-in incentives to manage

their drug benefits to avoid medical complications. Part D

regulations require plans to develop and submit an

explanation of their own quality assurance systems, but

these regulations do not require specific quality assurance

performance measures.

The need for quality assurance measures and systems to

reduce medication errors and adverse drug interactions is

well documented for the elderly population (Booz Allen

Hamilton 2004, Goulding 2004, Fick et al. 2003, Beers

1997). However, peer-reviewed literature does not 

reach consensus on methods for determining which 

drugs are appropriate for the elderly, and under which

circumstances. NCQA has recently proposed some

prescription drug measures to examine safe drug

utilization in its health plan accreditation process (see 

text box, p. 12). One of its proposed measures assesses

how well health plans reduce their elderly members’ use

of drugs that are contraindicated for elderly people. CMS

will have the data needed to implement this kind of quality

assurance measure. With its medical and drug claims 

data, CMS also could begin to examine the frequency 

of emergency room visits due to adverse drug events and

drug-to-drug interactions, depending on the adequacy of

claims’ diagnosis information.

A common tool that health plans and PBMs use for 

quality assurance is point-of-sale electronic messaging to

alert pharmacists about safety concerns before dispensing

particular drugs. Claims processing systems typically

screen for potential drug interactions, overuse, incorrect

dosage, allergy contraindications, and clinical abuse or

misuse. Performance measures, therefore, often examine

whether plans employ these types of alerts, whether 

the alerts are up to date with best clinical practice, and

whether pharmacists find the messages clear and easy 

to understand. 

Some panelists indicated that pharmacists receive a large

number of messages and alerts. This barrage of messages

may lead some pharmacists to ignore many alerts in 

order to fill prescriptions in a timely manner. One recent

report to CMS noted that too many redundant messages

and outdated warnings may cause pharmacists to disable

electronic messaging features or routinely override

messages (Booz Allen Hamilton 2004). The Academy 

of Managed Care Pharmacy (AMCP) has published

guiding principles on electronic messaging systems. 

One principle suggests that plans and PBMs revise their

claims processing systems to eliminate the number of

redundant messages that pharmacists receive per claim,

such as the following two similar messages: “drug not

covered for females” and “drug not covered for patient

gender.” By eliminating such redundancies, plans and

PBMs could improve pharmacists’ ability to focus on

important clinical safety alerts. 

The expert panelists agreed that physician prescribing

remains the most important and influential component of

quality assurance in drug utilization. Accordingly, health

plans and PBMs are exploring ways to educate physicians

at the moment in which they prescribe medication

therapies. Electronic prescribing (e-prescribing)

technology can help physicians make safe prescribing

decisions, prescribe formulary medications, and reduce

errors due to illegible handwriting. We discuss 

e-prescribing further on page 33.

Health plans typically focus more broadly on quality

assurance than PBMs because they provide an integrated

benefit package and seek accreditation. Health plans 

have a greater opportunity to integrate measures of

pharmaceutical quality with broader measures of quality

of care. A number of organizations measure and evaluate

health plans’ quality assurance programs for accreditation

purposes. Because PBMs usually are not independently

accredited, they do not necessarily evaluate their

performance on the same specific measures, but 

PBMs may adopt practices that are consistent with 

the accreditation standards required of their client health

plans (Booz Allen Hamilton 2004).5 Also, health plans 

are typically at risk if prescription drug utilization or

underutilization results in medical complications; thus,

health plans have built-in incentives to monitor and

improve the safety of members’ prescription drug

utilization. PBMs are not usually at risk for medical

costs—such as hospitalizations—that are associated with

underutilization of needed medications or unsafe drug

utilization. Additionally, PBMs that are not integrated

within a health plan or insurer do not typically collect data

on their enrollees’ health status and health care utilization.

To encourage plans to connect health outcomes with

prescription drug use, the MMA requires that all Part D

plans offer a medication therapy management program

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 11
(MTMP) to targeted beneficiaries—namely, those who

have multiple chronic conditions, are taking multiple

medications, or have high expected drug expenses. MMA

introduced the MTMP to improve therapeutic outcomes

through activities such as pharmacist consultations. 

These consultations could include a review of member

beneficiaries’ full drug regimens to detect the potential 

for adverse drug interaction as well as patterns of

prescription drug overuse and underuse. In the early stages

of the Medicare drug benefit, CMS will allow plans to

determine the methods and types of providers they will

use to implement MTMP services. CMS is delaying the

collection of performance measures for these programs but

will require plans to report some operational data, such as

the numbers of eligible and participating beneficiaries.

Considering that the MMA expects MTMPs to improve

12 Monitoring the imp lementation of Part D

Current and proposed drug utilization and quality measures in HEDIS 

The Health Plan Employer Data and Information

Set (HEDIS) is a set of standardized performance

measures designed to allow purchasers and

consumers to compare managed care organizations 

on the basis of quality. HEDIS is a model for emerging

systems of performance measurement in other areas of

health care delivery. The National Committee for Quality

Assurance (NCQA), a not-for-profit organization that

evaluates and publicly reports on the quality of managed

care organizations, maintains HEDIS.

In 2006, health plans will report on more than 60 HEDIS

performance measures, including measures that assess

appropriate medication treatment for patients with

asthma, depression, heart attack, and other conditions.

Below are some of NCQA’s current and proposed

HEDIS measures that relate specifically to 

prescription drugs:

• Outpatient drug utilization. This current

measure summarizes data on outpatient utilization

of prescription drugs. It includes the total cost 

of prescriptions, the average cost of prescriptions

per member per month, the total number of

prescriptions, and the average number of

prescriptions per member per year. 

• Antibiotic utilizations. For 2006, NCQA proposes

to look also at possible overutilization of selected

antibiotics known to contribute to antibiotic drug

resistance compared with overall antibiotic use. 

The measure provides information on outpatient

antibiotic use by drug class, including total and

average number of antibiotics per member per 

year and average days per antibiotic prescription.

• Pharmacotherapy management of chronic

obstructive pulmonary disease (COPD)

exacerbations. This proposed measure assesses

whether members who were discharged home

following a COPD exacerbation episode treated 

in the emergency department or in an inpatient

hospital setting received systemic corticosteroids

within 7 days and/or bronchodilators within 

21 days. 

• Drugs to be avoided in the elderly. Among

health plan enrollees age 65 and older and in

Medicare, proposed HEDIS measures include two

rates: (1) the percentage who received at least one

prescription for a drug to be avoided in the elderly,

and (2) the percentage who received prescriptions

for at least two different drugs to be avoided in 

the elderly. The first rate assesses the extent to

which elderly patients have had some exposure to

potentially harmful drugs. The second rate further

assesses if elderly patients have been exposed to

multiple harmful drugs. NCQA identifies drugs 

to be avoided in the elderly population based on

clinical journal publications and clinical consensus. 

• Annual monitoring of patients on persistent

medications. This proposed patient safety

measure would assess whether adults taking

medications for chronic conditions are receiving

timely monitoring to prevent potential problems

associated with persistent use of these drugs,

including drug toxicity, electrolyte imbalances,

renal failure, and liver damage. therapeutic outcomes, performance measures that assess

reductions in adverse health events due to drug-to-drug

interactions may be an important future measure.

Benefit administration and management 

Purchasers rely on health plans and PBMs for

administrative functions such as processing prescription

drug claims, managing drug identification cards, and

adjudicating primary and secondary payer information.

The expert panelists stated that performance measures 

for these tasks are relatively common, and CMS could

monitor them under Part D.

Generally speaking, PBMs and health plans are able to

process most drug claims almost instantaneously through

electronic communication links with their network

pharmacies, but delays and errors can occur. Many

purchasers routinely look at the accuracy of their PBM’s

eligibility determinations, dispensing fee payments, and

cost-sharing charges (Mercer 2003b). Many panelists

noted that if CMS monitored these administrative tasks 

at the beginning of Part D implementation, beneficiaries

may experience smoother enrollment into the Medicare

drug benefit.

Under Part D, plans will need to provide pharmacies 

with drug price information so that they can calculate

beneficiary cost sharing at the point of sale. Additionally,

plans must provide monthly statements to beneficiaries

explaining their year-to-date drug spending, if any. CMS

will contract with a single company that will provide Part

D plans and CMS with electronic information regarding

other payers (e.g., employer-sponsored supplemental 

plans that wrap around the Medicare plan).6 Plans will 

use this information to track members’ out-of-pocket

spending for covered drugs. CMS could implement

performance measures on the accuracy of cost-sharing

charges to ensure that beneficiaries are paying the 

correct amounts for their medications. 

Enrollee satisfaction

Health plans and PBMs commonly measure member

satisfaction rates and offer relevant performance

guarantees to their clients. In addition to survey 

results, purchasers can also examine plans’ call-center

performance and disenrollment rates to evaluate member

satisfaction. Panelists noted that both CMS and Part D

plans could conduct some of these activities. 

Satisfaction surveys

Health plans and PBMs routinely provide their current 

and potential clients with results of enrollee satisfaction

surveys (Mercer 2003b). Purchasers typically determine

their own target threshold for enrollee satisfaction,

recognizing that they may not be able to compare rates

between plans that use different survey instruments.

However, purchasers can track enrollee satisfaction over

time when the plan or PBM presents the purchasers with

periodic survey results. 

Under Part D regulations, CMS will conduct consumer

satisfaction surveys of Part D enrollees and provide the

results to beneficiaries as they are making enrollment

decisions. CMS is reviewing possible survey instruments

and anticipates working with the Agency for Healthcare

Research and Quality (AHRQ) to develop a survey that

measures beneficiaries’ experience with their prescription

drug coverage.7 Using this survey, CMS can obtain

consumer satisfaction rates directly from beneficiaries. 

Call center operations 

Many panelists stated that the performance of plans’ and

PBMs’ customer-service call centers plays an important

role in influencing enrollee satisfaction. Purchasers

commonly examine the length of time that callers wait 

on hold, as well as abandonment rates (the share of calls 

in which the caller hangs up while waiting on hold to talk

with a service representative). Under Part D, CMS could

collect the same performance measures that it currently

collects for the discount drug card program—namely,

hours of operation and call-center response times. Some

panelists also suggested that CMS collect data on call

centers’ ability to serve non-English speakers.

Retention and disenrollment rates

By examining the extent to which members voluntarily

stay in or disenroll from plans, CMS will have additional

indicators of consumer satisfaction. Under Part D,

beneficiaries will be able to switch plans once during 

the year, and more frequently if they are eligible for

Medicaid or if they reside in long-term care facilities.8

In general, plans with high retention rates are likely to

show higher consumer satisfaction than plans with 

lower retention rates. In addition, Medicare can use 

this information to track beneficiary satisfaction with 

the Part D benefit, as a whole. 

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 13
Data needs

As noted above, CMS will be collecting a large amount of

data on Part D, including drug utilization and plan benefit

information. In addition to claims and spending data, Part

D sponsors must submit data on pharmacy discounts,

aggregate pharmaceutical manufacturer rebates, generic

dispensing rates, formulary design, prior authorizations,

nonformulary exceptions, appeals, coordination of benefits

for out-of-pocket determination, call-center operations,

grievances, and enrollment/disenrollment. CMS will also

collect satisfaction survey data from beneficiaries and

additional health claims data from other providers.

Therefore, CMS will have a rich and comprehensive set 

of data for Part D analysis. Indeed, CMS will have more

robust information on Part D than it collects on Part C—

the Medicare Advantage program.

CMS has stated that it intends to construct and use

performance measures to monitor the Part D benefit. 

At this time, CMS has not yet selected these measures 

or determined how they will be used. In the long term,

these uses could include (but are not limited to) releasing

some measures publicly, using some measures to

determine financial awards in a pay-for-performance

model, or factoring some measures into future plan

contracting decisions. In addition to using measures to

assess plan performance, CMS could also use them to

assess how well the overall benefit is meeting its

objectives for the beneficiary population and could 

design operational changes accordingly.

At the start of the benefit, plans are likely to encounter

several logistical challenges. Therefore, analysis of 

plan performance in the initial year should take these

difficulties into consideration. Data analysis of the early

stages of Part D will be essential to help policymakers

identify and shape important and useful performance

measures for the program over time.

In addition to CMS, congressional support agencies are

charged with reporting to the Congress about the impact 

of Medicare payment policies on cost, quality, and access.

Data on Part D are necessary for analyzing program

performance and making policy recommendations.

Therefore, CMS will need to develop a process for the

timely dissemination of Part D data to congressional

support agencies.

RECOMMENDATION

The Secretary should have a process in place for timely

delivery of Part D data to congressional support

agencies to enable them to report to the Congress on

the drug benefit’s impact on cost, quality, and access.

RATIONALE

Congressional agencies need these data to monitor and

evaluate the new Part D benefit in the initial stages of the

program and over the long term.

IMPLICATIONS

Spending

• This recommendation would not increase federal

program spending.

Beneficiary and provider

• This recommendation would have no direct impact on

beneficiaries. It also would not affect provider cost or

administrative burden because it does not require

submission of additional data.

Paying plans, setting premiums, and

enrollment in Part D

A number of private organizations have announced that

beginning next year, they intend to offer PDPs nationwide,

offer them in several PDP regions, or offer MA–PDs.9

Although plan entry constitutes an important half of the

equation in establishing Part D, uncertainty remains about

how many Medicare beneficiaries will choose to enroll.

Beneficiaries’ decisions about whether to sign up for a

Part D plan will depend, in part, on what premiums 

they must pay.

In this section, we review how CMS will pay Part D plans,

how it will set enrollee premiums, and why premiums may

vary across geographic regions. We discuss the following:

• Under Part D, enrollee premiums are likely to differ

around the country. One implication of Part D’s

premium-setting approach is that beneficiaries 

who live in parts of the country with higher use of

prescription drugs could face higher premiums than

people who live in areas with lower use. Plans may be

able to reduce this geographic variation by managing

enrollees’ use of prescription drugs. Nevertheless,

14 Monitoring the imp lementation of Part D
higher Part D premiums might lead to lower

enrollment in some parts of the country.

• Because CMS will auto-enroll beneficiaries who are

dually eligible for Medicare and Medicaid, these

individuals could represent a disproportionate share

of early enrollees in Part D plans. The share of dual

eligibles varies between 9 percent and 29 percent of

each region’s Medicare population. An open question

remains: How will differences in the proportion of

dual eligibles in each region’s population affect

geographic variation in Part D premiums?

Prescription drug plan regions

In late 2004, CMS announced its decision to establish 34

separate PDP regions, or groupings of states (Figure 1-2).

Stand-alone drug plans must offer the same benefit and

charge the same premium to all Medicare beneficiaries

who enroll within a given PDP region.10 A single legal

entity may offer PDPs in several or all regions; CMS

considers each of that company’s regional PDPs a separate

plan. Entities that have drug plans in several regions may

choose to use the same formulary everywhere that they

operate, but they are not required to do so. However, the

company must submit separate bids to CMS for each PDP;

as a result, premiums for that entity’s plans could vary

across regions.

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 15

Note: PDP (prescription drug plan). 

Source: CMS 2005h.

CMS established 34 PDP regions

FIGURE

1-2
When creating the regions, CMS considered three 

factors. First, it looked for combinations of states in 

which sufficient numbers of Medicare beneficiaries live,

in order to ensure that at least two PDPs would have an

economically viable risk pool.11 At the same time, CMS

did not want to make the eligible population of regions too

large—potential Part D plan offerors expressed concern

about the degree of insurance risk to which they would 

be exposed, particularly during Part D’s startup. Second,

CMS aimed to keep PDP regions as compatible as

possible with MA regions; in doing so, CMS would 

avoid beneficiary confusion and simplify operations 

for MA–PDs. Finally, CMS sought to group states that 

had similar average levels of drug spending.

Medicare’s payments to plans

Each plan (stand-alone PDP and MA–PD) will submit

bids annually to CMS by the first Monday in June. Those

bids should reflect the plan’s expected benefit payments

plus administrative costs after they deduct expected

federal reinsurance subsidies. (See text box on federal

subsidies at the end of this chapter.) Plans will base their

bids on expected costs for a Medicare beneficiary of

average health; CMS will then adjust payments to plans

based on the actual health status of the plans’ enrollees. 

CMS will pay plans a monthly prospective payment

(called a direct subsidy) for each enrollee. This payment

equals the plan’s approved bid times the enrollee’s risk

adjustment factor, minus the enrollee’s premium for

standard coverage. In addition, CMS may pay plans

monthly prospective payments for average estimated

individual reinsurance on high-cost enrollees with drug

spending above the true out-of-pocket threshold. CMS 

will also pay plans monthly prospective payments for

beneficiaries who are enrolled in Medicare’s low-income

subsidy program. Although CMS will provide these

payments prospectively each month, the agency will

reconcile actual levels of enrollment, risk factors, levels 

of incurred allowable drug costs (after rebates and other

discounts), reinsurance amounts, and low-income

subsidies at the end of each year. 

Enrollee premiums

The main reason that beneficiary premiums will vary

among plans is that enrollees must pay for any difference

between their plan’s bid and the national average bid

amount. CMS bases the direct subsidy on a national

weighted average of plan bids. Thus, enrollees in costlier

plans could face higher-than-average premiums for

standard Part D coverage; similarly, enrollees in less

expensive plans would pay lower-than-average premiums.

This situation will likely happen within a given PDP

region. Likewise, beneficiaries who live in a part of the

country with higher-than-average spending on prescription

drugs may find that all plans in their area charge premiums

that are higher than the national average. The situation

would be reversed in regions with lower spending.

To calculate Medicare’s direct subsidy, CMS will average

the bids of risk plans (MA–PDs and PDPs), weighting

each bid by expected levels of enrollment. Enrollees 

will pay a portion of the national average bid plus any

difference between their plans’ bid and the national

average. (See text box for an example of how CMS will

calculate enrollee premiums.)

Policymakers disagree on the extent to which geographic

variation in Part D premiums is appropriate and

acceptable. Differences in opinion stem from whether one

believes that the costs of geographic variation in drug

benefits should be borne by the individuals who live in

regions that use more prescriptions, or redistributed more

broadly across all enrollees. Some believe that Part B’s

approach—in which enrollees pay the same premium

everywhere—is the fairer approach. Others believe that—

like the Part D benefit—it would be fairer for Medicare to

provide the same federal dollar subsidy to plans (adjusted

for each member’s health status) and require enrollees to

pay more if their region’s benefit spending is higher. 

Geographic variation in prescription

drug spending

The specific way in which Part D premiums are

calculated—with the enrollee premiums picking up 

the full difference from the national average—tends 

to magnify, in percentage terms, geographic variation in

drug spending. (See text box on p. 18 for a simulation 

of premium variation for a sample of Medicare

beneficiaries.) But to what extent does drug spending

vary? Such variation could occur if prices for the same

drugs differ around the country, or if prescription drug 

use varies geographically.

Variation in drug prices

Several factors suggest that drug prices should not vary

much across the country. Many of the entities involved in

making, delivering, and managing prescription drugs (such

as pharmaceutical manufacturers, retail pharmacy chains,

16 Monitoring the imp lementation of Part D
and PBMs) are large organizations with national contracts.

As a result, one might not expect to see much variation in

retail prices for drugs, except perhaps for differences in

transportation expenses or the cost of retail operations.

Past research finds only limited evidence of geographic

variation in prices. One recent study analyzed retail prices

of prescription drugs posted on the website for the

Medicare-endorsed drug discount cards. Researchers

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 17

How will CMS calculate enrollee premiums for Part D?

As a hypothetical example, assume that three

plans submit bids to offer Medicare’s new

prescription drug benefit in 2006, and each plan

has one-third of the total expected enrollment in Part D 

(Table 1-3). Plan 2 expects to have monthly drug

claims, administrative costs, and profits that are about

average, while Plans 1 and 3 expect to have costs that

are higher and lower, respectively. To submit their bids

to CMS, each plan will calculate monthly costs for a

Medicare beneficiary of average health, and then

subtract an estimate of the average monthly amount 

of individual reinsurance subsidies that the plan 

expects to receive from Medicare for its enrollees.

CMS will calculate the average of submitted bids,

weighted by the plans’ share of total enrollment. From

this nationwide average, the Medicare Prescription Drug,

Improvement, and Modernization Act of 2003 (MMA)

specifies that plan enrollees must pay a base premium

plus any difference between their plan’s bid and the

nationwide average bid. The basic enrollee premium

equals the nationwide average times a factor with a

numerator of 25.5 percent and a denominator of 100

percent minus CMS’s estimate of the plan’s revenues for

Part D benefits that it receives from federal individual

reinsurance. In the example below, this sum equals $37

per month. Thus, the enrollee’s premium is the sum of

the base premium plus the difference between his or her

plan’s bid and the national average bid. 

Example of how monthly enrollee premiums could vary 

for three prescription drug plans

Plan 1 Plan 2 Plan 3

Plan's expected cost of drug claims, administration, and profit $164 $146 $128

Plan's expected individual reinsurance subsidies – 42 – 38 – 33

Plan bid submitted to CMS $122 $108 $95

Plan's expected share of enrollment in Part D 33% 33% 33%

National average bid $108 $108 $108

Base enrollee premium $37 $37 $37

Amount by which plan's bid exceeds the national average bid + 14 – 0 – 13

Enrollee's monthly premium $51 $37 $24

Enrollee’s monthly premium divided by 

the base enrollee premium 1.36 1.00 0.64

Note: All bid costs are for basic Part D coverage for a Medicare beneficiary of average health. The national average bid is the average plan bid weighted by 

each plan's share of enrollment. The base beneficiary premium equals the national average bid multiplied by [0.255 / (1 – CMS's estimate of the 

percentage of total plan revenue attributable to individual reinsurance subsidies)]. This example assumes no adjustment of premiums for geographic 

differences in the prices of prescription drugs.

Source: MedPAC analysis based on data from CMS.

TABLE

1-3
18 Monitoring the imp lementation of Part D

Premium variation for a sample of privately insured Medicare enrollees

To demonstrate how Part D premiums will be set,

we asked Direct Research, LLC, to analyze a

sample of medical and drug claims for privately

insured individuals who are also enrolled in Medicare—

totaling about 1 million people in 2001. These data are

not representative of the Medicare population as a

whole: On average, the individuals for whom we have

claims have more years of education, higher incomes,

more comprehensive medical and drug coverage, and

somewhat better health status than the typical Medicare

beneficiary. 

The data set includes the number and type of

prescriptions filled at retail and mail-order pharmacies,

by type of drug. For price information, we mapped

nationwide average transaction prices for each national

drug code (NDC) in 2001 medical expenditure panel

survey (MEPS) data to NDCs listed on the privatepayer drug claims. As is the case with many claims 

data sets, price information from MEPS excludes any

manufacturers’ rebates. 

We used these data to examine two questions. First,

how much geographic variation in drug spending

exists? Second, what might premiums look like,

assuming that all Part D plans have their region’s

average mix of enrollees? For each individual, we

calculated the amount of Part D cost sharing that the

enrollee would owe and what benefits a standard plan

would cover, offset by federal individual reinsurance

subsidies for people with very high drug spending. We

calculated the average monthly cost per member for

Percentage geographic variation in drug spending and simulated 

premiums for a sample of privately insured individuals

FIGURE

1-3

Note: PDP (prescription drug plan). The nationwide averages have a value of 1.0, and regional values are depicted as an index relative to the nationwide mean. 

 Premiums were estimated from privately insured prescription drug claims for individuals who are also enrolled in Medicare. Estimates assume that plan 

 administrative costs are 5 percent of total enrollee drug spending. Premium estimates do not include assumptions about cost management savings or additional 

 enrollee utilization associated with insurance coverage.

 * The interquartile ratio is the value for the 75th percentile divided by the value for the 25th percentile. It measures the amount of variation across regions, an 

 amount that is less influenced by extreme values.

Source: Direct Research, LLC, for MedPAC. Index where 1.0 equ

als

the n

ationwide 

aver

age

1.4

.8

1.0

1.2

.6

.4

.2

0

Range of index values for total drug

spending per person across PDP regions

Range of index values for monthly

premiums across PDP regions

Ratio of highest region to lowest region = 1.4

Interquartile ratio* = 1.1

Ratio of highest region to lowest region = 2.5

Interquartile ratio* = 1.2

Contains values

for the 25th

through 75th 

percentile

Contains values

for the 0 through 

100th percentile

continued on next page
found little or no variation in the lowest available price for

the same drug across geographic regions (Bryant et al.

2004). On average, they found that retail prices were

slightly lower in rural states; however, variation in prices

across pharmacies within the same state was the more

striking phenomenon. In an analysis of 1998 retail prices

for 25 high-volume prescription drugs, researchers found

that third-party payers in the Northeast and West were

able to obtain greater discounts relative to cash customers

than purchasers in the South and Midwest (Department of

Health and Human Services 2000). In another study using

2002 data, researchers found only modest variation across

the country in the average price of a prescription (Sager

and Socolar 2004). However, researchers in that study did

not control for differences in the mix of drugs used.

The MMA specifies that when calculating enrollee

premiums, CMS may adjust the national average bid for

geographic variation in prescription drug prices. CMS

decided not to make such an adjustment in 2006 (CMS

2005a). The Department of Health and Human Services is

looking into whether an adjustment may be necessary.

Variation in the use of prescription drugs 

Geographic variation in Part D premiums will probably be

more closely associated with variation in prescription drug

use rather than variation in drug prices. In setting enrollee

premiums, the MMA does not call for any geographic

variation adjustment based on the use of prescription

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 19

Premium variation for a sample of privately insured Medicare enrollees (cont.)

enrollees in each PDP region, adjusting for health 

status using risk indexes estimated with CMS’s riskadjustment model. We added costs to approximate a

plan’s administrative expenses. Finally, we estimated

member premiums for each PDP region by following

the MMA’s formula—with members in each region

paying the difference between their average plan costs

and national average costs.

In percentage terms, our results suggest that enrollee

premiums for this sample of individuals show more

geographic variation than per capita drug spending

(Figure 1-3). Across the 34 PDP regions, average per

capita drug spending varies between a low of about 

0.8 and a high of 1.1, where 1.0 equals the nationwide

average. When ranked by drug spending per person, 

the highest-ranked region has spending that is 1.4 times

that of the lowest-ranked region. In the middle of the

distribution, regions at the 75th percentile have per

capita spending that is 1.1 times that of regions at the

25th percentile. By comparison, the distribution of our

simulated premiums is wider: ranging from about 0.5 

to 1.3, where 1.0 equals the nationwide average. The

highest ranked region has simulated premiums that are

about 2.5 times those of the lowest ranked region, and

the interquartile ratio for the distribution of premiums is

1.2. If the nationwide average Part D premium is $37

per month in 2006, enrollees like those represented by

these claims data who live in regions that fall in the

middle of this distribution (the interquartile range)

might see premiums that vary by about $8 per month.

Enrollees who live in most of the regions (spanning

from the 10th percentile to the 90th percentile) might

see premiums that vary by about $13 per month.

Individuals who live in regions at the tails of this

distribution would see greater variation in premiums.

In order to simulate premiums, we made a number of

additional assumptions. We inflated each person’s level

of prescription drug spending in 2001 to 2006 levels,

using nationwide projections of growth in drug

spending. We estimated plan benefits as though no

individuals would have supplemental drug coverage—

and thus, they would reach Part D’s catastrophic

threshold at $3,600 in out-of-pocket drug spending. 

We did not include any adjustment of each person’s

spending levels to reflect changes in the relative

generosity of their prescription drug coverage. Nor did

we make any adjustments to reflect plan management

that is more restrictive or less restrictive than that which

already occurs in the underlying drug claims. It is

possible that tighter management of prescription drug

spending could lead to less geographic variation in

spending than is observable today—and thus, premiums

might not vary as much. We assumed that plan

administrative costs would average about 5 percent 

of each region’s total drug spending. Finally, these

estimates are probably most sensitive to our assumption

that Part D plans operating in each region have their

region’s average mix of enrollees. drugs. However, the law does call on CMS to study

whether this type of an adjustment would be appropriate

and to report to the Congress by January 1, 2009. 

Available evidence shows considerable variation in 

rates of use, as well as the mix of drug therapies that

individuals use. For example, one study examined drug

claims for insured individuals ages 18 to 64 during 2000

(Express Scripts 2002). After adjusting for age and gender,

researchers found that the average annual number of

prescriptions per member across states varied by 150

percent, with higher values in the South and Midwest 

and lower ones in the Northeast and West. The same 

study documented geographic variation in prescribing

certain types of drug therapies. Calcium channel blockers,

prescription cough/cold/allergy medicines, corticosteroids,

and diuretics exhibited the widest variation. Similarly,

another study documented variation in prescribing for 

nine drug classes for an insured population across a

smaller geographic region—Michigan hospital service

areas (Wennberg 2000). Among prescriptions for adults,

researchers found the widest variation in antihistamines,

anti-anxiety drugs, proton pump inhibitors, and statins.

Evidence of geographic variation in

prescription drug spending

Various data sources provide information about

prescription drug spending. These data sources include

household surveys, manufacturer and retail surveys, and

information from drug claims. Unfortunately, each of

these data sources has limitations that complicate the

analysis of geographic variation for the Part D benefit.

The limitations vary depending on the particular data set.

Data from nationally representative surveys include too

few individuals to estimate geographic variation; surveys

of sales provide too little information about individual

people; and claims data—which typically include many

individual observations—are not fully representative of

the Medicare population. The most widely used household

surveys are designed to capture very detailed information

about use of, and spending on, health care services from 

a limited number of respondents. However, these surveys

do not include enough individuals to allow for an 

analysis of drug spending at the state level.12 Surveys 

of manufacturers and retail outlets (including brick-andmortar and sometimes mail-order pharmacies) serve as

another source of information, but they only allow one to

look at aggregate levels of retail sales or sales by type of

drug, rather than drug spending per individual.13 Insurers,

health plans, PBMs, and some public payers (including

Medicaid and state pharmacy assistance programs) 

collect very detailed drug claims. Currently, however,

neither private nor public drug claims data sets are fully

representative of the Medicare population. Beneficiaries

who have either Medicaid or retiree coverage probably use

more prescription drugs, on average, than the Medicare

population as a whole, because those individuals either

have more comprehensive coverage, are sicker, or both.

For Part D, CMS will require private plans to submit

certain data from their drug claims to allow the agency 

to make and reconcile payments, build risk adjusters, 

and perform periodic audits. However, no such data 

are available today. CMS is using the same types of 

data described above—particularly the Medicare Current

Beneficiary Survey, as well as Medicaid and privatepayer drug claims.14 The agency has also made much of

its data available to organizations that are considering

bidding to become Part D plans. 

Due to the lack of a gold standard among drug data sets,

plans face a very difficult task in constructing their initial

bids for Part D. Some potential entrants—such as MA

plans, insurers, and PBMs—can use their own existing

claims information to help in that effort. Nevertheless, 

a plan’s current data probably do not fully represent 

the mixtures of enrollees that the plan will have after

January 1, 2006. 

Although no gold standard exists among drug data sets,

publicly available data suggest geographic variation exists

in prescription drug spending. However, patterns in that

variation are not consistent and depend on which data

source one uses. Figure 1-4 divides the country into 

four regions—the Northeast, Midwest, South, and West. 

We needed to aggregate the data by these regions because

data limitations, such as survey sample sizes, make less

aggregate estimates unreliable. For each data set, we

calculated average per capita drug spending by state 

and then calculated an average per region, weighted by

population. We did not adjust those values for differences

in health status. The absolute levels of per capita drug

spending differ across data sets because each source

reflects somewhat different populations and time periods.

For that reason, Figure 1-4 shows regional variation

around an index value of 1.0, which represents the 

overall national average specific to each data set. 

20 Monitoring the imp lementation of Part D
Although they show some geographic variation, the data

sets do not tell precisely the same story. In general, the

data show that per capita drug spending in the South is

somewhat higher than the nationwide average and that

spending in the West is lower than average. One data 

set suggests that people who live in the Northeast have 

the highest spending per person; other data show that

individuals in the Midwest or South have the highest

spending per person. 

Why does prescription drug 

spending vary?

A number of factors are likely to be associated with

geographic variation in drug spending, including the

health status of the individuals who live in a region, the

number of providers who operate in the area, regional

differences in prescribing patterns, the average incomes of

beneficiaries in each region, and the availability of health

and drug coverage. 

Generally, one would expect individuals who are in poorer

health to use more prescription drug therapies. CMS’s Part

D risk-adjustment model supports this expectation (CMS

2005a). CMS adapted its hierarchical condition category

(HCC) model, which uses demographic and diagnosis

information from Medicare Parts A and B claims (or

comparable information submitted by MA plans) to

predict plan claims’ liability for a standard Part D 

benefit.15 The model predicts more than 20 percent of

variation in drug spending across individuals, which is

higher than the risk-adjustment models CMS uses to

predict spending for Parts A and B benefits. 

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 21

Geographic patterns of per capita drug spending vary by data source 

FIGURE

1-4

Note: MEPS (Medical Expenditure Panel Survey), MCBS (Medicare Current Beneficiary Survey, Cost and Use file). The U.S. average per capita spending level for each data 

 source equals one. MEPS data reflect a nationally representative sample of the U.S. population. MCBS data reflect a nationally representative sample of Medicare 

 beneficiaries. We pooled MCBS observations during the 1998–2001 period to increase sample sizes before constructing the index. CMS provided average levels of drug 

 spending by state for a sample of federal retirees and their spouses who are age 65 or older. CMS estimated per capita drug spending at the state level for people of all 

 ages using a variety of data sources for its national health expenditures. The Kaiser Family Foundation’s estimates of drug spending are based on 2003 VectorOne data 

 from Verispan collected from retail pharmacies, third-party payers, and other sources.

Source: Direct Research, LLC, for MedPAC. Index where 

aver

age 

spending equ

als 1.0

1.2

.6

.8

1.0

.4

.2

0

MCBS pooled, 

1998–2001

Kaiser Family Foundation,

under age 65, 2003

Northeast Midwest South West

MEPS, all ages, 

2002

CMS website, 

sample of federal 

retirees and spouses 

age 65+, 2002

National health

expenditures, 1998

Kaiser Family Foundation,

age 65 and older, 2003
In order to evaluate average health status across PDP

regions, we used CMS’s risk-adjustment model and

calculated indexes of Part D benefit spending using

diagnosis codes in 2001 claims data for a 5 percent 

sample of fee-for-service Medicare beneficiaries.16

With a nationwide average of 1.0, those indexes range

from 0.87 to 1.05 across the PDP regions (Table 1-4). 

The region with the highest index shows predicted drug

benefit spending that is 1.2 times that for the region with

the lowest index. The interquartile ratio—a measure less

influenced by the tails of the distribution—is 1.1. Regions

with the lowest risk indexes tend to be in the West and

Midwest, but those with the highest indexes include

regions in the South, East, and Midwest.

Because Medicare beneficiaries are, on average, healthier

in certain parts of the country than others and because

drug spending relates to an individual’s health status, 

risk-adjustment models can help to predict geographic

variation in drug spending. But by their nature, predictions

of health status from such models are imperfect. In other

words, risk-adjustment factors do not reflect all of the

variation in health status that exists among Medicare

beneficiaries. Thus, the underlying health status of

beneficiaries in a region probably accounts for more of 

the geographic variation in drug spending than researchers

can predict. One key reason is that researchers build risk

adjustors from claims data, which have some well-known

limitations. For example, providers may not record

diagnoses thoroughly or consistently on claims. They 

are most likely to report diagnoses when they are actively

treating a beneficiary for a condition. If an individual has 

a condition that does not require active intervention in a

given year, providers may not list the diagnosis

information on his or her claims.

Other factors that may explain geographic variation in

drug spending include the relative supply of providers, the

composition of that workforce, and physician prescribing

patterns in the area. Previous research suggests that

spending for Medicare Parts A and B by state is positively

correlated with the number of specialists per 10,000

population and negatively correlated with the number of

general practitioners per 10,000 (Baicker et al. 2004).

Likewise, the relative availability and composition of a

region’s physician workforce may also explain how many

prescriptions a population uses, on average. Patterns of

prescribing may differ across regions. For example, it may

be acceptable to prescribe antibiotics more routinely in

some parts of the country compared with others.

Average levels of income are also related to variation in

prescription drug spending, but third-party coverage

complicates that relationship. Medicare beneficiaries who

22 Monitoring the imp lementation of Part D

Variation in characteristics of PDP regions

Ratio of 

Range highest region Interquartile 

of values to lowest region ratioa

Region’s HCC risk index for covered drug benefit spendingb 0.87–1.05 1.2 1.1

Percentage of region’s elderly population 

with income less than 100% FPLc 7–19 % 2.8 1.5

with income less than 150% FPLc 14–34 2.4 1.4

Percentage of region’s Medicare population 

that receives a Part B buy-ind 9–29 3.2 1.6

who also have employer-sponsored coveragee 22–55 2.5 1.2

who are enrolled in Medicare Advantage plansf <0.5–32 159.4 6.5

Note: PDP (prescription drug plan), HCC (hierarchical condition category), FPL (federal poverty level). a The interquartile ratio is the value for the 75th percentile divided by the value for the 25th percentile. It measures the amount of variation across regions, 

an amount that is less influenced by extreme values.

b Estimated using CMS’s model and based on diagnoses in 2001 claims for a 5% sample of Medicare fee-for-service beneficiaries. The nationwide average 

is 1.00.

c Based on the 2000 census. 

d “Part B buy-ins” are dual eligibles for Medicare and Medicaid. Their state Medicaid program pays their Part B premium. e Data pooled from the 1999, 2001, and 2003 Current Population Surveys.

f CMS Medicare Advantage state and county penetration report files, June 2004.

Source: Direct Research, LLC, for MedPAC.

TABLE

1-4
have very low incomes may qualify for Medicaid and may

thereby receive fairly comprehensive prescription drug

coverage. Likewise, people who earn higher incomes are

more likely to have employer-sponsored retiree health

benefits, which often include drug coverage. In general,

individuals who have third-party drug coverage tend to

pay lower prices for a given drug at the point of sale, but

they also tend to use a costlier mix of drugs compared to

individuals with no drug coverage (Department of Health

and Human Services 2000). 

Average incomes of Medicare beneficiaries and the

availability of health coverage vary broadly across PDP

regions. For example, in some regions as few as 7 percent

of the Medicare population earn incomes below the federal

poverty level, while in other regions nearly 20 percent 

fall below the poverty level. The share of each region’s

beneficiaries who are dually eligible for Medicare and

Medicaid (as measured by the number whose states pay

for their Part B premium) ranges between 9 percent 

and 29 percent. The availability of and enrollment in

employer-sponsored health coverage or MA plans 

varies even more widely. 

Geographic variation in each of these factors suggests that

considerable variation could exist in drug spending and in

Part D premiums. On the other hand, private plans’ efforts

to manage the Part D benefit could reduce geographic

variation in drug spending and in premiums.

Who will enroll in Part D?

Although important, premiums for Part D plans are just

one of several factors that Medicare beneficiaries will

consider in deciding whether to enroll in the new program.

Part D is quite complex, and the general level of Medicare

beneficiaries’ understanding about the new benefit and

how it works will be important in their decision making.

In order to encourage broad initial enrollment, Part D

includes a penalty for late enrollment similar to that of

Part B. However, many Medicare beneficiaries may not be

aware of or understand that provision yet. Even those who

know more about the late enrollment penalty may find its

initial level—about $5 per month for those who postpone

signing up until 2007—low enough to be worth delaying

enrollment until they know more about the program. 

The Commission suggests that CMS move as quickly as

possible to determine whether the penalty amount fairly

reflects any higher costs associated with delaying

enrollment (MedPAC 2004). CMS should inform

Medicare beneficiaries of the penalty and how it could

affect their premiums if individuals delay enrollment.

More than six million Medicare beneficiaries—over 15

percent of the Medicare population—are eligible for

Medicaid (MedPAC 2004). These individuals may

represent a disproportionate share of early enrollees in 

Part D because CMS plans to auto-enroll them into plans

at the end of 2005. As Table 1-4 shows, the percentage of

each region’s Medicare population that consists of dual

eligibles varies considerably around the country. It is

unclear how differences in the proportion of each region’s

Medicare population that CMS auto-enrolls will affect

geographic variation in Part D premiums.

There is even greater uncertainty about how many other

types of Medicare beneficiaries will enroll in Part D plans.

Currently, Medicare beneficiaries get drug coverage from

a variety of sources. In 2001, just over 30 percent of the

Medicare population had retiree drug coverage. Decisions

by these individuals about whether to enroll will depend

on how their former employers respond to the introduction

of Part D. About one-quarter of beneficiaries currently

have individually purchased Medigap policies, and their

response to Part D is also uncertain. Only a small share 

of those Medigaps currently include prescription drug

coverage—this share makes up less than 10 percent 

of total enrollment in standard Medigap policies. It is

unclear how many beneficiaries who purchase Medigap

policies without drug coverage will be willing to pay an

additional premium to enroll in Part D plans.

MedPAC plans to monitor enrollment trends in Part D.

CMS will hold Part D’s initial open enrollment period

from November 15, 2005, through May 15, 2006. 

During that time, beneficiaries will likely receive a lot 

of information about Part D, both from CMS and from

individual plans operating in each region. As we shall 

see in the next section, CMS will have to make that

information easy to obtain and understand to ensure 

broad participation in Part D.

The Medicare discount drug card and

beneficiary outreach for Part D 

Before beneficiaries can enroll in Part D plans, they must

learn about the program and the choices they face. In the

months before Part D becomes effective, CMS, the states,

beneficiary advocates, and drug plans must educate

beneficiaries about the new drug benefit. In 2004,

Medicare beneficiaries became eligible to enroll in the

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 23
Medicare-sponsored discount drug card program.

Beneficiaries who earned incomes below 135 percent of

the federal poverty level could receive additional

subsidies. By implementing the drug card program, 

CMS provided states with some early experience in

reaching Medicare beneficiaries and counseling them

about prescription drug plan choices. We interviewed

individuals who participated in these efforts to determine

what lessons they learned that could improve outreach

efforts for Part D. 

Elderly and disabled Medicare beneficiaries will begin

enrolling in Medicare prescription drug plans in

November 2005.17 To begin receiving benefits by January

1, beneficiaries must navigate a tight timeframe. CMS, 

the Social Security Administration (SSA), state Medicaid

programs, and beneficiary advocates will have little time

to educate beneficiaries about their choices, help those

who are qualified apply for low-income subsidies, 

and help beneficiaries make informed decisions. State

Medicaid officials and beneficiary advocates have found 

it particularly difficult to inform low-income Medicare

beneficiaries about their health insurance options. 

In this section, we examine the challenges that state

officials and beneficiary advocates face in educating

beneficiaries about the discount drug card program. 

Next, we assess the relevance of this experience for the

outreach efforts designed to inform dual eligibles—and

other beneficiaries who are eligible for low-income

subsidies—about their choices in 2006. 

We draw four key lessons from state experiences with the

discount drug card:

• CMS and drug plans must provide accurate, easily

obtainable information about plan options.

Counselors emphasized that beneficiaries need 

timely and accurate information. In the first weeks 

and months of the discount card program, counselors

and beneficiaries encountered difficulties using the

web-based tool, inaccuracies in the information that

CMS provided, and changes in plan offerings. This

confusion may have deterred enrollment in the

discount card program.

• CMS should design federal outreach efforts so that

they direct beneficiaries to state outreach and

enrollment activities. States currently are responsible

for providing prescription drug coverage to many

individuals who will need to enroll in drug plans under

Part D, including dual eligibles and enrollees in State

Pharmacy Assistance Programs (SPAPs). To avoid

confusion and ensure access to information and

counseling, CMS should send materials to Medicare

beneficiaries that indicate sources of assistance

available in the state in which they reside—including

Medicaid, SPAPs, and State Health Insurance

Assistance Programs (SHIPs)—state-based

organizations that receive federal funds to provide

information and counseling about insurance issues 

to Medicare beneficiaries.

• CMS needs to develop better strategies for conducting

targeted outreach to Medicare populations. State

officials found it difficult to reach low-income

beneficiaries, individuals with disabilities, enrollees

with low literacy, and beneficiaries with limited

English proficiency. Interviewees emphasized the

importance of one-on-one counseling to explain

eligibility for complex programs such as Part D and

noted that adequate resources for SHIPs are crucial.

However, even with enhanced funding, SHIPs will 

not be able to counsel all beneficiaries who need help

understanding their choices under Part D. CMS will

need to inform physicians and pharmacists about the

program because they often serve as trusted

intermediaries for beneficiaries.

• CMS should consider auto-enrollment for

prescription drug coverage and low-income subsidies

for selected Medicare populations. Federal, state, 

and private outreach efforts were relatively ineffective

in enrolling large numbers of beneficiaries in the

discount card program. For example, of the estimated

7.3 million Medicare beneficiaries who were eligible

to enroll in the transitional assistance program 

in 2004, only 1.5 million actually enrolled. Autoenrollment was far more effective than voluntary

enrollment and accounted for a large share of the

overall enrollment. SPAPs and Medicaid officials, 

as well as SHIP directors and counselors, suggested

that auto-enrollment will be a critically important 

step in the success of Part D. 

The Medicare discount drug 

card program

The MMA included the discount drug card program to

provide temporary assistance with the cost of prescription

drugs to Medicare beneficiaries until the Part D benefit

begins in 2006. In exchange for an annual fee of up to $30,

24 Monitoring the imp lementation of Part D
drug card enrollees receive discounts off the retail price of

prescription drugs. The cost of the card and the discounts

vary depending on the card a beneficiary selects and the

drugs a beneficiary uses. Different cards offer different

combinations of discounts on different drugs, and

discounts also vary across pharmacies. Beneficiaries could

enroll in a discount card at any time without penalty, but

once they enroll they could only change cards once—

between November 15 and December 31, 2004. 

Medicare beneficiaries who earn incomes below 135

percent of the federal poverty level can also receive

transitional assistance. Those who qualify do not have

to pay enrollment fees and they receive a credit of $600 

per year on their discount cards.18 Beneficiaries who are

enrolled in Medicaid or other public or private insurance

plans (except for SPAPs) cannot enroll in the card

program and are not eligible for the subsidy. 

Similar to Part D, the discount drug card program is

voluntary. Before the program began, federal government

agencies, state agencies, and private plans all engaged in

efforts to inform beneficiaries about available cards and

subsidies and to facilitate enrollment. CMS and SSA sent

mailings to all Medicare beneficiaries about the discount

card and the availability of transitional assistance. These

mailings informed beneficiaries that they could call a

federal customer service line or use Medicare’s website 

to obtain comparative information on discount cards. In

addition, the federal government provided new funding 

to SHIPs to help beneficiaries who sought assistance in

making choices about the discount cards. The private

companies that sponsored Medicare-approved drug

discount cards also marketed their cards to the Medicare

population and received enrollment applications for the

cards and for the low-income subsidy.

CMS implemented the program quickly. The agency

approved card sponsor applications on March 26, 2004.

Beneficiary enrollment began on May 3, and cards became

effective on June 1. Beneficiaries could choose from 

39 national cards as well as other regional cards. CMS

estimated that 15.4 million beneficiaries were eligible for

the program, including 7.3 million who were eligible for

transitional assistance. Despite beneficiary education and

outreach efforts by CMS, SHIPs, and SPAPs,19 enrollment

was lower than expected. By December 2004, 5.8 million

beneficiaries had enrolled in discount card programs,

including 1.5 million who were also receiving transitional

assistance (CMS 2004).20 The majority of these

individuals were enrolled automatically through their 

MA plan or SPAPs.

MedPAC contracted with researchers at the National

Opinion Research Center (NORC) and Georgetown

University to examine state experience in helping to

implement the drug card. They focused on the successes

and challenges of outreach strategies and how these

experiences might inform implementation of the Medicare

drug benefit. Between March and September 2004,

researchers conducted structured interviews with 46

state officials, pharmacists, and beneficiary counselors 

in 26 states. 

State outreach strategies

In early interviews that researchers conducted before CMS

implemented the discount card program, state officials

indicated that states would conduct outreach activities,

contingent on federal funding. These interviews revealed

that the level of effort and resources committed to

outreach would vary across states. For example, some

SHIP programs are well-funded and supplement their 

staff through a large base of volunteer counselors in a

wide variety of field locations. Other programs may 

have few volunteers and few outreach sites.

None of the interviewees suggested that they would

implement outreach efforts to enrollees in Medicare

Savings Programs, which include the Qualified Medicare

Beneficiary (QMB) program and Specified Low-Income

Medicare Beneficiary (SLMB) program. Few of these

state officials had developed plans to target disadvantaged,

frail, and isolated populations with information about the

discount card. SHIP officials suggested that they had little

capacity to identify beneficiaries who were potentially

eligible for transitional assistance in their state.

Because Medicaid recipients were not eligible for the

discount card, SHIPs and SPAPs primarily conducted 

the outreach for the discount drug card program. SHIPs

typically conducted broad, community-based outreach 

to increase awareness about the discount card and lowincome subsidy programs, and responded to requests for

assistance and information. SPAPs generally undertook a

more targeted approach. They actively reached out to their

enrollees to ensure funding for those who were eligible 

for transitional assistance subsidies. 

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 25
In general, SHIPs:

• tried to increase community awareness of the discount

card and other prescription drug assistance programs,

and

• included information about the cards and transitional

assistance as part of their normal counseling services.

In general, SPAPs:

• sent direct mailings to their members providing

information about the discount cards, and

• sometimes chose to auto-enroll their members in a

preferred drug card program.

State experience with the discount card

With some exceptions, SHIP counselors reported low

levels of interest in the cards and low levels of voluntary

enrollment in both the discount card and transitional

assistance programs. They identified a number of factors

that limited voluntary enrollment, including a perception

by beneficiaries that the program was too complex and

offered relatively little savings to enrollees. SHIP

counselors suggested that outreach efforts had failed to

reach many of the low-income individuals who would

benefit most from the $600 annual subsidy. 

Interviewees emphasized the importance of one-on-one

counseling for Medicare beneficiaries. In interviewees’

experience, direct mailings, call centers, and website

information all posed problems for communicating

important information to beneficiaries. According to

counselors, beneficiaries routinely receive large amounts

of direct mail that advertise drugs and other health care

services and items. As a result, official state mailings

might attract no more attention than any other form of

advertising. Low literacy, limited English proficiency, 

and limited understanding of health care programs also

interfere with beneficiaries’ ability to comprehend and 

act on direct mail instructions. 

Additionally, counselors expressed concern that the 

1-800-Medicare call center operators provided too much

information, rather than helping beneficiaries narrow their

options. Counselors also worried that these operators 

were conveying inaccurate information. In a 2004 study

conducted by the GAO, researchers received inaccurate

answers to 29 percent of their questions and could not

obtain any answer 10 percent of the time. Among other

recommendations, GAO suggested that CMS provide

more thorough testing of contractors’ ability to answer

questions and monitor the accuracy rate for frequently

asked questions.

Lastly, counselors expressed mixed feelings about the

Medicare web-based decision tool that CMS developed.

The agency intended this database—The Prescription

Drug and Other Assistance Programs—to allow

beneficiaries to compare discount cards. Counselors 

found this tool useful in their offices but inaccessible to

most elderly beneficiaries. Even beneficiaries who were

computer literate and had Internet connections in their

homes were unlikely to have the high-speed connections

necessary to use the drug card website.

On the other hand, some counselors reported that the

publicity over the discount card created new opportunities

for beneficiary education. Beneficiaries who did not

previously know about the SHIP’s resources came for

counseling sessions and were screened for eligibility for

other programs. Depending on the state, this could include

Medicaid or SPAP screening, and screening for nonhealth

programs such as energy assistance.

By comparison, SPAPs experienced success with autoenrollment and facilitated enrollment in a preferred card 

or cards. In cases in which programs auto-enrolled

beneficiaries, programs gave beneficiaries the choice 

of opting out of the program after enrollment. Eleven

states used auto-enrollment to sign up their program

recipients for a specific or preferred discount card or cards

(Fox 2005). For example, New Jersey auto-enrolled all

members who were eligible for transitional assistance into

a preferred card program unless those members explicitly

opted out of the program. Connecticut required all state

program members who were eligible for transitional

assistance to apply for a discount card and supplied 

them with a list of all the cards available within the state

(Rutgers Center for State Health Policy 2004). States that

used auto-enrollment achieved high participation rates in 

a short period of time—these rates ranged from 80 to 90

percent of eligible members. Conversely, the five states

that encouraged members to voluntarily enroll in 

the discount card program experienced much lower

enrollment rates, ranging from 2 to 40 percent (Fox 2005).

Lessons learned for implementing Part D 

Interviewees suggested that the challenges of

implementing the discount card program—and the

resulting low levels of voluntary enrollment, especially 

26 Monitoring the imp lementation of Part D
of beneficiaries who were eligible for the low-income

subsidies—were likely to become more problematic in

2006 with the implementation of Part D. SHIP counselors

worried about the program’s complexity and noted that

elderly Medicare beneficiaries would likely be confused

by the drug benefit design, including the deductible,

coverage gap, and catastrophic coverage. Interviewees

noted that any changes to the operation of the benefit—

for example, mid-year changes to the formularies—

would compound the already formidable challenges to

beneficiary education. SHIP counselors indicated that

beneficiaries could feel overwhelmed by the number of

choices they face and thus may fail to enroll in a program

that could provide them with significant benefits. 

Many interviewees acknowledged that their organizations

are designed to assist a mainstream elderly population.

However, the organizations are less equipped to

effectively counsel hard-to-reach groups such as those in

nursing homes or other long-term care settings; younger

beneficiaries with disabilities; and members of racial and

ethnic minorities who face linguistic, cultural, and

educational barriers. Interviewees stressed the need for

targeted strategies to reach these populations. They

suggested that CMS should develop strategies that 

include physicians and pharmacists who experience 

daily contact with beneficiaries.

Interviewees repeatedly stressed the success of autoenrollment in reaching low-income populations. When

CMS implements Part D, the agency will auto-enroll

Medicare beneficiaries who are also eligible for

comprehensive Medicaid benefits in plans. CMS will 

not use auto-enrollment for other groups but will develop

alternative mechanisms to facilitate enrollment for some

other low-income groups. In particular, CMS may use

such mechanisms to target individuals who are enrolled 

in the Medicare Savings Program if they have not enrolled

in a Part D plan by May 2006. SPAPs had requested 

CMS to give them the authority to auto-enroll their

members, but CMS did not accept this recommendation

(CMS 2005b). CMS should monitor enrollment by lowincome groups in Part D and increase auto-enrollment, 

if necessary.

Once beneficiaries enroll in Part D plans, they will have 

to learn how to use plan procedures to ensure that they

receive needed drugs. In the next section, we examine 

plan formulary exceptions and appeals processes.

Formulary exceptions and the 

appeals processes

Medicare Advantage drug plans (MA–PDs) and standalone Medicare prescription drug plans (PDPs) can 

use techniques developed in the commercial market to

control cost and enhance the quality of the drug benefit.

These techniques include formulary development, tiered

copayment benefit structures, prior authorization,

pharmacy networks, and mail order pharmacies. Plans

must establish formulary exceptions and appeals processes

to ensure that these techniques do not deprive beneficiaries

of access to needed medications. 

MedPAC staff interviewed physicians, beneficiary

advocates, pharmacists and representatives from health

plans, and pharmacy benefit managers (PBMs) about

formulary exceptions processes and beneficiary appeals.

In this section, we present findings from our research on

how the private market and Medicaid handle requests for

prescription drugs that are not on a plan’s formulary or

require prior approval. We compare current practice with

requirements under the Medicare drug benefit. 

We found the following key findings: 

• Plans and PBMs currently have well-established

processes to handle formulary exceptions and prior

authorization requests. Accrediting organizations and

states scrutinize these processes, and the processes 

are similar to those that CMS regulations prescribe. 

• Patients usually do not appeal denied requests for

formulary exceptions. Physicians frequently decide that

the formulary drug is acceptable, when the pharmacist

informs them of the nonformulary status of the

prescribed drug. When patients and physicians pursue

requests, plans report very high approval levels. 

• The volume of appeals may increase under Part D.

• Beneficiaries who are dually eligible for Medicare 

and Medicaid will have fewer appeal rights under 

Part D than they currently have under Medicaid. 

For example, Medicaid programs must continue to

provide ongoing drug treatment to beneficiaries while

an appeal is underway. Part D plans will not face this

requirement. When dual eligibles begin receiving their

drug benefit from Part D plans, some may be taking

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 27
drugs that are not on their plans’ formulary. CMS 

will need to monitor plan transition policies to ensure

that beneficiaries continue to receive appropriate

medications and do not delay or stop treatment because

they face unfamiliar formulary exceptions processes. 

Formulary exceptions: Current practice

and Part D

Health plans and PBMs are experienced at handling

requests for formulary exceptions. Requests for exceptions

depend on the structure of the benefit. In a closed

formulary,21 drug coverage is limited to the specific

medications that the plan places on the formulary.

However, plan members sometimes may get an additional

drug covered if the plan determines that the drug is

medically necessary. In this case, a member—with

physician support—requests a formulary exception. Plans

may grant exceptions provided that the physician has

shown that the covered formulary drugs are ineffective or

will likely result in adverse consequences for the member. 

In a tiered or incentive-based formulary, the plan charges

different copayments for covered drugs. Typically,

copayments differ for generic drugs, preferred branded

drugs, and nonpreferred branded drugs, with generic drugs

carrying the lowest copayments. Plans may limit access to

nonpreferred drugs by requiring the member’s physician

to get prior approval from the plan before dispensing the

drug. State Medicaid programs also may require prior

authorization for many drugs, particularly in those states

that have preferred drug lists. 

Under the final regulations published January 28, 2005,

CMS permits plans to use tools such as tiered copayments,

closed formularies, prior authorizations, and step therapy

to manage utilization and cost of the Medicare drug

benefit. The regulations discuss plan procedures to handle

requests for formulary exceptions and prior authorizations.

CMS requires plans to establish processes and notify 

plan members of policies for obtaining formulary and

copayment exceptions, but CMS does not mandate

specific methods. 

Currently, plans differ on the number of drugs they restrict

and the rationale for requiring prior authorization. One

interviewee emphasized that his plan placed on its prior

authorization list only those drugs required to treat chronic

conditions because beneficiaries refill prescriptions for

these drugs multiple times. However, another interviewee

reported that his plan placed some new antibiotics on its

prior authorization list.

Interviewees gave many examples of cases in which a

particular drug might require preauthorization. Some

examples include:

• the drug is not on the plan’s formulary 

(for closed formularies);

• a lower cost formulary drug is available;

• an equally effective over-the-counter medicine 

is available;

• a nonpreferred drug is heavily advertised 

and is subject to overutilization;

• the drug is a high-cost injectable;

• the request is for a larger quantity of the drug 

than plan administrators believe is clinically

appropriate; and

• physicians prescribe the drug for a number 

of conditions without sufficient supporting 

medical evidence.

Because the formulary exceptions and prior authorization

processes are generally the same, we do not distinguish in

this section between the two. However, we remind readers

that a plan’s benefit package sometimes excludes entire

specific categories or types of drugs. For example most

private plans do not cover over-the-counter medications.

In those cases, the plan would not consider those drugs

part of the covered benefit and thus the formulary

exceptions processes would not apply. Part D plans 

cannot cover drugs that Medicaid programs may 

exclude (such as weight loss drugs) and cannot cover

drugs eligible for Medicare Part A or Part B coverage. 

How does the process work?

Call centers serve as the first point of contact for

formulary exceptions and prior authorization. Plan

representatives in call centers—often pharmacy

technicians—receive preauthorization requests from

providers and use written protocols to determine if the

request meets clinical guidelines for approval. The plan’s

pharmacy and therapeutics (P&T) committee usually

approves the protocols. Many of our interviewees reported

that call-center workers could approve requests but could

not deny them. Pharmacists or physicians who work for

the PBM or health plan usually review requests that do not

28 Monitoring the imp lementation of Part D
meet criteria stipulated in plans’ protocols. (Some states

mandate that only a physician can reject a request for 

prior authorization.) At this point, the plan may ask the

prescribing physician for additional information. If 

the plan physician still rejects the request, the plan

administrator will ask a medical director and/or

pharmacist (who has not been involved in the original

decision) to review the request. An additional negative

decision would constitute a coverage decision, and a

patient who wished to pursue the request would then 

go through the health plan’s formal appeals process. 

As discussed below, all interviewees reported that

prescription drugs rarely are the focus of formal appeals. 

Many requests do not go through the entire internal

process. Physicians frequently decide, after they learn 

of the prescribed drug’s nonformulary status, that 

the formulary drug is acceptable. When physicians 

pursue requests, plans report very high levels of prior

authorization approvals. Most interviewees indicated 

that the most common reason for initially rejecting a

request was the lack of evidence of medical necessity.

When providers supplied such evidence, plans granted

most requests. 

We found considerable variation in the extent to which

plans rely on prior authorization. Some interviewees

reported that the costs of reviewing prior authorization

requests limit the utility of the process. Because plans

must meet timeframe requirements for handling prior

authorization requests, they determine call-center staffing

based on the number of requests that staff must handle 

on a daily basis. Additionally, requests for prior

authorizations and other exceptions pose a burden to 

plan members, physicians, and pharmacists. Plans may

decide that the savings realized from these processes 

are outweighed by the negative effects on patient and

provider relationships. Several interviewees reported that

some drugs were taken off prior authorization lists 

because nearly all requests were approved. However, 

other interviewees cited specific cases in which clinical

evidence indicated that a drug was being overused. In

those cases, plans typically deny requests for exceptions. 

The following cases are typical:

• One plan representative noted that the plan required

prior authorization for all nonsedating antihistamines

after one product in this class became available to

patients over the counter. In order for members to

receive coverage for any of the prescription products

in this category, their physicians had to document 

that the over-the-counter medicine had not controlled

their patients’ allergies—a process known as step

therapy. Our interviewee reported that the plan had 

to hire six new employees to handle the resulting

volume of calls requesting exceptions. However, the

plan calculated that it has saved $10 million because

of this one decision.

• Several interviewees reported that they placed all

medications in the cyclo-oxygenase–2 (COX–2)

therapeutic class on the prior authorization list. 

Their plans received many requests for exceptions, 

but the plans believed that the drugs were overused

compared with other pain medications and thus were

only appropriate for a small group of high-risk

individuals. Due to the high volume of requests for

exceptions, the plan reviewed its criteria. However,

plan physicians concluded that their original decision

was clinically appropriate and they continued to deny

requests for exceptions.

• Several interviewees reported placing human growth

hormone on their prior authorization list. They

covered the product in cases where clinical evidence

of medical necessity was available. However, they did

not want to cover it for lifestyle uses such as body

building. In these types of cases, plans will often ask

for additional clinical information to ensure that the

physician is prescribing the product for a medically

necessary reason.

• One interviewee pointed out that prior authorization

can be useful even when the plan approves the request

in nearly all cases. He noted that when a pharmacy

notifies a physician that a patient’s plan does not cover

the requested drug—but covers other drugs to treat 

the same condition—the physician often agrees to

prescribe the preferred drug without a request for 

prior approval ever reaching the call center.

State Medicaid programs often use prior authorization 

as their main cost management tool. These plans cannot

use tiered cost sharing or closed formularies to move

beneficiaries to preferred drugs. Placing drugs on a prior

authorization list is one way in which Medicaid programs

can affect physician prescribing patterns. 

Interviewees reported that plans keep careful records on

the results of their exceptions processes. Plans then use the

data to evaluate their utilization management tools and to

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 29
weigh the costs and benefits of restricting use of particular

medications. If a plan receives many requests for

exceptions for a specific drug, it may ask its P&T

committee to review the clinical evidence on the 

product and determine whether to change the drug’s

formulary status. 

Managing prior authorization

Although all interviewees agreed that, ideally, providers

would receive prior authorization before they write a

prescription, this is often not the case. Most physicians 

see patients from a variety of health plans. Each plan 

will have its own formulary, prior authorization list, 

and specific procedures for obtaining approval. Recent

research indicates that the majority of physicians do not

know which drugs are on their patients’ formularies 

(Shih and Sleath 2004). 

Frequently, the need for prior authorization will only

become apparent when a patient brings a prescription to a

pharmacy. The pharmacist who is attempting to process

the prescription will receive an electronic message from

the PBM indicating that the drug cannot be dispensed as

written. Pharmacists say that the exact content of the

message differs depending on insurer and PBM. Some

messages simply report that the plan does not cover the

drug. Other plans provide suggested alternative covered

drugs, or provide phone numbers that physicians can call

to get prior authorization. Upon receiving the electronic

message, the pharmacist usually contacts the prescribing

physician. At this point, the physician may change the

prescription to the plan’s preferred drug or request prior

authorization from the plan. Alternatively, the pharmacist

may tell the patient that her plan does not cover the drug.

Then the patient must decide whether to pay out of 

pocket for the requested drug, leave without any drug,

or go back to her physician and ask for a drug that is 

on the plan’s formulary. 

In most cases, plans have little control over which actions

the pharmacist and physician will take and only limited data

on what actually happens. In one small study, researchers

analyzed what happens to patients when pharmacies reject

their nonformulary prescriptions (Cox et al. 2004). They

found that the majority of health plan members eventually

get a drug to treat their condition. About 40 percent of

surveyed individuals got the formulary drug while 15

percent got prior authorization for the prescribed branded

drug. A little over 10 percent received no medication 

for the treatment, and an equal share paid full price 

for the medication.

Pharmacists and physicians will most likely consider 

the prior authorization process unpaid additional work.

Apart from the time it takes to contact physicians for prior

authorizations, pharmacists report that the PBM or other

electronic messaging company charges them a transmittal

transaction fee for every message they must relay before 

a prior authorization is approved. One physician noted 

that two staff nurses each spend about one hour per day

providing information for prior authorization requests.

Further, plan members are likely to be unhappy with 

their health plan if they cannot get access to a drug that

they believe is medically necessary or if they have to 

make multiple visits to the pharmacy to get a single

prescription filled.

Plans try to alleviate provider burden in a number of ways,

including notification, provider outreach, and automation:

• Notification. Plans and PBMs use a number of

methods to inform plan members and providers 

about their formularies and exceptions processes. 

In some cases, members receive a notice at the

pharmacy that details why the plan rejected their

prescription, lists alternative formulary drugs, and

notes the steps that the beneficiary should take if she

wants to challenge the plan’s decision. A recent court

decision (Hernandez v. Meadows) requires the Florida

Medicaid program to give beneficiaries written notice

at the pharmacy if their prescriptions are rejected.

Other states are considering similar requirements. 

(see text box).

• Provider outreach. Some plan interviewees reported

spending much of their time meeting with network

physicians and pharmacists. The goal was to explain

their formulary and exceptions procedures, address

provider complaints, and, ideally, convince providers

that the evidence-based processes used to maintain the

plan’s formulary provide added value to clinicians.

Some plans have experimented with giving physicians

hand-held electronic devices that are loaded with the

plan’s formulary, thus enabling easy access when

physicians write prescriptions.22

• Automation. Several interviewees told us that their

plan tried to make the prior authorization process as

seamless as possible. For example, pharmacists’

computer systems may have automatic edits to check

30 Monitoring the imp lementation of Part D
that a plan member has tried a preferred drug before

dispensing a nonpreferred drug to treat the same

condition. Members who tried the preferred drugs can

get the nonpreferred drug without a formal prior

authorization. (However, this system cannot work for

new plan members.)

If plans reject prior authorization requests, members can

appeal the decision through the plan’s general appeals

process. 

Appeals processes: Current practice 

and Part D

Under CMS regulations, beneficiaries may appeal many

aspects of the exceptions process. Appeals may be filed by

beneficiaries, their authorized representative, or their

prescribing physician, but the prescribing physician must

provide a supporting statement. Beneficiaries can appeal

the following:

• failure to cover a Part D drug,

• a negative decision concerning an exceptions request,

• a negative decision on a request for lowered cost

sharing for a drug,23 and

• failure to provide a coverage determination in a timely

manner.

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 31

Hernandez v. Meadows

I

n 2002, a coalition of advocacy groups filed suit

against the Florida Medicaid Agency for failure to

provide fair hearings and written notice to Medicaid

enrollees when denying them coverage of prescription

drugs. The plaintiffs claimed that the agency violated the

Social Security Act and constitutional guarantees of due

process, causing beneficiaries irreparable injury due to

erroneous denials of coverage for necessary medications.

The settlement agreement—approved May 14, 2004—

obligates Florida Medicaid to require posting of notices

in pharmacies (Figure 1-5) and to provide pharmacy

providers with informational pamphlets that they can

distribute to Medicaid recipients when Medicaid 

denies payment for a prescription. In addition to posting

notices in several languages within the pharmacy itself

and providing recipients with written information

explaining why Medicaid denied payment of a

prescription, the state must also provide an ombudsman

to help beneficiaries receive timely resolution of claim

payment rejections. If reasonable efforts to do so fail,

enrollees are entitled to a fair hearing. 

The settlement also protects beneficiaries by requiring

Medicaid to ensure payment for a temporary supply of

medication for three business days in the case of an

emergency or ongoing therapy. Additionally, if a

beneficiary requests a hearing, he or she is entitled to

payment for therapy from the date of the request until

the hearing. Finally, Florida Medicaid agreed to pay 

the pharmacy for supplying a multisource brand drug 

to the enrollee if the prescriber writes on the script that

the drug is medically necessary. The Hernandez v.

Meadows settlement has become a model standard 

of beneficiaries’ rights that advocates in other states 

are attempting to replicate. 

Source: NHeLP, National Health Law Program, 2004.

IMPORTANT NOTICE

TO MEDICAID RECIPIENTS 

If your pharmacist has told you that Medicaid, or your Medicaid HMO, 

will not cover your prescription today, they must give you a written notice 

(pamphlet) explaining the reason. The notice will advise you what steps 

you need to take to correct the problem.

If you do not get a notice, call 1-866-490-1901. If you do not 

receive a response, then call your local legal services/legal aid offi ce. 

Notice required by Hernandez

v. Meadows settlement

FIGURE

1-5
Plans will have to meet quicker timeframes for making

Part D coverage decisions than private plans typically

require, although many interviewees said that their plans

usually make decisions quickly. Plans must make initial

Medicare coverage determinations no later than 72 hours

after a member requests a determination and the physician

provides necessary documentation. After the plan receives

the request and necessary documentation, it must make 

an expedited coverage decision within 24 hours.

Currently, health plans and PBMs must meet various

requirements for treatment of appeals. Different standards

apply depending on the provider of the drug benefit and

the state in which the plan is located. In the course of our

interviews, plans frequently cited NCQA accreditation

criteria and state Medicaid agencies’ requirements. 

In addition, some states have mandated that all health

plans that operate within their borders do one or more 

of the following:

• define processes for urgent and nonurgent appeals, 

• set notification requirements, 

• determine timeframes for responding to appeals and

notifying members, and

• establish auditable records of appeals transactions. 

Some systems require plans to have an external 

appeals process, as well. 

Although all plan representatives with whom we talked

described an appeals process that applied to their drug

benefit, interviewees agreed that issues involving

prescription drugs rarely became the focus of external

appeals. One plan representative noted that he had not

seen a single case involving prescription drugs go to

external appeals in three years. One consumer advocate

commented that plan members rarely challenged plan

decisions on drugs because they did not know that they

could appeal. Another advocate suggested that patients

either got their drugs when they needed them or decided

that they could get along without them.

However, beneficiaries did appeal decisions on some 

types of drugs. For example, interviewees indicated that

members have appealed decisions involving injectable

drugs that physicians prescribed for off-label uses.

Additionally, beneficiaries sometimes appealed decisions

on psychiatric drugs such as atypical antipsychotics.

Most health plans had little or no experience with appeals

of cost-sharing requirements. One plan representative

noted that his plan sometimes decided, informally, to

reduce cost sharing for nonpreferred drugs when the plan

determined these drugs to be medically necessary. For

example, an interviewee from an integrated delivery

system with its own pharmacies reported that pharmacists

have the authority to lower copayments when a

beneficiary cannot afford the required copayment.

However, another interviewee reported that his plan 

never grants requests for lower copayments because 

drugs on the third tier were always considered covered—

but only for the higher copayment. Plans set premiums

based on projections of utilization across the different

cost-sharing tiers.

Beneficiary advocates expressed particular concern that

dual eligibles would not have the same appeal rights that

they have under Medicaid. Currently, Medicaid recipients

have the right to a pre-termination hearing before the

program can reduce or end ongoing drug treatment.

Medicaid programs must continue to provide the benefits

at issue until the dispute is resolved (Rosenbaum 2004).

No such right exists under Part D. As beneficiaries move

from Medicaid coverage to Part D coverage, they may

discover that the drug they have been taking for a chronic

condition is not listed on their new plan’s formulary.

Advocates are concerned that beneficiaries will delay or

stop treatment rather than initiate a formulary exception

request or appeal. 

CMS regulations require plans to develop a transition

policy for new members who are already taking a

particular drug that is not listed on their new plan’s

formulary. In guidelines issued on March 16 (CMS

2005b), CMS does not mandate any specific policies but

does suggest that plan sponsors consider a range of

strategies to address the needs of groups such as dual

eligibles and individuals who have chronic conditions.

One suggested strategy includes allowing a temporary

one-time refill of a past medication while allowing the

plan, the enrollee, and the physician to decide if a

beneficiary can switch to a formulary medication. The

transition supply could vary by drug, by individual

medical needs, or by an individual’s location (e.g., a 

long-term care facility). Although CMS had not issued

these guidelines at the time of our interviews, a number 

of interviewees suggested that their plans already have

informal processes in place to accommodate beneficiaries

who move from one plan to another. 

32 Monitoring the imp lementation of Part D
Part D issues related to exceptions 

and appeals

Our research suggests that a number of issues involving

the exceptions and appeals processes will likely arise

under the Medicare prescription drug benefit. Interviewees

identified the following issues:

• Will plans have the resources to deal quickly with a

potentially high volume of appeals? Plans may face a

higher volume of appeals than is currently the case.

For example, Part D regulations could cause more

beneficiaries to appeal cost-sharing tiers. In addition,

notification requirements that inform beneficiaries

about their appeals rights may also generate increased

activity. Lastly, expedited appeals would require a

decision within 24 hours, a faster turnaround time than

plans today commonly require. If expedited appeals

become a frequent occurrence, plans may face a

significant expense in managing the appeals and

exceptions process. 

• Will the benefit structure affect the plans’ ability to

use the exceptions process to steer utilization? One

interviewee pointed out the potential difficulties of

putting drugs on a nonpreferred third tier or using

prior authorization. Part D plan members will have 

to pay 100 percent of the cost sharing for spending

that falls below the deductible and above the initial

benefit limit (Figure 1-1, p. 5). Members and their

physicians may resent the additional burden of getting

a drug preauthorized when they will still have to pay

its full cost, albeit at the discounted price negotiated

by the plan. However, prior authorization decisions

will be particularly important to beneficiaries because

only spending for drugs covered by their plan will

count toward the benefit’s out-of-pocket limit.

• How will plans distinguish between drugs that

should be covered under Part B rather than Part D?

Several interviewees noted that many drugs covered

under Part B for some conditions or sites of care

would be considered Part D drugs in other situations.

For example, physicians prescribe oral antinausea

drugs to treat the side effects of chemotherapy, but

they also may prescribe these drugs for other cases of

extreme nausea. Part B would cover the drugs only for

the first situation. Although plans may use prior

authorization for all medications that might be Part B

drugs, interviewees suggest that this situation may be

a complex issue that cannot be easily resolved.

• Will CMS publicly report plan appeals and

grievances statistics? Regulations require that plans

notify beneficiaries of appeal processes. Beneficiary

advocates placed a high value on public disclosure 

of a drug plan’s appeals record. They suggest that 

this would be an important quality measure for

beneficiaries to use when choosing a plan. Our

interviewees expressed disagreement on this issue.

Some representatives of health plans and PBMs

agreed that public reporting would be valuable. 

Others suggested that differences in plan policies on

formulary management would make comparison of

overall statistics meaningless. Instead, they suggested

that the exceptions and appeals process should be

transparent to beneficiaries so that plan members and

physicians could evaluate the evidentiary standards

that plans use to make coverage decisions. Plans

would make public the conditions under which they

grant formulary exceptions and the evidence required

to meet these conditions.

CMS has announced its intention to examine all aspects of

formulary development and management to ensure that

plans do not discriminate against beneficiaries with highcost medical needs. The agency may scrutinize plan use of

tools such as prior authorization. In its review of plan

submissions, CMS will have to balance carefully the need

to ensure beneficiary access to necessary medications with

the plans’ ability to control unnecessary utilization. If plan

sponsors believe that they will not be able to use tools like

prior authorization to manage drug utilization, they may

charge higher premiums or be reluctant to participate in

the program. 

Looking forward: Electronic prescribing

and other areas of future research 

Members of our expert panel and other interviewees 

agreed that the diffusion of e-prescribing technology 

would improve many of the access, quality, and cost

issues we discuss in this chapter. Patients, physicians,

pharmacists, and drug plans would save time and money 

if physicians could determine a drug’s formulary status

and get necessary prior authorizations when they write

prescriptions. However, most interviewees agreed that

diffusion of the technology is still slow (although some

reported recent progress). Some physicians raised questions

about the technology’s cost and adaptability to the way in

which physicians practice. One physician commented that

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 33
the version of e-prescribing used by a partner in his practice

increased the time that his partner needed to write a

prescription and thus reduced his productivity. 

CMS issued a proposed rule (CMS 2005e) to promote the

diffusion of e-prescribing. The rule proposes preliminary

standards for electronic prescribing that could form the

basis of final uniform standards for the technology—

standards that would promote patient safety, quality of

care, efficiency, and cost savings in the delivery of 

care. MedPAC intends to monitor these efforts as 

they move forward.

In the coming months, plans will be submitting bids to

become PDPs or MA–PDs. By September 2005, CMS

should make available information about plan offerings,

including premiums, benefit designs, and formulary

systems. MedPAC intends to analyze this data and

describe its impact on enrollment in Part D plans.

Depending on the availability of data, we will evaluate

how the Medicare drug benefit meets the goal of ensuring

a quality benefit at an affordable cost in the future. 

34 Monitoring the imp lementation of Part D

Federal subsidies for the Part D drug benefit

The Medicare Prescription Drug, Improvement, and

Modernization Act of 2003 designed Part D so that

CMS would provide subsidies to serve three purposes:

• encourage beneficiary enrollment,

• encourage plan participation by reducing cost

uncertainty, and 

• reduce out-of-pocket liability for beneficiaries with

low incomes and limited assets. 

The forms of these subsidies are important because

without high enrollment and limitations on risk, private

entities might not want to offer a stand-alone drug plan. 

Few examples of stand-alone drug plans exist today

because beneficiaries, particularly those who have

chronic conditions, can predict their drug spending

fairly well. Enrollees would pick coverage that suits

their prescription drug needs, thus raising the risk of

adverse selection. Private plans might also be reluctant

to offer drug-only coverage because they could find it

difficult to predict growth in the use of new drug

therapies, and, therefore, hard to set premiums reliably. 

The Medicare program will provide a subsidy that

averages 74.5 percent of standard coverage for all 

types of beneficiaries. That average subsidy will 

take two forms:

• Direct subsidy—a capitated payment calculated 

as a share of the adjusted national average of plan

bids. Although no one can predict levels of

enrollment in Part D, in general, high direct

subsidies should lead to higher enrollment, 

which makes private entities more likely to offer 

a Medicare plan.

• Individual reinsurance—Medicare will subsidize

80 percent of drug spending above an enrollee’s

catastrophic threshold. Reinsurance acts as a form

of risk adjustment by providing greater federal

subsidies for the highest cost enrollees.

In addition, Medicare will establish symmetric risk

corridors separately for each plan to limit a plan’s

overall losses or profits. Under risk corridors, 

Medicare limits a plans’ potential losses (or gains) 

by financing some of the higher-than-expected costs 

(or recouping excessive profits). Also, plans that enroll

low-income beneficiaries will receive a fourth type 

of subsidy to cover some of these enrollees’ cost

sharing and premiums.

Note that although plans will get essentially the same

level of direct subsidy per enrollee (albeit modified by a

risk adjuster to reflect health status), the level of

subsidies granted through the other three mechanisms

could differ substantially from plan to plan. Subsidy

dollars will vary depending on the characteristics of

individuals that each plan enrolls (e.g., income, health

status, and supplemental coverage stats), as well as on

how each plan structures its risk corridors. Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 35

1 The term “true out of pocket” refers to a feature of Part D

which directs fewer federal subsidy dollars toward enrollees

who have supplemental coverage. Specifically, only certain

types of spending on behalf of the beneficiary count toward

the catastrophic threshold: the beneficiary’s own out-ofpocket spending; that of a family member or official charity;

supplemental drug coverage provided through qualifying

state pharmacy assistance programs or Part D’s low-income

subsidies; and, under CMS’s demonstration authority,

supplemental drug coverage paid for with MA rebate dollars.

2 These threshold amounts in the standard benefit would

increase each year by CMS’s estimate of the annual change

in drug spending per person. For example, CMS currently

projects that by 2010, the standard benefit’s deductible

would be $331, the initial benefit limit would reach $2,980

rather than $2,250, and the catastrophic threshold would be

$4,767 rather than $3,600 (Boards of Trustees 2005).

3 MA–PDs may use rebate dollars—that is, a portion of the

difference between CMS’s payment rates and a plan’s bid 

for providing basic services covered by Medicare Parts A

and B—to enhance the Part D benefit. Chapter 2 of this

report provides further information about rebate dollars.

4 PBMs do not typically report members’ spending on

noncovered drugs, for which members pay fully out of

pocket.

5 A few PBMs have received accreditation from quality

assurance organizations for aspects of their business, such 

as specific disease management programs (Booz Allen

Hamilton 2004).

6 When beneficiaries sign up for a Medicare Part D plan, they

are required to report whether they also have prescription

drug coverage through a third party.

7 In its Part D regulations, CMS notes that these surveys will

likely be adapted from the Consumer Assessment of Health

Plans Survey (CAHPS).

8 Under certain circumstances, individuals can switch plans

more than once per year, such as when they move out of the

area or when their plan discontinues offering the benefit.

9 CMS officials have commented that it is “highly unlikely”

that CMS will need to use a fallback plan in the initial

operation of Part D. 

10 Some exceptions exist. Under employer waivers, for

example, a PDP could have a separate risk pool and premium

for the retirees of a specific employer. 

11 If a region does not have at least one MA–PD and one

PDP—or two stand-alone PDPs—available, CMS must

contract with a fallback plan to offer Part D. MA–PDs and

PDPs are known as risk plans because they will bear

insurance risk on enrollees’ benefit spending. Fallback plans

will not bear insurance risk. 

12 Two important household surveys that capture prescription

drug spending are the Medical Expenditure Panel Survey

(MEPS) and the Medicare Current Beneficiary Survey

(MCBS). MEPS includes the noninstitutionalized U.S.

population; it has fewer respondents who are Medicare

beneficiaries than the MCBS. MCBS was specifically

designed to represent the wide variety of individuals who

make up the Medicare population. Household surveys are

subject to the problem of recall bias—the notion that

individuals may not recall accurately the number and type 

of prescriptions they got filled. Additionally, household

surveys typically do not include information about rebates

from pharmaceutical manufacturers—these rebates can 

lower prices for prescription drugs.

13 CMS uses such data from the Census Bureau and private

survey organizations such as IMS Health to help it estimate

nationwide prescription drug spending in the national health

accounts. Other private companies, such as Verispan,

similarly collect data from retail pharmacies and other

sources. 

14 According to CMS’s 45-day notice to plans, the agency used

drug claims for a sample of federal retirees and spouses who

also have Medicare coverage to build initial risk adjusters for

nondisabled beneficiaries and those who are not dual

eligibles. For the latter two groups, CMS used Medicaid

claims data (CMS 2005a).

15 CMS initially developed a model that predicts a person’s

total drug spending (plan benefit spending plus cost sharing),

and then modified the model to predict Part D liability alone.

This modification is particularly important given the peculiar

structure of the standard Part D benefit, with a large range of

spending for which the enrollee must pay 100 percent

coinsurance. That coverage gap substantially reduces the

amount of insurance risk that plans must bear. On average,

benefit spending made up about 40 percent of total spending. 

Endnotes
36 Monitoring the imp lementation of Part D

16 Each region’s index is the average of predicted prescription

drug spending divided by the predicted national average. 

17 CMS will randomly assign those beneficiaries who are

dually eligible for Medicare and Medicaid to plans beginning

in October, although they will be able to switch plans at any

time if their assigned plan does not meet their needs. 

18 Low-income beneficiaries can still enroll for transitional

assistance, but their credit is prorated depending on their date

of enrollment.

19 SPAPs provide drug coverage or assistance to low-income

elderly or persons with disabilities who do not qualify for

Medicaid. As of March 2005, 39 states had established or

authorized one of these programs

(www.ncsl.org/programs/health/drugaid.htm). 

20 As of March 4, 2005, enrollment had reached 6.3 million,

with about 1.8 million beneficiaries receiving transitional

assistance (CMS 2005d). 

21 A closed formulary is defined as a list of specific drugs

limited to only some of the commercially available products

in each therapeutic class. An open formulary is defined as a

comprehensive listing of medications typically including

almost every commercially available product in each

therapeutic class. A tiered or incentive-based formulary

contains different cost sharing for preferred and nonpreferred

brand-name drugs, as well as generic drugs, thereby giving

patients a financial incentive to request preferred or generic

medications. Most plans currently have open-tiered

formularies, but we interviewed representatives from a

number of organizations that also have closed formularies.

For a more in-depth look at these issues, see MedPAC’s

2004 Report to the Congress.

22 Health plans that have closed physician and pharmacy

networks experience much less difficulty informing

providers about the formulary. Physicians have only one

formulary to keep in mind when they are writing

prescriptions. Additionally, providers participate in

developing the formulary and may have greater confidence

in it. In some cases, these physicians may be able to

prescribe nonformulary drugs without going through a prior

authorization process.

23 Under the final rule, beneficiaries may appeal to reduce 

cost-sharing requirements for a nonpreferred branded drug 

to the level of cost sharing for a preferred branded drug.

Beneficiaries may not appeal other cost-sharing

requirements.
Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 37

Academy of Managed Care Pharmacy. 2004. Guiding principles

for effective electronic messaging. AMCP. http://www.amcp.org/

data/nav_content/e%5Fmessaging%5Ffinal%2Epdf.

Baicker, K. and A. Chandra. 2004. Medicare spending, the

physician workforce, and beneficiaries’ quality of care. 

Health Affairs Web Exclusives www.healthaffairs.org (April 7):

W4-148–W4-197.

Beers, M. H. 1997. Explicit criteria for determining potentially

inappropriate medication use by the elderly. An update. Archives

of Internal Medicine 157, no. 14: 1531–1536.

Berman, C. 2005. Targeted removal of barriers to care.

Presentation at the Pharmacy Benefit Management Institute 

2005 Prescription Drug Utilization Management Conference. 

March 30–April 1.

Boards of Trustees, Federal Hospital Insurance and Federal

Supplementary Medical Insurance Trust Funds. 2005. 2005

Annual Report of the Boards of Trustees of the Federal Hospital

Insurance and Federal Supplementary Medical Insurance Trust

Funds. Washington, DC: Boards of Trustees.

Booz Allen Hamilton. 2004. Task C–Drug utilization

management and quality assurance best practices and standards.

PBS–500–02–0028. Rockville, MD: Centers for Medicare &

Medicaid Services, Department of Health and Human Services.

Bryant, J., J. Corea, and A. Sydlaske. 2004. Assessment of

beneficiary savings in the Medicare drug discount card program.

Washington, DC: The Lewin Group. August 12.

Centers for Medicare & Medicaid Services, Office of Public

Affairs, Department of Health and Human Services. 2004.

Medicare modernization benefits in the first year. 

Report no. 202–690–6145. http://www.cms.hhs.gov/media

/press/release.asp?Counter=1276. Baltimore, MD: CMS.

Centers for Medicare & Medicaid Services, Department of Health

and Human Services. 2005a. 45-day notice for 2006 MA rates.

Baltimore: CMS. http://www.cms.hhs.gov/healthplans/

rates/2006/45-day.pdf. 

Centers for Medicare & Medicaid Services, Department of Health

and Human Services. 2005b. Information for Part D sponsors on

requirements for a transition process. Baltimore: CMS.

http://www.cms.hhs.gov/pdps/transition_process.pdf.

Centers for Medicare & Medicaid Services, Department of Health

and Human Services. 2005c. Medicare Part D reporting

requirements. Baltimore, MD: CMS. http://www.cms.hhs.gov/

pdps/Rptreq4cmnts_032305.pdf.

Centers for Medicare & Medicaid Services, Department of Health

and Human Services. 2005d. Phone conversation with Peter

Ashkenaz, March 23.

Centers for Medicare & Medicaid Services, Department of Health

and Human Services. 2005e. Medicare program; e-prescribing

and the prescription drug program. Federal Register 70, no. 23

(February 4): 6256–6274.

Centers for Medicare & Medicaid Services, Department of Health

and Human Services. 2005f. Instructions: Requirements for

submitting prescription drug event data. Baltimore: CMS.

http://www.cms.hhs.gov/pdps/FINALPAPER041205.pdf.

Centers for Medicare & Medicaid Services, Department of Health

and Human Services. 2005g. Medicare program; Medicare

prescription drug benefit. Federal Register 70, no. 18 (January

28): 4193–4742.

Centers for Medicare & Medicaid Services, Department of Health

and Human Services. 2005h. MA and PDP regions. Baltimore:

CMS. http://www.cms.hhs.gov/medicareform/mmaregions/

pdpmap/pdpmap.asp.

Chawla, A. J., M. R. Hatzmann, and R. L. Long. 2001.

Developing performance measures for prescription drug

management. Health Care Financing Review 22, no. 3 

(Spring): 71–84.

Cox, E., R. Henderson, and B. Motheral. 2004. Health plan

member experience with point-of-service prescription step

therapy. Journal of Managed Care Pharmacy 10, no. 4

(July/August): 291–298.

Department of Health and Human Services. 2000. Report to the

President: Prescription drug coverage, spending, utilization, and

prices. Washington, DC: HHS. http://aspe.hhs.gov/health/

reports/drugstudy/.

Express Scripts, Inc. 2002. Geographic variation in the use of

health care. No. 01–1319. St. Louis, MO: Express Scripts.

http://www.express-scripts.com/ourcompany/news/

outcomesresearch/prescriptiondrugatlas/pdaBackground.pdf.

Fick, D. M., J. W. Cooper, W. E. Wade, et al. 2003. Updating the

Beers criteria for potentially inappropriate medication use in older

adults. Archives of Internal Medicine 163, no. 22 (December 8):

2716–2724.

Fox, K. 2005. Lessons from implementation of Medicare Rx

discount cards in state pharmacy assistance programs and

implications for Part D. Powerpoint presentation at State

Coverage Initiatives National Meeting, February 4, in

References
Washington, DC. http://www.statecoverage.net/0205/fox.pdf.

Goulding, M. R. 2004. Inappropriate medication prescribing for

elderly ambulatory care patients. Archives of Internal Medicine

164, no. 3 (February 9): 305–312.

Government Accountability Office. 2005. Medicaid drug rebate

program: Inadequate oversight raises concerns about rebates

paid to states. GAO–05–102. Washington, DC: GAO.

http://www.gao.gov/cgi-bin/getrpt?GAO-05-102. 

Government Accountability Office. 2004. Medicare: Accuracy of

response from the 1-800-MEDICARE help line should be

improved. GAO–05–130. Washington, DC: GAO.

http://www.gao.gov/cgi-bin/getrpt?GAO-05-130.

Health Policy Alternatives, Inc. 2003. Pharmacy benefit

managers (PBMs): Tools for managing drug benefit costs,

quality, and safety. Washington, DC: Health Policy Alternatives.

Medicare Payment Advisory Commission. 2004. Report to the

Congress: New approaches in Medicare. Washington, DC:

MedPAC.

Mercer Human Resource Consulting. 2003a. Navigating the

pharmacy benefits marketplace. Washington, DC: California

HealthCare Foundation.

Mercer Human Resource Consulting. 2003b. Prescription drug

benefit plans: A buyer’s guide. Washington, DC: California

HealthCare Foundation.

National Committee for Quality Assurance. 2005. Draft

document for HEDIS 2006 public comment. Washington, DC:

NCQA. http://www.ncqa.org. 

National Health Law Program. 2004. Hernandez v. Meadows

settlement agreement materials. NHeLP.

http://www.healthlaw.org/pubs/hernandez/casematerials.html. 

Rosenbaum, S. 2004. Grievance and appeals procedures: An

analysis of the MMA and proposed regulations. Washington, DC:

Kaiser Family Foundation. September.

Rutgers Center for State Health Policy. 2004. States’ issues and

concerns with implementation of Medicare Part D prescription

drug coverage. Summary of an audioconference with states.

http://www.statecoverage.net/pdf/medicarepartd.pdf.

Sager, A., and D. Socolar. 2004. Poorer, sicker states face

heavier drug cost burdens. Boston: Health Reform Program,

Boston University School of Public Health.

http://dcc2.bumc.bu.edu/hs/Poorer_Sicker_States_Face_Heavier_

Drug_Cost_Burdens_14_July_2004.pdf.

Shih, Y., and B. Sleath. 2004. Health care provider knowledge of

drug formulary status in ambulatory care settings. American

Journal of Health-System Pharmacists 61, no. 24: 2663.

U.S. Senate and House. 2003. Medicare Prescription Drug,

Improvement, and Modernization Act of 2003. 108th Cong., 1st

sess., H.R. 1.

Wennberg, D., and Wennberg, J. 2000. Dartmouth Atlas of

Health Care in Michigan. Detroit: The Trustees of Dartmouth

College and Blue Cross Blue Shield Association.

http://www.bcbsm.com/atlas/foreword.shtml.

38 Monitoring the imp lementation of Part D
Medicare Advantage payment

areas and risk adjustment

CHAPTER 2
RECOMMENDATIONS

2A The Congress should establish payment areas for Medicare Advantage local plans that

have the following characteristics:

• Among counties in metropolitan statistical areas, payment areas should be collections 

of counties that are located in the same state and the same metropolitan statistical area.

• Among counties outside metropolitan statistical areas, payment areas should be 

collections of counties in the same state that are accurate reflections of health care 

market areas, such as health service areas.

COMMISSIONER VOTES: YES 16 • NO 0 • NOT VOTING 0 • ABSENT 1

 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2B The Secretary should update health service areas before using them as payment areas in 

the Medicare Advantage program. In addition, the Secretary should make periodic updates

to health service areas to reflect changes in health care market areas that occur over time.

COMMISSIONER VOTES: YES 16 • NO 0 • NOT VOTING 0 • ABSENT 1
Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 41

edPAC is mandated to identify the appropriate

payment area for Medicare Advantage (MA) 

local plans and assess the new risk-adjustment

system in the MA program. The current county

definition of payment areas presents two problems. First, some counties

have too few beneficiaries to obtain stable adjusted average per capita

costs. Second, adjacent counties often have very different payment rates.

Plans may offer more limited benefits in the counties with the lower rates

or avoid them altogether. Our recommendation addresses these problems by collecting counties into larger

groups. Among urban counties, payment areas should be counties that are located in the same metropolitan 

statistical area. Among rural counties, payment areas should be collections of counties that are accurate 

reflections of health care market areas. Our assessment of the new risk-adjustment system indicates that it 

predicts beneficiaries’ costs much better than a “demographic” system that CMS has used for a number of years. 

2

In this chapter

• AAPCCs vary widely

• How can Medicare improve

payment areas for MA local

plans?

• Payment area 

recommendations

• How accurately does the 

CMS–HCC model reflect 

cost differences?

CHAPTER

M

Medicare Advantage

payment areas and

risk adjustment
The Medicare Prescription Drug, Improvement, and

Modernization Act of 2003 (MMA) directs MedPAC to

study three issues related to the payment system in the

Medicare Advantage (MA) program (see text box for bill

language):

• The factors underlying geographic variation in

adjusted average per capita costs (AAPCCs),

including differences in input prices, service use, and

practice patterns;

• The appropriate geographic area for payment of MA

local plans; and

• The accuracy of the CMS–hierarchical condition

category (CMS–HCC) risk-adjustment model in terms

of how well it reflects differences in costs of providing

care to different groups of beneficiaries.

AAPCCs are five-year moving averages of per beneficiary

spending at the county level by fee-for-service (FFS)

Medicare. CMS adjusts AAPCCs for county differences in

FFS beneficiaries’ health status. In the Medicare risk

program that preceded Medicare Advantage and

Medicare+Choice (M+C), the county payment rates that

served as the base rates for plan payments equaled 95

percent of the AAPCCs.

The direct link between AAPCCs and payments created

perceptions of geographic inequity. Plans were more likely

to serve counties with high AAPCCs and typically offered

more comprehensive benefits. Many policymakers viewed

the geographic differences in benefits and availability of

plans as inequitable (MedPAC 2001).

In response to the variation in plan benefits and

availability, the Balanced Budget Act of 1997 (BBA)

created the M+C program and reduced the link between

AAPCCs and payments. Under the BBA, county rates

were the highest of three possibilities or prongs:

• a floor rate,

• a blend of local and national rates, or

• a minimum update from the previous year.

Under this new payment system, plan payments often

increased more slowly than plan costs, causing many plans

to leave the M+C program or reduce benefits. In response,

the MMA created the MA program and reestablished a

stronger link between payments and AAPCCs by making

county rates in 2004 the maximum of four prongs: the

three from the BBA plus the AAPCCs. In subsequent

years, CMS will update county rates by 2 percent or the

national average growth in FFS spending, whichever is

42 Medicare Advantage p ayment areas and risk adjustment

Medicare Prescription Drug, Improvement, and Modernization Act, 

Title II, Sec. 211(f)

(f) MedPAC study of AAPCC.

(1) Study. The Medicare Payment Advisory

Commission shall conduct a study that assesses the

method used for determining the adjusted average

per capita cost (AAPCC) under section 1876(a)(4)

of the Social Security Act (42 U.S.C.

1395mm(a)(4)) as applied under section

1853(c)(1)(A) of such act (as amended by

subsection (a)). Such study shall include an

examination of:

(A) the bases for variation in such costs

between different areas, including differences

in input prices, utilization, and practice

patterns.

(B) the appropriate geographic area for

payment of MA local plans under the Medicare

Advantage program under part C of title XVIII

of such Act; and

(C) the accuracy of risk adjustment methods in

reflecting differences in costs of providing care

to different groups of beneficiaries served

under such program.

(2) Report. Not later than 18 months after the date

of the enactment of this Act, the Commission shall

submit to Congress a report on the study conducted

under paragraph (1). larger. However, the MMA also requires CMS to

recalculate AAPCCs at least every three years. For

counties in which the recalculated AAPCCs exceed the

updated amounts, CMS will use the recalculated AAPCCs

as the county rates.

In 2004 and 2005, CMS used the county rates as the base

rates for paying MA plans. In 2006 and subsequent years,

CMS will use county rates to create benchmarks against

which plans will bid. The benchmark for each plan will be

a weighted average of the county rates for the counties in

the plan’s service area; the weights will be the projected

enrollment from the counties in the plan’s service area.

A plan that bids below its benchmark will have a base rate

equal to its bid, adjusted in each county in its service area

to reflect differences in the county rates. In addition, the

plan will receive 75 percent of the difference between its

bid and its benchmark, which the plan must return to its

enrollees in the form of additional benefits, reduced cost

sharing, or lower premiums. The federal government will

retain the remaining 25 percent. Chapter 3 of this report

provides more detail on the bidding process. A plan that

bids above its benchmark will have a base rate equal to its

benchmark, adjusted in each county in its service area to

reflect differences in the county rates. The plan’s enrollees

will pay a premium equal to the difference between its bid

and its benchmark.

Medicare’s use of county payment rates to create

benchmarks reflects the fact that counties serve as the

payment area for MA local plans. These plans are “local”

in that their service areas can be as small as a single

county. This contrasts with regional plans that will begin

service in 2006. Regional plans must serve entire regions,

the smallest of which are entire states.

MA local plans receive capitated payments for each

enrollee. Each payment is the product of two factors: a

base payment rate (described above) and a beneficiarylevel risk score that reflects the expected costliness of a

beneficiary relative to the national average. Risk scores,

which CMS obtains from a method of risk adjustment,

have the purpose of adjusting plan payments so that

Medicare pays plans appropriately based on their

enrollees’ risk profiles. If risk adjustment does not

function properly, payments will not accurately reflect 

the risk profiles of plans’ enrollees. Some plans will be

overpaid while others will be underpaid, depending on

their enrollees’ risk profiles. This can lead to competitive

advantages for plans with favorable risks. Further,

inaccurate accounting for risk can lead Medicare to pay

more or less than intended to the MA program.

The Medicare risk program’s risk-adjustment model 

used administrative data including beneficiaries’ age, sex,

and other demographic features as well as some program

features. Research shows that this “demographic” 

model does not effectively account for differences in

beneficiaries’ expected costliness to the Medicare

program. Consequently, Medicare paid more for MA

enrollees who were in good health and less for those who

were in poor health than for similar FFS beneficiaries.

The BBA required the Secretary to improve the riskadjustment system. As a first step, CMS began using the

principal inpatient diagnostic cost group (PIP–DCG)

model in 2000. The PIP–DCG measures beneficiaries’

health status using demographic information and principal

diagnoses from hospital inpatient stays in a defined prior

12-month period.

The Medicare, Medicaid, and SCHIP Benefits

Improvement and Protection Act of 2000 mandated that in

2004, Medicare base its risk adjustment system on data

from hospital inpatient and ambulatory settings. CMS has

developed this model—the CMS–HCC—and began using

it in 2004. By law, CMS must phase in the CMS–HCC, so

the agency currently uses two systems to risk adjust

payments to MA plans: The CMS–HCC adjusts 50 percent

of each payment, and the demographic system adjusts the

remaining 50 percent. The percentage of each payment

that the CMS–HCC will adjust will increase to 75 percent

in 2006 and 100 percent in 2007. CMS will introduce a

new version of the CMS–HCC in 2007 that will include

more diseases than the current version.

AAPCCs vary widely

In MedPAC’s June 2003 report, we examined an issue

similar to variation in AAPCCs: state-level variation in

FFS spending per beneficiary (MedPAC 2003). We sought

to identify how much of the variation in FFS spending by

state we can attribute to:

• the price of inputs such as wages and office rents;

• special payments received by some hospitals,

including graduate medical education (GME)

payments, indirect medical education (IME)

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 43
payments, and disproportionate share (DSH)

payments to hospitals that provide indigent care; and 

• beneficiaries’ health status.

We calculated measures of variation among states before

and after we adjusted for these factors.1 We found that

adjusting FFS spending for geographic differences in these

factors reduces the variation by nearly 40 percent.

In this study, we use largely the same method to analyze

variation, with three differences: a different geographic

unit (counties), a slightly different variable (AAPCCs),

and we did not identify variation due to differences in

beneficiaries’ health because CMS adjusts AAPCCs for

health already (see text box). Without the need to adjust

for differences in health, our analysis identified variation

in AAPCCs attributable to geographic differences in the

price of inputs and IME, GME, and DSH payments.

Adjusting for differences in the price of inputs and in IME,

GME, and DSH payments reduces the variation in

AAPCCs by about 14 to 17 percent, depending on the

measure (Table 2-1).2 We attribute the variation that

remains after we adjusted AAPCCs for these factors to

providers’ practice patterns, beneficiaries’ preferences for

care, and the mix of providers.

This remaining variation largely reflects differences in

service use. These differences are not related to quality. In

fact, measures of quality tend to be higher in low-use areas

(Fisher et al. 2003, MedPAC 2003).

Even though AAPCCs are strongly related to per

beneficiary FFS spending, the proportion of the variation

in county-level AAPCCs for which we have accounted is

much smaller than the proportion of variation in state-level

per beneficiary FFS spending for which we accounted in

MedPAC’s June 2003 Report to the Congress. This

discrepancy reflects the fact that CMS already adjusts

AAPCCs for differences in beneficiaries’ health. We

analyzed county-level per beneficiary spending and

attributed about 40 percent of the variation to the

combination of health, input prices, and IME, GME, and

DSH payments, similar to our findings for state-level per

beneficiary spending.

How can Medicare improve payment

areas for MA local plans?

We have identified two problems in using counties as

payment areas for MA local plans. First, many counties

have small Medicare populations. Among these counties,

unusually high or low health care use by just a few

beneficiaries can cause substantial annual changes in

AAPCCs, which are based on moving averages of per

beneficiary spending in FFS Medicare. For example, we

estimate that the AAPCC for White Pine County, Nevada

(which has 1,300 FFS beneficiaries) increased by 12

percent from 2001 to 2002.

Large annual changes in AAPCCs become an issue when

CMS makes annual updates to county payment rates. For

example, if CMS recalculates AAPCCs using data from a

year in which a county experienced unusually large FFS

spending, the county could have a county rate much higher

than its “true” AAPCC. CMS could carry forward that

erroneously high rate through the update mechanism that

increases county rates by the larger of 2 percent or the

percentage increase in the national average FFS spending.

A second problem that counties present is that adjacent

counties often have very different AAPCCs. When this

occurs, plans tend to offer more limited benefits in the

county with the lower AAPCC—or to avoid that county

altogether (MedPAC 2001).

44 Medicare Advantage p ayment areas and risk adjustment

Differences in price of inputs 

and special payments to hospitals

account for about 15 percent of 

variation in AAPCCs

Measure of variation

Average of

Standard Coefficient absolute

AAPCC deviation of variation difference

Adjusted for health 76.2 14.4 60.7

Adjusted for health; input 65.8 12.3 50.1

prices; and IME, GME,

and DSH payments

Percent change 13.6% 14.4% 17.4%

Note: AAPCC (adjusted average per capita cost), IME (indirect medical 

education), GME (graduate medical education), DSH (disproportionate 

share). The measures of variation are weighted by number of beneficiaries

in each county.

Source: MedPAC analysis of county-level fee-for-service spending and other data 

from CMS.

TABLE

2-1
These two problems are fairly easy to solve. Any payment

area definition that groups counties into larger geographic

units would increase the number of Medicare beneficiaries

within payment areas, making AAPCCs more stable over

time.3 In addition, grouping would reduce the frequency of

large differences in AAPCCs among adjacent counties.

Although plans often create service areas that consist of

clusters of contiguous counties, these clusters do not

address the problems presented by the county definition of

payment areas. Instead, payment areas should be defined

groups of counties and plans should, in general, be

required to cover the entire payment area. The Secretary

could make exceptions in situations in which plans have

difficulty creating a provider network throughout a

payment area.

Developing an appropriate payment area involves more

than simply grouping counties, however. When we

consider alternative payment areas, we must be attentive

to two issues:

• Although we advocate larger payment areas, they

must not be so large that the cost of serving

beneficiaries would vary widely within payment areas.

Indeed, some counties in the western United States

cover very large areas already.

• Payment areas should closely match the market areas

that plans serve.

If a payment area definition fails to address either of these

issues, plans may find that their payments exceed their

costs in some parts of a payment area and fall short of

their costs in other parts. Plans would have an incentive to

serve the parts of the payment area in which they are

profitable and avoid the parts in which they are not.

However, if Medicare requires plans to serve the entire

payment area they could not act on that incentive. In that

situation, the potential for financial losses in some parts of

a payment area may cause plans to avoid the payment area

altogether.

Alternatives to the county definition of

payment areas

In response to the problems presented by counties, we

have developed and evaluated three alternative definitions

of payment areas, all using counties as the building block:

• Within each state, MSAs for urban counties and

statewide rural areas for rural counties.4 We grouped

urban counties into MSAs. If an entire MSA lies

within the boundaries of a single state, the MSA

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 45

Method for measuring variation in adjusted average per capita costs

We estimated an adjusted average per capita

cost (AAPCC) for each county using data on

Part A and Part B spending from 1998

through 2002. We calculated per beneficiary Part A and

Part B amounts in each county for each of those years.

We then calculated five-year averages of the Part A and

Part B amounts and added those results to create a per

beneficiary FFS spending amount for each county.

CMS standardizes AAPCCs using beneficiaries’ risk

scores from the CMS–hierarchical condition category

risk-adjustment model. To be consistent with CMS, we

divided each county’s per beneficiary FFS spending by

the average risk score for FFS beneficiaries living in

that county. The end result of this method is the

AAPCCs that we used to analyze variation among

counties.

In our measures of variation, we weight each county by

its Medicare population. The result is we weight

beneficiaries— not counties—equally. Without

weighting, beneficiaries in less populous counties

would have more influence on the variation than those

in more populous counties.

Variation in the price of inputs to care has an important

effect on variation in AAPCCs. The Medicare program

uses hospital wage indexes (HWIs) and three

geographic practice cost indexes (GPCIs) to adjust

provider payments for geographic differences in input

prices. CMS uses the three GPCIs to create geographic

adjustment factors (GAFs) that are weighted averages

of the GPCIs. We used the HWIs and GAFs to

determine the effect that differences in input prices have

on the variation in AAPCCs. would serve as a single payment area. But if an MSA

crosses state borders, the portion of the MSA in each

state would serve as a distinct payment area. Within

each state, we grouped all rural counties into a single

statewide rural area that would serve as a distinct

payment area. The first diagram in Figure 2-1

illustrates how the MSA/statewide rural area

definition would look in southern Texas around the

Corpus Christi, Brownsville, McAllen, and Laredo

MSAs. The counties with patterns are located in

MSAs, and the unshaded counties are part of the

statewide rural area of Texas.

• Health service areas (HSAs) for urban and rural

counties. We grouped urban and rural counties into

HSAs as defined by Makuc et al. (1991) (see text box

for description). If an HSA lies within the boundaries

of a single state, the HSA would serve as one payment

area. But if an HSA crosses state borders, the portion

of the HSA in each state would serve as a distinct

payment area. The second diagram in Figure 2-1

illustrates how the HSA definition would look in the

same part of southern Texas shown in the first

diagram.

• MSAs for urban counties and HSAs for rural

counties. This definition is a hybrid of the other two

alternatives. We grouped urban counties into MSAs

and rural counties into HSAs. The third diagram in

Figure 2-1 illustrates how the MSA/HSA definition

would look around the same part of southern Texas

shown in the first two diagrams. The counties with

patterns are located in MSAs, and the gray-shaded

counties are located in HSAs.

We chose to treat MSAs and HSAs that cross state borders

as more than one payment area because plans typically

face different laws, rules, and guidelines in different states.

We identified 20 MSAs that cross state borders and have

at least one county served by one or more coordinated care

plans that participate in Medicare. In only six of these

MSAs did plans consistently cross state borders and serve

all the states covered by the MSA. In the other 14 MSAs,

most or all plans that serve an MSA did not serve all states

of that MSA.

In addition to the three alternatives discussed above, we

also considered using hospital referral regions (HRRs) as 

a payment area definition (Wennberg and Cooper 1999).

HRRs have an attractive attribute in that they represent

health care market areas for tertiary medical care.

Nevertheless, we chose not to use them for two reasons.

46 Medicare Advantage p ayment areas and risk adjustment

Three definitions of payment areas, southern Texas

FIGURE

2-1

Note: MSA (metropolitan statistical area), HSA (health service area). If an MSA or HSA is divided by state borders, the part in each state is a distinct payment area. 

 Statewide rural areas are counties in the same state lying outside MSAs. The counties with patterns represent MSAs. The gray-shaded areas represent HSAs. 

 The counties without patterns, in the first diagram, are part of the statewide rural area of Texas.

Source: MedPAC analysis of metropolitan statistical areas defined by the Office of Management and Budget and health service areas defined by Makuc et al. 1991. 

MSA/Statewide

rural area

HSA MSA/HSA

Urban counties in MSAs

Rural counties in HSAs
First, some are very large, covering more than half the

area of large states such as New Mexico and Kansas. 

In these circumstances, we are concerned about large

variations in cost of care within payment areas. Second,

we are concerned that some HRRs—such as

Albuquerque—include both urban areas and large rural

areas, yet other HRRs—such as Miami—are strictly

urban. Plans already behave differently in different

payment areas, offering comprehensive benefits in some

areas, while offering more limited benefits in other areas

or avoiding them altogether. The lack of homogeneity

among urban payment areas that would be caused by

HRRs could exacerbate those differences.

Using larger payment areas reduces

annual changes and large differences

between adjacent counties

We use the MSA/HSA definition of payment areas as an

illustrative example in a statistical analysis that

demonstrates the advantages of payment areas that are

larger than counties. We estimated AAPCCs from 2001

and 2002 that are based on four-year moving averages of

per capita spending by FFS Medicare, removing the effect

of increases over time in national average per capita FFS

spending.6 We then compared the 2001 and 2002

AAPCCs.

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 47

Defining health service areas

The health service areas (HSAs) we used in our

analysis consist of sets of one or more counties

in which most of the short-term hospital care

received by beneficiaries who live in an HSA occurs in

hospitals that are in the same HSA. Very little shortterm care occurs in hospitals outside the HSA.

A study by Makuc et al. (1991) defines the HSAs. Their

method for grouping counties has the following

features:

• They predetermined that HSAs would number

about 800.5

• In the initial step, the number of groups equaled the

number of counties (approximately 3,100).

• In the second step, they combined the two groups

(counties) with the greatest “flow” of short-term

hospital care among Medicare beneficiaries. They

defined flow as the proportion of all hospital stays

among beneficiaries in one group that occur in

hospitals in another group.

• In each subsequent step, they combined the two

groups with the greatest flow of short-term hospital

care.

• They continued combining groups until they

obtained the predetermined number of HSAs. 

Note: AAPCC (adjusted average per capita cost). Larger payment areas are a 

 combination of metropolitan statistical areas (MSAs) for urban counties and 

 health service areas (HSAs) for rural counties. If an MSA or HSA is divided by 

 state borders, the part in each state is a distinct payment area. The results reflect 

 absolute values of the percent change in AAPCCs from 2001 to 2002.

Source: MedPAC analysis of county-level fee-for-service spending and other data 

 from CMS. Percent of 

all counties

50

40

30

20

10

0

0–1 >5 1–2 2–3 3–4 4–5

County alone Larger payment area

Percent change in counties

AAPCCs from 2001 to 2002

Larger payment areas result

in more stable AAPCCs

FIGURE

2-2
We found that using a larger payment area would produce

more stable AAPCCs. The average change in AAPCCs

from 2001 to 2002 under the MSA/HSA definition of

payment areas is 1.4 percent, compared with 2.1 percent

for the county definition. Also, larger payment areas have

a less dispersed distribution of annual changes. Under the

MSA/HSA definition, 45 percent of counties have an

annual change of less than 1 percent, and 2 percent of

counties have an annual change of more than 5 percent.

Under the county definition, 35 percent of counties have

an annual change of less than 1 percent, and 7 percent of

counties have an annual change of more than 5 percent

(Figure 2-2, p. 47).

We also found that large differences in AAPCCs between

adjacent counties occur much less frequently under the

larger payment areas. Under the MSA/HSA definition, 14

percent of all beneficiaries live in counties that have an

adjacent county with an AAPCC that is at least 15 percent

higher, compared to 21 percent of beneficiaries under the

county definition (Figure 2-3).

One consequence of larger payment areas is that they

would reduce AAPCCs for some counties and increase

them for others. We estimate that 43 percent of

beneficiaries live in counties that would have lower

AAPCCs under the larger payment area, 37 percent live 

in counties that would have higher AAPCCs, and 20

percent live in counties that would have the same AAPCC.

Evaluating alternative payment area

definitions

The statistical analysis in the previous section showed that

larger payment areas have clear advantages and are

preferable to the county definition. In this section, we

address the question: Given that larger payment areas are

better than the county definition, what is the best method

for grouping counties to obtain the best payment areas?

48 Medicare Advantage p ayment areas and risk adjustment

Note: AAPCC (adjusted average per capita cost). Larger payment areas are a 

 combination of metropolitan statistical areas (MSAs) for urban counties and 

 health service areas (HSAs) for rural counties. If an MSA or HSA is divided by 

 state borders, the part in each state is a distinct payment area.

Source: MedPAC analysis of county-level fee-for-service spending and other data 

 from CMS. Percent of benefici

aries

70

60

50

40

30

20

10

0

15% higher 10% higher 5% higher

County alone Larger payment areas

Adjacent county has AAPCC more than:

Larger payment areas 

smooth differences in 

AAPCCs among counties

FIGURE

2-3

Note: AAPCC (adjusted average per capita cost), MSA (metropolitan statistical 

 area), HSA (health service area). If an MSA or HSA is divided by state 

 borders, the part in each state is a distinct payment area. Statewide rural 

 areas are counties in the same state lying outside MSAs.

Source: MedPAC analysis of county-level fee-for-service spending and other data 

 from CMS. Number of Medic

are benefici

aries 

at 10th

percentile of p

ayment 

are

a definition

10,000

9,000

8,000

7,000

6,000

5,000

4,000

3,000

2,000

1,000

0

MSA/statewide 

rural area

HSA County MSA/HSA

Payment area definition

Larger payment areas have 

more Medicare beneficiaries 

and more stable AAPCCs

FIGURE

2-4
We evaluate the three larger payment area alternatives

described on pages 45–46, basing our evaluation on 

four criteria:

• Will CMS and plans face substantial burdens in

collecting the data necessary to determine plan

payments?

• Will payment areas have enough beneficiaries to

obtain reliable AAPCCs?

• How well do payment areas match the market areas

that plans serve?

• Would payment areas be too large to be fairly

homogeneous in terms of costs of serving

beneficiaries?

Will CMS and plans face substantial burdens

from data collection?

Because the three alternatives that we considered use the

county as their building block, neither CMS nor plans

would have any additional burden from collecting the data

necessary to determine plan payments. Also, plans often

use counties as the building block for their service areas.

Therefore, our use of counties as the basis for building

payment areas has some favorable attributes.

Will the three alternatives have enough

beneficiaries?

Relative to the county definition, all three alternatives

would tend to increase the number of Medicare

beneficiaries in payment areas (Figure 2-4). Therefore,

each alternative would increase the stability of AAPCCs.

For example, when we consider the distribution of the

number of beneficiaries among payment areas, the county

at the 10th percentile had 809 beneficiaries in 2002. In

contrast, the MSA/statewide rural area definition had more

than 9,200 beneficiaries at the 10th percentile, HSAs had

2,700 beneficiaries, and the MSA/HSA definition had

2,600. The MSA/statewide rural area definition had the

highest number of beneficiaries because statewide rural

areas often encompass more counties than MSAs 

and HSAs.

How well do payment areas match plan

market areas?

Ideally, payment areas should perfectly match the

geographic areas that plans serve (plan market areas). 

We have identified two measures that can give us a 

sense of how well a payment area definition matches 

plan market areas:

• If one county of a payment area is served by at least

one plan, are all counties in the payment area served

by at least one plan? For example, if a payment area

has two counties and we know that at least one plan

serves one of those counties, we ask: Does at least one

plan serve both counties? Note that the same plan does

not have to serve all counties of a payment area.

• If a plan serves at least one county in a payment area,

does it serve the entire payment area?

Under both measures, if some parts of a payment area are

covered but other parts are not, the payment area might

not accurately represent plan market areas. In our analysis,

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 49

How payment areas compare with market areas 

of Medicare Advantage and private-sector plans 

If one county in an area is served by If a plan serves one county in an

plans, likelihood all counties are served area, likelihood it serves all counties

Payment area definition Private-sector plans MA plans Private-sector plans MA plans

MSA/HSA 94.9% 69.6% 69.8% 59.4%

MSA/Statewide rural area 93.8 65.6 63.4 52.5

HSA 93.3 49.0 55.4 41.8

Note: MA (Medicare Advantage), MSA (metropolitan statistical area), HSA (health service area). If an MSA or HSA is divided by state borders, the part in each state is a 

distinct payment area. Statewide rural areas are counties in the same state lying outside MSAs. 

Source: MedPAC analysis of data from CMS and InterStudy.

TABLE

2-2
we considered how well our three proposed alternatives

match the market areas of coordinated care plans that

participate in MA as well as the market areas of HMOs 

in the private sector.

Among the three alternatives, the MSA/HSA definition

performs the best, when we consider market areas of MA

plans and those of private-sector HMOs. The HSA

definition performs the worst (Table 2-2, p. 49).

Would payment areas be too large?

We want payment areas that are large enough to obtain

stable AAPCCs, but small enough so that the cost of

serving beneficiaries is fairly homogeneous. We measured

the homogeneity of cost under each alternative as the

difference between the largest and smallest AAPCCs

among counties in the same payment area. When we

consider the payment areas within each definition that

show the largest differences (90th percentile and higher),

the MSA/statewide rural area definition has the largest

differences relative to the other definitions (Figure 2-5).

We are not surprised by this result because statewide rural

areas can encompass relatively large geographic areas,

increasing the likelihood of large differences in per capita

spending.

Payment area recommendations

We do not consider any of the three alternatives an

optimal payment area. This is to be expected; no single

method of grouping counties can perfectly match all plan

market areas because markets differ.

Despite the shortcomings of our alternatives, the Congress

can improve payment areas over the county definition by

making the following changes:

• MSAs should serve as the payment area for urban

counties.

• Payment areas for rural counties should be collections

of counties that represent health care market areas for

Medicare beneficiaries. An example is the HSAs we

examined in this report.

We prefer MSAs to HSAs for urban counties because

MSAs match plan market areas better (Table 2-2, p. 49).7

For rural counties, we prefer to use payment areas that 

are smaller than statewide rural areas because statewide

rural areas often have high variations in the cost of serving

beneficiaries. This could make them unattractive to plans

and unnecessarily hinder plans from serving rural areas.

The Secretary generally should require plans to serve

entire payment areas, irrespective of the payment area

definition. But plans also should have the opportunity 

to obtain waivers allowing them to serve only specific

portions of a payment area if they can show that it is

difficult to form provider networks throughout the

payment area.

If the Congress chooses to implement our recommended

payment area definition, three issues should be considered

before the Secretary puts it into practice. First, the

Secretary should confirm whether plans have any concerns

that a few payment areas have unusual characteristics that

the Secretary should address. Second, if an MSA is so

large that most MA local plans do not serve all of it, the

Secretary could consider dividing the MSA into smaller

groups of counties. Third, MA plans are facing substantial

changes in the near future, including a new payment

system based on plan bids and a prescription drug benefit.

It may be prudent to allow plans time to become

accustomed to these other changes before introducing new

payment areas.

50 Medicare Advantage p ayment areas and risk adjustment

Note: AAPCC (adjusted average per capita cost), HSA (health service area), 

 MSA (metropolitan statistical area). If an MSA or HSA is divided by state 

 borders, the part in each state is a distinct payment area. Statewide rural areas

 are counties in the same state lying outside MSAs.

Source: MedPAC analysis of county-level fee-for-service spending and other data 

 from CMS.

Largest difference in AAPCCs

within p

ayment 

are

as $400

300

350

250

150

50

200

100

0

Min 10 20 30 40 50 60 70 80 90 Max

Percentile rank

HSA

MSA/HSA

MSA/statewide rural area

Geographic differences in AAPCCs

are greater in larger payment areas

FIGURE

2-5
The effect of this recommendation on plan participation

and beneficiary enrollment in MA plans is uncertain.

Relative to the county definition, the MSA/HSA definition

tends to increase plan payments in counties that currently

have low county rates, which could increase plan

participation and beneficiary enrollment. In contrast, the

MSA/HSA definition tends to decrease payments in

counties with high rates, which could decrease plan

participation and beneficiary enrollment. Consequently,

we cannot predict the effect that changes in beneficiary

enrollment would have on overall program spending.

Finally, no payment area definition is perfect. One

problem presented by the MSA/HSA definition is that

payment areas may have noncontiguous counties.

Nevertheless, the MSA/HSA definition is better than the

current county definition. If the MSA/HSA definition does

create noncontiguous payment areas, the Secretary could

examine those situations to determine whether he should

break up an HSA into smaller groups of counties.

RECOMMENDATION 2A

The Congress should establish payment areas for

Medicare Advantage local plans that have the

following characteristics:

• Among counties in metropolitan statistical areas,

payment areas should be collections of counties that

are located in the same state and the same

metropolitan statistical area.

• Among counties outside metropolitan statistical

areas, payment areas should be collections of

counties in the same state that are accurate

reflections of health care market areas, such as

health service areas.

RATIONALE 2A

Counties are often too small to serve adequately as

payment areas for MA local plans. However, counties

should be the building block for larger payment areas

because plans and CMS would have no additional data

collection burden. Our assessment of alternatives to the

county definition shows that among urban counties, MSAs

are reasonably good matches for plan market areas.

Among rural counties, payment areas must not be so large

that the cost of providing care varies widely within

payment areas. HSAs are reasonable matches to that

criterion and have the additional attribute of reflecting

market areas for short-term inpatient stays among

Medicare beneficiaries.

IMPLICATIONS 2A

Spending

• This recommendation should have no direct effect on

program spending.

Beneficiaries and plans

• The effect on plan participation is ambiguous. On the

one hand, plans may decrease the areas they serve if

larger payment areas sufficiently reduce opportunities

for isolating payment areas in which payments are

favorable relative to costs. On the other hand, plans

may increase the areas they serve if payments increase

sufficiently in counties that they currently do not

serve. Because of the uncertain effect on plan

participation, this recommendation would have an

ambiguous effect on beneficiaries’ access to MA

plans.

We caution that the HSA definition we used in our

analysis is purely for illustrative purposes. Makuc and

colleagues (1991) defined HSAs using data from hospital

inpatient stays that occurred in 1988. If the Congress

chooses HSAs as a payment area, the Secretary should

first update those HSAs and keep them up to date over

time. The Secretary should use the most recent source data

and make sure the updates reflect changes in service areas.

The update will be a complicated process, and the

Secretary should allow ample time for it to be done

properly.

RECOMMENDATION 2B

The Secretary should update health service areas

before using them as payment areas in the Medicare

Advantage program. In addition, the Secretary should

make periodic updates to health service areas to reflect

changes in health care market areas that occur over

time.

RATIONALE 2B

Makuc and colleagues (1991) developed the current

version of HSAs using data from hospital inpatient stays

that occurred in 1988. The Secretary should update HSAs

to reflect changes in health care markets that have

occurred since then. In addition, health care markets will

continue to change, and the HSAs should receive periodic

updates to reflect those changes.

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 51
IMPLICATIONS 2B

Spending

• This recommendation should have no direct effect on

program spending.

Beneficiaries and plans

• This recommendation should have no effect on plan

participation or beneficiaries’ access to plans.

How accurately does the CMS–HCC

model reflect cost differences?

The measure that we use to evaluate the accuracy of the

CMS–HCC model is the predictive ratio, which indicates

how well a risk adjuster predicts the costliness of a group

of beneficiaries to the Medicare program. The definition

of a predictive ratio for a group is the group’s mean

costliness predicted by a risk adjuster divided by the mean

of the group’s actual costliness. If a risk adjuster predicts 

a group’s costliness perfectly, predicted costliness equals

actual costliness and the predictive ratio equals 1.0. But 

if a risk adjuster overpredicts a group’s costliness, the

predictive ratio will be greater than 1.0. Alternatively, 

if a risk adjuster underpredicts a group’s costliness, the

predictive ratio will be less than 1.0. In summary, the

closer a predictive ratio is to 1.0, the better the risk

adjuster has performed.

We based the predictive ratios in our analysis on 

predicted and actual costliness in 2002. The data that 

we used to obtain predicted and actual costliness are 

from administrative and claims information from a

random sample of 5 percent of beneficiaries in FFS

Medicare. We used the same version of the CMS–HCC

that CMS has used in 2004 and 2005.

In our analysis, we grouped beneficiaries using

characteristics that reflect either good or bad health. 

These characteristics include:

• quintile of costliness in 2001;

• number of hospital inpatient stays in 2001; and

• conditions diagnosed in 2001, including alcohol or

drug dependence, diabetes with complications,

diabetes without complications, congestive heart

failure, acute myocardial infarction (AMI), chronic

obstructive pulmonary disease, unspecified stroke,

cerebral hemorrhage, and hip fracture.

For each of these groups, we compared the predictive

ratios from the CMS–HCC to predictive ratios from a

model similar to the demographic system. We chose not 

to use the actual demographic system because some of the

data used in that model—such as institutional status—are

difficult to obtain. Instead, we chose a model that uses

beneficiaries’ age and sex to predict their costliness to 

the Medicare program. Other researchers have used the

age/sex model in several studies as a point of reference 

for the performance of other risk-adjustment models 

(Pope et al. 2000, Pope et al. 1999, Ellis et al. 1996).

52 Medicare Advantage p ayment areas and risk adjustment

CMS–HCCs better predict 

beneficiaries’ costliness than 

a demographic model

Predictive ratios from 

two risk adjusters

Beneficiary

group CMS–HCCs Age/Sex

Quintile of costliness in 2001

Lowest 1.34 2.53

Second 1.30 1.96

Third 1.19 1.47

Fourth 0.98 0.96

Highest 0.83 0.44

Number of inpatient stays in 2001

Zero 1.07 1.38

One 0.96 0.65

Two 0.92 0.49

Three or more 0.80 0.29

Conditions diagnosed in 2001

Alcohol/drug dependence 0.99 0.39

Diabetes w/complications 0.99 0.44

Diabetes w/o complications 0.99 0.72

Congestive heart failure 0.90 0.50

Acute myocardial infarction 0.98 0.64

COPD 0.93 0.67

Unspecified stroke 1.03 0.79

Cerebral hemorrhage 1.09 0.65

Hip fracture 1.08 0.80

Note: CMS–HCCs (CMS–hierarchical condition category); COPD (chronic

obstructive pulmonary disease). A predictive ratio for a group of 

beneficiaries is the mean of their costliness predicted by a risk-adjustment 

model divided by the mean of their actual costliness. The age/sex model 

uses beneficiaries' age and sex to predict costliness. All conditions listed 

are used in the CMS–HCC model.

Source: MedPAC analysis of 5 percent sample of beneficiaries participating

in fee-for-service Medicare in 2001 and 2002.

TABLE

2-3
Our results show that in each group, predictive ratios are

closer to 1.0 under the CMS–HCC than under the age/sex

model (Table 2-3). This indicates the CMS–HCC does a

better job than the age/sex model of predicting the

costliness of beneficiaries who are in good health and

those who are in bad health.

However, the CMS–HCC leaves room for improvement.

For example, the predictive ratio is 1.34 for beneficiaries

in the lowest quintile of costliness in 2001 and 0.83 for

beneficiaries in the highest quintile, indicating the

CMS–HCC overpredicts the costliness of beneficiaries

who are in good health and underpredicts for those who

are in poor health. CMS will introduce an improved

version of the CMS–HCC in 2007 that should reduce 

these prediction errors.

A final issue is that CMS will use the CMS–HCC to

predict how much MA enrollees would cost Medicare if

they were enrolled in the FFS program. This can be a

problem if Medicare’s goal is to pay MA plans accurately

for the costs plans incur in providing care to their enrollees

and the relative costs of treating conditions are markedly

different between FFS Medicare and MA plans. For

example, the relative cost of treating a beneficiary who

had an AMI to a beneficiary who has no conditions could

be different between the FFS and MA programs.

Conversely, if FFS Medicare and MA plans have the same

relative costs in treating conditions, this issue is irrelevant.

Some observers have found little or no difference between

health care delivery systems in terms of the relative costs

of treating conditions. But to definitively determine

whether relative costs are different or similar between MA

plans and FFS Medicare, we must have data on the costs

that plans incur in providing care to individual enrollees.

These data are not available to Medicare, but CMS might

wish to explore this issue by collecting the necessary data

from one or more MA plans. Those that pay their

providers on an FFS basis would be less burdened than

other plans in compiling such a database. 

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 53
1 The measures of variation include the standard deviation,

which is the square root of the variance; the coefficient of

variation, which is the standard deviation divided by the

mean of the distribution; and the average of the absolute

differences from the mean.

2 We also estimated the variation in AAPCCs attributable 

to input prices and the variation due to IME, GME, and 

DSH payments. We found that adjusting for input prices

reduces the variation by about 15 percent and adjusting 

for differences in special payments to hospitals reduces 

the variation by about 8 percent. When we adjust for these

factors simultaneously, the reduction in variation is about 

15 percent, less the sum of the individual effects—23

percent. This occurs because input prices and special

payments to hospitals interact in such a way that their

impacts are mitigated when taken together.

3 By law, state governors can request that payment areas in

their states be groups of counties rather than single counties,

but none have done so. The law allows three possibilities: 

(1) making the entire state one payment area; (2) grouping

counties that are located in metropolitan statistical areas

(MSAs) into payment areas and grouping counties that 

are not located in MSAs into a single payment area; and 

(3) grouping noncontiguous counties.

4 Our definitions of urban and rural are based on definitions 

of metropolitan and micropolitan statistical areas created by

the Office of Management and Budget (OMB) in 2004.

OMB grouped counties into metropolitan statistical areas,

micropolitan statistical areas, and rural areas. We define

urban counties as those that are located in metropolitan

statistical areas, and we define rural counties as those that 

are located in either micropolitan statistical areas or 

rural areas.

5 The basis for this decision was results from work with health

care commuting areas (HCCAs), which were developed in

1976 using data from 1968 to 1970. Makuc and colleagues

decided it was reasonable for the number of HSAs to be

about equal to the number of HCCAs. They found that the

HCCAs performed well as health service areas and there 

had not been a major change in the number of hospital 

beds between 1970 and 1988 (where 1988 is the year of 

their data).

6 Earlier, we used five-year averages to analyze the variation

in AAPCCs among counties. We used four-year averages to

analyze annual changes because we have data from 1998

through 2002. We used data from 1998 through 2001 to

obtain four-year averages for 2001 and data from 1999

through 2002 to obtain four-year averages for 2002.

7 We also examined the 20 largest metropolitan areas to see

how well the MSA/HSA definition and the HSA definition

match the areas served by HMOs participating in the Federal

Employees Health Benefits (FEHB) Program. In general, the

MSA/HSA definition performs better because the HSA

definition often includes more rural counties that the FEHB

Program plans do not serve.

54 Medicare Advantage p ayment areas and risk adjustment

Endnotes
Ellis, R. P., G. C. Pope, L. I. Iezzoni, et al. 1996. Diagnostic cost

group (DCG) and hierarchical coexisting conditions (HCC)

models for Medicare risk adjustment. Waltham, MA: Health

Economics Research, Inc. April 26.

Fisher, E. S., D. E. Wennberg, T. A. Stukel, et al. 2003.

Implications of regional variations in Medicare spending, part 1:

The content, quality, and accessibility of care. Annals of Internal

Medicine 138, no. 4 (February 18): 273–287.

Makuc, D. M., B. Haglund, D. D. Ingram, et al. 1991. Vital and

health statistics: Health service areas for the United States, series

2, no. 112. Hyattsville, MD: National Center for Health Statistics.

November.

Medicare Payment Advisory Commission. 2003. Report to the

Congress: Variation and innovation in Medicare. Washington,

DC: MedPAC.

Medicare Payment Advisory Commission. 2001. Report to the

Congress: Medicare payment policy. Washington, DC: MedPAC.

Pope, G. C., R. P. Ellis, A. S. Ash, et al. 2000. Diagnostic cost

group hierarchical condition category models for Medicare risk

adjustment. Waltham, MA: Health Economics Research, Inc. 

July 31.

Pope, G. C., C. F. Liu, R. P. Ellis, et al. 1999. Principal inpatient

diagnostic cost group models for Medicare risk adjustment.

Waltham, MA: Health Economics Research, Inc. February 24.

Wennberg, J. E., and M. M. Cooper. 1999. The Dartmouth atlas

of health care in the United States: A report on the Medicare

program. Chicago: AHA Press.

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 55

References

The Medicare

Advantage program

CHAPTER 3
RECOMMENDATIONS

3A The Congress should eliminate the stabilization fund for regional preferred provider

organizations.

COMMISSIONER VOTES: YES 15 • NO 1 • NOT VOTING 0 • ABSENT 1

 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3B The Secretary should calculate clinical measures for the fee-for-service program that

would permit CMS to compare the fee-for-service program to Medicare Advantage plans.

COMMISSIONER VOTES: YES 16 • NO 0 • NOT VOTING 0 • ABSENT 1

 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3C The Congress should clarify that regional plans should submit bids that are standardized

for the region’s Medicare Advantage–eligible population. 

COMMISSIONER VOTES: YES 16 • NO 0 • NOT VOTING 0 • ABSENT 1

 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3D The Congress should remove the effect of payments for indirect medical education from

the Medicare Advantage plan benchmarks.

COMMISSIONER VOTES: YES 16 • NO 0 • NOT VOTING 0 • ABSENT 1

 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3E a) The Congress should set the benchmarks that CMS uses to evaluate Medicare

Advantage plan bids at 100 percent of the fee-for-service costs. 

COMMISSIONER VOTES: YES 16 • NO 0 • NOT VOTING 0 • ABSENT 1

b) At the same time, the Congress should also redirect Medicare’s share of savings from

bids below the benchmarks to a fund that would redistribute the savings back to Medicare

Advantage plans based on quality measures. 

COMMISSIONER VOTES: YES 16 • NO 0 • NOT VOTING 0 • ABSENT 1

 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3F The Congress should put into law the scheduled phase-out of the hold-harmless policy that

offsets the impact of risk adjustment on aggregate payments through 2010.

COMMISSIONER VOTES: YES 16 • NO 0 • NOT VOTING 0 • ABSENT 1
Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 59

edPAC supports giving Medicare beneficiaries a

choice among health care delivery systems.

Where private plans can improve the efficiency

and quality of health care services for Medicare

beneficiaries they should be encouraged to do so and beneficiaries should

be given an opportunity to choose them. The Medicare Prescription

Drug, Improvement, and Modernization Act of 2003 (MMA) introduced

a number of changes to the program of private plans in Medicare and 

created the Medicare Advantage (MA) program. New types of plans

were introduced, plan quality requirements were altered, and payment

policies were modified. Some of these changes raise issues concerning

financial neutrality and the conditions of competition between choices. This chapter provides an overview of 

major changes and provides recommendations on a number of provisions related to the MA program. 

3

In this chapter

• Overview of changes to the 

managed care program 

under the MMA

• What are the new types 

of plans?

• Quality

• Enrollment

• Benefits

• The MA bidding process 

for 2006

• Financial neutrality under 

the 2006 bidding system

CHAPTER

M

The Medicare 

Advantage program
MedPAC supports private plans in the Medicare program.

In general, Medicare beneficiaries should be able to

choose between the fee-for-service (FFS) Medicare

program and the alternative delivery systems that private

plans can provide, as long as the choices are efficient for

the program. Private plans may have greater flexibility 

in developing innovative approaches to care, and these

plans can more readily use tools such as care coordination

and other health care management techniques to improve

the efficiency and quality of health care services that

Medicare beneficiaries receive. 

Since 1982, Medicare beneficiaries in many areas of the

country have been able to choose between whether to

receive care under the traditional FFS program or through

private plans—which, in return for a fixed monthly

payment from the Medicare program, agree to provide a

benefit package at least equivalent to that available in FFS.

Often, these plans have supplemented Medicare benefit

packages and have offered them for less than the price

beneficiaries pay for supplemental Medigap policies.

Private plans in Medicare have experienced varying

degrees of enrollment over the years, peaking at 

17 percent of the Medicare population in 1999 but

declining to 12 percent by 2004 (MedPAC 2004a). 

MedPAC also supports financial neutrality between

payment rates for the FFS program and private plans.

Additionally, MedPAC supports equitable payment 

rates among private plans. Financial neutrality means 

that the Medicare program should pay the same amount,

regardless of which Medicare option a beneficiary

chooses. If a beneficiary chooses a more expensive plan,

that beneficiary can choose to pay additional premiums. 

In paying private plans more than FFS—or paying certain

private plans more than other private plans—the payment

system encourages inefficiency and contributes to

increased overall spending for the Medicare program

(MedPAC 2004b).

Financial neutrality is important because Medicare costs

are high and will continue to increase rapidly for the

foreseeable future, particularly with the impending

eligibility of the baby boom generation. The Medicare

program needs to offer private options that will help

reduce, not increase, overall program spending. In raising

MA plans’ rates above FFS rates in order to attract plans

to new areas of the country, Medicare does not create

incentives for the efficient provision of high-quality care.

Medicare should set payment rates to encourage plans to

achieve high quality with lower resource use. It may 

be consistent with the Congress’s goal of increased

availability of MA plans to set MA rates higher than FFS

rates in the short term to help plans build infrastructure;

however, to continue to do so would be a disservice both

to Medicare beneficiaries and—in these times of

increasing budget deficits—the taxpayer. If MA plans

exist in markets only because payment rates are higher

than FFS rates, any reduction in those rates would likely

lead to considerable disruption for beneficiaries; they

would have to switch to another MA plan or return 

to the FFS program. This change could make Medicare

beneficiaries’ perceptions of the MA program

unfavorable—as happened after plans withdrew from

Medicare in the late 1990s—and could ultimately

undermine the ability of efficient, high-quality MA 

plans to succeed under Medicare. 

However, MedPAC is also aware that the Congress has

raised payment rates for private plans and has introduced

new types of private plans, such as regional preferred

provider organizations (PPOs), to encourage expansion of

the MA program to new areas and to try to reverse several

years of declining enrollment. Lowering rates to achieve

financial neutrality in the short run would likely reduce 

the participation of plans and beneficiaries in the MA

program; doing so in the midst of the 2006 bidding

process would cause significant disruption. Regional 

PPOs and new local MA plans are preparing to enter the

MA program, but they might reconsider whether to enter

certain markets—or whether to leave certain markets after

a short period of time. Additionally, some provisions in

the MMA, such as the more competitive system, may

provide valuable information to inform our thinking 

about more appropriate payment rates.

Thus, MedPAC supports a policy of financial neutrality

for the MA program, coupled with incentives for

delivering high-quality care. We have found that

organizations are more likely to be efficient when they

face financial pressure. The Medicare program needs 

to exert consistent financial pressure on both the FFS 

and MA programs, coupled with meaningful quality

measurement and pay-for-performance programs, in 

order to maximize the value it receives for the dollars it 

is spending. MedPAC recognizes that the Congress may

not be able to achieve this objective immediately. We

designed the recommendations in this chapter to provide

future, as well as immediate, steps toward this objective. 

60 The Medicare Advantage p rogram
Overview of changes to the managed

care program under the MMA

The MMA is the Congress’s most recent attempt to

increase private plans’ participation in the Medicare

program. The MMA changed several major elements of

the program for private plans that participate in Medicare.

These changes include:

• Types of plans. The MMA added two new types of

plans: regional PPOs and special needs plans.

• Payment method. The MMA changed the method of

payment from one in which Medicare pays plans

based on an administered price to one in which plans

will bid against an administered price.

• Drug benefit provision. All MA plans—except

private fee-for-service (PFFS) and Medicare Savings

Account (MSA) plans—will offer the minimum drug

benefit that will be available to all beneficiaries under

Part D. 

• Enrollment period. Current policy allows

beneficiaries to change plans on a monthly basis.

Beginning in 2006, the enrollment process will change

to an annual open enrollment period. However, dual

eligibles (that is, beneficiaries who are eligible for

both Medicare and Medicaid) will be allowed to

change plans at any time.

• Name of program. The MMA renamed the program

from Medicare+Choice (M+C) to Medicare

Advantage (MA).

Table 3-1 details the full list of MMA changes in 

the MA program.

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 61

Medicare Advantage changes as a result of the MMA 

Program feature Medicare+Choice Medicare Advantage

Types of plans HMOs, PPOs, PFFS, MSA, HMOs, regional and local PPOs, PFFS, MSA,

specialized plans special needs plans

Cost plans Were to expire 12/31/04 Expire 12/31/07 unless fewer than two Medicare

Advantage plans in an area

Quality Quality assurance focus Quality improvement focus

Enrollment ESRD allowed only if beneficiary ESRD allowed only if beneficiary already enrolled in

already enrolled in Medicare+Choice Medicare Advantage plan prior to onset of ESRD or

plan prior to onset of ESRD if beneficiary enrolled in special needs plan that 

accepts ESRD beneficiaries

Open enrollment period Continuous monthly Annual, with several exceptions

Medicare benefits package All Part A and Part B services except hospice All Part A and Part B services except hospice; certain

types of plans must offer a Part D drug plan. Regional 

PPOs must offer a combined deductible and stoploss

Payment Administered prices based on three-prong system Bidding with administered prices as a benchmark in a 

two-prong system

Additional benefits Difference between plan costs and price 75% of difference between plan bid and benchmark must

must be returned as additional benefits. If Part B be returned as additional benefits/premium reductions;

premium reduction, 80% of difference available 25% of difference retained by Medicare

and 20% retained by Medicare

Payment areas County County, for local plans; regions, for regional plans

Basic risk adjustment CMS–HCC method CMS–HCC method

Note: HMO (health maintenance organization), MMA (Medicare Prescription Drug, Improvement, and Modernization Act of 2003), PPO (preferred provider 

organization), PFFS (private fee-for-service), MSA (medical savings account), ESRD (end-stage renal disease), CMS–HCC (CMS–hierarchical condition category).

Source: Medicare Prescription Drug, Improvement, and Modernization Act of 2003.

TABLE

3-1
What are the new types of plans?

The MMA allowed two new types of plans under the MA

program and changed several features of the existing plans.

Regional PPOs

The addition of regional PPOs was probably the most

visible change to the types of plans allowed to participate

in the program. PPOs in the private market generally

contract with a set of providers to offer services at

discounted fees. Providers accept the lower fees in return

for anticipated higher patient volume, because PPO

members generally have financial incentives—structured

through differences in cost sharing—to seek care from

preferred providers. Unlike a health maintenance

organization (HMO), PPO members can receive care from

providers outside the preferred PPO network, although

they generally pay higher cost sharing for doing so. PPOs

and point-of-service plans (POS)—which have a similar

plan design—existed under the earlier M+C program. 

But until CMS established a PPO demonstration program

in 2003, these types of plans were slow to emerge.

However— perhaps in preparation for the emergence of

regional PPOs in 2006 and the subsequent moratorium 

on local PPOs (discussed later in this chapter)—CMS

received new applications from 70 local PPOs for 2005,

26 of which the agency approved. These were available 

to beneficiaries as of January 2005. These new PPO

offerings are in addition to those from the existing

demonstration PPOs. Regional PPOs differ from local

PPOs in that they must serve the entire region that CMS

has defined for this type of plan. 

PPO regions

Some policymakers hope that requiring plans to serve

larger regions will bring MA plans to more parts of the

country and give beneficiaries more choices. Policymakers

also expect that specific provisions in the MMA relating 

to payment, network adequacy, and cost sharing will

encourage private plans to serve rural as well as urban

areas in a region. The MMA specified a minimum of 10

regions and a maximum of 50 regions for regional PPOs

and required that the Secretary construct the regions based

on an analysis of current health insurance markets. (As we

discuss later, the Secretary ultimately decided on 26 PPO

regions.) During the course of Medicare’s managed care

program, the Congress has often taken steps to encourage

private plans to broaden their service areas, hoping that

these plans—with their often attractive benefit packages—

would make themselves available to more beneficiaries.

Most notable have been congressional increases in

payment rates in areas that have below-average levels 

of FFS program spending. (We discuss the payment rates

later in this chapter.) These areas often tend to be rural.

MedPAC and others have cited two primary reasons 

(other than Medicare payment rates) why MA plans are

less likely to serve rural, sparsely populated areas

(MedPAC 2001). First, unlike managed care products 

sold to employers (in which plans market to an employer

to win the business of an entire group of employees), MA

plans sell policies to individual Medicare beneficiaries.

Marketing individual products is expensive, and the 

return on investment is lower in areas that contain few

Medicare beneficiaries. 

Second, plans face difficulty in building provider networks

in less densely populated areas. In areas that have many

competing hospitals and physicians, these providers are

more willing to accept a plan’s contracting terms. In rural

areas, less competition among providers means less

incentive to negotiate with plans over fees and other 

plan requirements. Additionally, health plans face certain

fixed costs before they can enroll a single member. Thus,

plans face problems in establishing programs in low-cost

(generally rural) areas, and they have certain advantages 

in higher cost (generally urban) areas. 

62 The Medicare Advantage p rogram

Note: FFS (fee-for-service).

Source: MedPAC analysis of Adjusted Community Rate Proposal data. Cost to deliver benefits

FFS

Plan

FFS costs

Fixed 

administrative 

costs

Comparison of private plan versus 

FFS costs, by market area, 2004

FIGURE

3-1
MedPAC illustrates these problems in an analysis of

private plan adjusted community rate (ACR) data. In 

areas that have low levels of FFS costs, plan costs exceed

FFS costs. However, in areas that have high levels of FFS

costs, plans are increasingly able to provide Medicare

benefits at less than FFS costs (either by managing care

more efficiently or negotiating reduced prices from

providers)—even considering their initial fixed costs

(Figure 3-1). This helps to explain why the majority 

of MA enrollment is in higher cost, urban areas.

One type of MA plan—the PFFS plan—specifically

targets enrollees in rural areas where Medicare payment

rates are high relative to spending under the traditional

FFS program.1 Because PFFS plans do not need to

contract with providers to meet Medicare’s access and

participation requirements, they face lower fixed costs.

These PFFS plans are considered to have met the access

requirements by paying providers at least the fees that

would apply under the traditional FFS program, thus

enabling them to compete in lower cost rural counties.

Although for several years only one company offered

these types of plans, several more companies offered them

in 2004 and 2005—and we expect more in 2006. As of

March 2005, total enrollment in PFFS plans was 71,000, 

a small share of the 5.6 million total enrollment in private

plans, but an increase of more than 150 percent from

March 2004 (Figure 3-2).

The Congress hopes that regional PPOs will have much

broader appeal to Medicare beneficiaries than existing

plan types because PPOs have become the most popular

health insurance option in the private sector, following a

consumer backlash against HMOs in the late 1990s. If

many of these plans enter the program to serve regions

across the country, private plans will be more widely

available to beneficiaries. The ultimate popularity of the

regional PPO offering will not be evident for a number of

years, but as of May 2005, plans had indicated an interest

in becoming regional PPOs in 21 of the 26 PPO regions

(Inside Washington Publishers 2005).

CMS analyzed a number of factors in determining 

how to establish regions to encourage regional PPOs’

participation in the MA program (CMS 2004) (Figure 3-3,

p. 64). These factors included the following:

• Population size. CMS concluded that an area needs at

least 200,000 eligible beneficiaries for a plan to be

able to form networks. CMS also concluded that the

region should include no more than 3 million

beneficiaries because of potential start-up costs.

• Sufficient number of existing competitors. CMS

looked at whether existing competitors were already

located in the area, expecting that the regional PPO

plans would be developed by companies already

offering health insurance coverage.

• Limited variation in payments within regions. CMS

grouped states that had similar average plan payments.

• The preservation of geographic patient flows. CMS

grouped states in which beneficiaries typically receive

care across state borders.

Based on this analysis of existing insurance markets, 

CMS chose 26 PPO regions. 

Regional PPO features

Regional PPOs and local MA plans must cover the same

Medicare Part A and B benefits as under the FFS program

(with the exception of hospice care). All MA plans must

follow local coverage decisions, but regional PPOs that

span multiple areas with differing policies can select a set

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 63 Enrollment (millions)

7

8

5

0

1

2

3

4

6

1994 1996 1998 2000 2004 2002

Total Risk

HCPP Cost PFFS

Note: HCPP (health care prepayment plan), PFFS (private fee-for-service).

Source: CMS.

Enrollment in Medicare 

private plans, by plan type

FIGURE

3-2
of local coverage policies from a single FFS contractor

group and apply them uniformly across the region.

Regional PPOs may also require different cost sharing for

in-network and out-of-network providers. Aggregate innetwork cost sharing in a regional PPO cannot exceed

aggregate cost sharing under FFS Medicare. Neither

regional PPOs nor local MA plans may allow providers to

balance-bill Medicare beneficiaries, nor may they limit

particular benefits to only in-network providers.2

Similar to local plans, regional PPOs generally must

ensure access to a network of providers. Local plans must

document this requirement with written agreements to

furnish services. However, recognizing the difficulty of

establishing provider networks in rural areas, CMS allows

regional PPOs to have more flexibility and to propose

alternative methods of establishing that they meet access

requirements. CMS states in its final MA regulation that it

“will allow MA regional plans to contract with CMS with

less robust networks of contracted providers” than CMS

requires of local coordinated care plans (CMS 2005a).

These plans will meet CMS’s access requirements

provided that the plans reimburse providers with whom

they do not contract at Medicare FFS rates and limit

enrollee cost sharing liability to in-network levels. For

example, a regional PPO may establish a network that

meets the statutory network adequacy requirements

throughout 85 percent of a region. In that part of the

region, the plan may charge higher cost sharing for 

out-of-network services. But in the part of the region

without a network, the plan cannot charge higher cost

sharing for out-of-network services. In certain areas,

CMS’s flexibility toward PPOs regarding network

adequacy requirements could be perceived as giving

regional PPOs an advantage over local MA plans.

64 The Medicare Advantage p rogram

ME

VT

NH

MA

RI

CT

NY

PA

NJ

DE

MD

DC

VA

NC

SC

GA

FL

AL MS

TX LA

AZ NM

OK

AR

TN

KY

OH

WV

MI

IL IN

WI

MN

IA

MO KS

NE

SD

MT ND

WY

CO

UT

NV

CA

ID

WA

OR

AK

HI

Source: CMS.

Medicare Advantage regions

FIGURE

3-3
Regional PPOs that use a combination of in- and outof-network services cannot require beneficiaries to 

get services preauthorized. However, plans can warn

beneficiaries that they do not cover certain services and

they can encourage beneficiaries to first call the plan to

determine whether it covers the services in question. 

Plans can offer an incentive for beneficiaries to call by

charging less cost sharing when beneficiaries notify 

them of their intent to use out-of-network services.

To the extent that they have deductibles, the MMA

requires regional PPOs to provide a combined deductible

for Part A and Part B services (thus combining the

deductibles for hospital, physician, and post-acute care),

and an overall cap on beneficiary cost-sharing liability.

The deductible may be waived for preventive services, and

the cap may differ for in-network and out-of-network cost

sharing. Neither the MMA nor its subsequent regulations

set parameters for these benefit design elements, although

the actuarial value of the deductible, coinsurance, and

copayments in an MA plan may not exceed the actuarial

value of the deductible, coinsurance, and copayments that

would apply, on average, to FFS enrollees. Additionally,

CMS continues to have the authority to disallow the

offering of an MA plan if CMS determines that the benefit

design is likely to substantially discourage enrollment by

certain MA-eligible individuals. Local MA plans do not

have to offer a combined deductible, or the overall cap 

on beneficiary out-of-pocket liability.

Financial incentives to attract regional PPOs 

The Congress added three types of financial incentives to

encourage regional PPOs to participate in MA: risk

sharing for 2006 and 2007, a regional stabilization fund,

and essential hospital payments that may go to certain

hospitals in a regional PPO plan’s network. In addition,

the MMA established a moratorium on local PPO plan

entry in 2006 and 2007 (the act permits existing local

PPOs to offer new products within the existing service

area). This moratorium is intended to prompt private plans

to consider participating as regional PPOs.

Risk sharing for 2006 and 2007

Risk sharing for regional PPOs is structured through “risk

corridors”—plan-specific spending targets against which

actual plan spending is compared. Risk corridors may

function as a valuable protection for plans that serve large

regions with variable conditions. If costs exceed the target,

Medicare gives additional payments to the plans; if 

costs fall below the target, plans must return funds to

Medicare following a set schedule (Figure 3-4, p. 66). 

For example, a regional PPO that Medicare paid $700 

per member per month but that spent $735 on benefits 

net of administrative expenses would receive an additional

$7 per member per month under this formula (but would

lose an additional $28). By contrast, a regional PPO that

Medicare paid the same amount per month but that had

actual costs of $630 would remit $29 back to Medicare

(but would retain $41 in additional profits).

The risk corridor provision does not extend to drug

benefits that MA plans may cover under Part D; Part D

already includes separate risk-sharing arrangements for

these benefits through reinsurance and risk corridors. 

Risk sharing applies to Part A and Part B services, 

as well as any additional benefits that the MA plan

provided through the rebate process (which we describe

later in this chapter). However, risk sharing does not apply

to administrative costs. The target with which CMS

compares the costs is the plan’s payment less the portion

of administrative expenses assumed in the plan’s bid. 

Regional stabilization fund

The MMA provided for a regional PPO stabilization fund.

This fund would make additional payments to regional

PPOs, thus encouraging them to not only enter but remain

in markets. Beginning in 2007, $10 billion will be

available for the fund, and the fund will remain in

operation until December 2013. The $10 billion in initial

funding will be supplemented by 50 percent of any

government savings that accrue as a result of regional

PPOs bidding below the benchmarks (we discuss the

benchmarks and bidding process later in this chapter). If

CMS uses the fund for two years in a row, it must report to

the Congress on the market conditions that led to the

fund’s use. In response, the Congress could then change

the regions or payment systems.

Payments from the fund may be available in the 

following circumstances:

• The regional PPO plan or plans that become the first

national plan or plans to serve all regions of the

country will receive a bonus amount equivalent to 

3 percent of the benchmark amount for each regional

plan the PPO offered.

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 65
• If no national plans are offered, the Secretary may

increase the benchmark for a regional PPO plan that

becomes the first to serve a region. The Secretary will

determine this extra amount. The Secretary also has

the discretion to raise the benchmark in a region that

did not have any regional PPOs the previous year.

• If a regional PPO intends to depart from a region—

thus leaving the region with fewer than two regional

PPO plans—and a national plan does not exist, the

Secretary may increase the benchmark in order to

retain plans.

Note that the national plan bonus is the least targeted of

these circumstances because the bonus will be paid to 

the national plan(s) in all regions, even if regional PPOs

already serve many regions. Additionally, the payments

for regional PPOs that intend to depart a region may be

administratively difficult to implement and may create

incentives for regional PPOs to threaten to leave the

program in order to receive additional payments.

66 The Medicare Advantage p rogram

Note: PPO (preferred provider organization). When costs are less than 92 percent of target, plan pays Medicare 2.5 percent of the target amount plus 80 percent of the 

 difference between 92 percent of the target and actual costs. When costs are between 92 and 97 percent of target, plan pays Medicare 50 percent of the difference 

 between actual costs and 97 percent of the target. When costs are between 97 and 103 percent of target, there are no risk corridor payments. When costs are between

 103 and 108 percent of target, Medicare pays plan 50 percent of the difference between actual costs and 103 percent of the target. When costs are more than 108 

 percent of target, Medicare pays plan 2.5 percent of the target amount plus 80 percent of the difference between actual costs and 108 percent of the target. PPO p

ayments (doll

ars)

800

850

250

300

700

350

400

450

500

550

600

650

750

200

150

0

Relationship of plan costs to target

Actual costs Risk corridor payment to Medicare Loss

Costs are less than

92% of target

Costs are 92 to

97% of target

Costs are 97 to

103% of target

Costs are 103 to

108% of target

Costs are more than 

108% of target

Profit Risk corridor payment from Medicare

PPO target

Risk corridors for regional PPOs under Medicare Advantage, 2006–2007 

FIGURE

3-4
RECOMMENDATION 3A

The Congress should eliminate the stabilization fund for

regional preferred provider organizations.

RATIONALE 3A

MedPAC supports a level playing field, not only between

MA plans and the FFS program but also among different

types of MA plans. The PPO stabilization fund explicitly

makes available additional funds to regional PPOs—

funds that are not available to other MA plans. MedPAC

understands that Congress intends the stabilization fund to

encourage regional PPO plans’ participation and that plans

may be unsure of the risk they face by participating in 

the regional PPO program. The Commission also notes

that the risk corridor system will shield regional PPOs

from risk during the first two years of the program. As

discussed earlier, regional PPOs will have more flexibility

in assembling a provider network because of the looser

network adequacy requirements. If, over time, specific

problems emerge regarding regional PPO market entry 

or exit, the Congress could revisit the kinds of incentives

that may be appropriate to attract plans to certain areas.

IMPLICATIONS 3A

Spending

• This recommendation has no spending implications

over one year, as Medicare will not make payments

from the stabilization fund until 2007. This

recommendation would decrease federal spending 

by $1 billion to $5 billion over five years. 

Beneficiaries and plans

• Although it is unclear what the PPO stabilization

fund’s precise impact would be on stimulating plan

entry and preventing plan exits, this recommendation

could potentially discourage regional PPOs from

entering certain regions. Similarly, certain PPOs may

exit regions in which they otherwise might have

chosen to stay had they received payments from the

stabilization fund. As a result, beneficiaries in certain

areas may have fewer private-plan options from 

which to choose. 

Essential hospital payments

Regional PPOs that have trouble contracting with

hospitals may ask CMS to make additional payments to

those hospitals in order to secure an adequate network.

The MMA defines these hospitals as “essential hospitals.”

They are not critical access hospitals (CAHs), but rather

are hospitals paid under the inpatient prospective payment

system (IPPS) for FFS Medicare. The regional PPO must

demonstrate that the hospital’s inclusion in the network is

necessary to meet the plan’s access requirements and that

the PPO has made a good-faith effort to contract with the

hospital, paying it IPPS payment rates. To satisfy the

access requirement, the regional PPO must also show 

that no competing hospitals in the area will contract with

the PPO. Additionally, the hospital must demonstrate that

IPPS rates are too low to cover the hospital’s costs.

The MMA limits essential hospital payments to $25

million per year in the aggregate (adjusted for inflation).

CMS makes essential hospital payments directly to

eligible hospitals. The payment to the hospital constitutes

the difference between the payment that the hospital

would receive under the IPPS and the amount that the

program would pay a CAH. CMS will make essential

hospital payments on a first-come, first-served basis until

the annual amount is spent. This program represents an

additional source of funding that CMS makes available to

regional PPOs and not to other MA plans—a situation that

does not align with the Commission’s position on financial

neutrality. Additionally, some regional PPOs may view

the essential hospital program as more of a deterrent than

an aid, as it provides an incentive for hospitals to refuse 

to contract with regional PPOs in the hope of securing

essential hospital payments.

Specialized plans 

The MMA created another new category of MA plans

called specialized MA plans for special needs individuals,

or special needs plans (SNPs). SNPs are local or regional

MA plans that enroll a disproportionate share (defined as 

a greater proportion of the target group of special needs

individuals than that which occurs nationally in the

Medicare population) of special needs individuals. In the

MMA, the Congress suggests that eligible beneficiaries

might include institutionalized patients, dual eligibles, and

other individuals who have severe or disabling chronic

conditions. Rather than defining these plans in advance,

CMS has opted to allow the plans themselves to propose

target populations; CMS will then evaluate the proposals on

a case-by-case basis. The criteria for choosing specialized

plans include the existence of clinical programs or special

expertise for that plan’s target population. CMS has

approved 48 SNPs and is reviewing 18 applications for

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 67
services to be offered later in 2005. In addition, more than

100 SNPs have submitted applications to provide services

in 2006 (CMS 2005b).

Specialized plans are not new to the Medicare program 

but have generally existed as CMS demonstration

programs. These specialized plans include social HMOs,

Evercare, plans for beneficiaries with end-stage renal

disease (ESRD), and plans for dual eligible beneficiaries

offered through both Medicare and Medicaid. The

Program of All-Inclusive Care for the Elderly (PACE) 

was a demonstration program and is now a permanent

program under Medicare and available under Medicaid at

individual state discretion. All of these programs provide

targeted services and care management to their enrollees.

Many observers of these earlier specialized demonstration

plans questioned whether Medicare’s payment method

accurately accounted for the potentially higher costs 

of these specialized populations. Plans and beneficiary

advocates expressed concern that even with risk

adjustment, CMS still might not pay plans accurately 

for beneficiaries who have limitations in activities of daily

living. CMS devised a special payment policy called a

frailty adjuster for some of these demonstration plans 

and for PACE. When MedPAC reviewed the social HMO

program, it suggested that the Secretary investigate the

need for broader payment adjustments for all frail

populations who are enrolled in private plans under

Medicare (MedPAC 2003).

By statute, CMS will pay specialized MA plans the same

way it pays all other MA plans: It will use the bidding

process and the same risk-adjustment factors detailed in

the subsequent sections of this chapter. The frailty adjuster

will not apply to MA plans—although it will continue 

to apply to demonstration plans. The preamble to the 

final MA regulation indicates that in 2006, CMS plans 

to include more diagnoses in its risk-adjustment model.

The broader model should better capture disease burden

among the Medicare population (CMS 2005a). CMS 

also plans to refine its risk-adjustment model over time,

perhaps including a frailty adjuster that the agency can

apply across the entire MA population (not just by type 

of plan)—a policy that MedPAC supports. 

Treatment of existing types of MA plans 

Along with the addition of two new types of plans under

MA, the MMA also made several changes to existing

plans’ participation in Medicare.

The Congress introduced MSAs combined with a highdeductible insurance product to the Medicare program in

the Balanced Budget Act of 1997. The pilot MSA program

was limited both in the number of enrollees permitted to

participate (390,000) and in the length of time during

which insurers could offer such products (the law

permitted no new enrollments after January 1, 2003). 

As a result, no organization decided to offer an MSA 

plan in the Medicare market. The MMA then permanently

removed these limits. However, even setting aside these

constraints, MedPAC concluded that two market

characteristics contributed to the absence of MSA

offerings in the earlier program: 

• little demand from the risk-averse Medicare

beneficiary population because of the high deductible,

and

• the difficulty of marketing a complex new product

(MedPAC 2000). 

However, it is possible that as more beneficiaries 

become accustomed to health savings–type accounts,

high-deductible insurance products in the non-Medicare

market, and high-deductible Medigap products, they 

may become interested in Medicare MSAs as well.

The MMA also introduced health savings accounts

(HSAs) as a health insurance option outside the Medicare

program. Similar to MSAs, these plans combine (a) an

account into which an employer can deposit funds to be

used to pay for health expenses and (b) a high-deductible

plan that limits the holder’s overall financial liability.

Medicare beneficiaries may not make HSA contributions.

However, people who participated in HSAs before 

they became eligible for Medicare may use funds

deposited earlier to pay Medicare Part A, Part B, or 

MA supplemental premiums and to pay (tax free) the

employee share of employer-related supplemental

coverage. Beneficiaries may not use HSA funds to pay 

for Medigap premiums without incurring a tax penalty.

CMS reimburses cost plans for 100 percent of their costs

instead of receiving a fixed monthly payment. Both the

Congress and CMS have considered eliminating cost 

plans from Medicare many times. The plans will be

eliminated starting in 2008, provided that their area

contains at least two MA plans. Risk plans have raised

concerns that cost plans can receive higher payments and

charge their enrollees lower premiums than plans that

accept risk for the full benefit package. These plans enroll

68 The Medicare Advantage p rogram
about 300,000 beneficiaries (another 100,000 are enrolled

in cost plans that provide Part B services only). CMS has

not permitted any new cost plans to join Medicare since

1997, although it has permitted service area expansions for

existing plans. 

Quality

In this section, we review the current situation regarding

quality in MA plans, explore the ability of beneficiaries 

and others to make quality comparisons between the FFS

program and MA plans, and review the requirements for

quality improvement that the MMA and related regulations

lay out. Finally, we look at the role that pay-forperformance might play in improving quality in MA plans. 

What do we know about the quality of

care in MA plans?

One of the ways in which CMS measures the quality of

care for MA plans is through the Health Plan Employer

Data and Information Set (HEDIS). Plans collect data on

HEDIS measures by reviewing administrative claims and

medical charts. Among MA plans, only HMOs report on

all HEDIS measures (MSAs do not report any HEDIS

measures, and PPOs only report those HEDIS measures

that they can assess without reviewing medical charts).

HEDIS measures for HMOs (which cover more than 

90 percent of MA enrollees) indicate that the clinical

effectiveness of care in Medicare plans is generally

improving over time, although some measures continue 

to show low rates (NCQA 2004). While certain MA 

plans generally perform extremely well on the HEDIS

measures, the data on overall plan scores vary

considerably, suggesting that certain plans could work 

to improve their overall quality of care.

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 69

Plans improve, but rates are still low on some measures 

Measure 2000 2001 2002 2003

Advising smokers to quit 59.7% 60.8% 61.5% 63.3%

Beta-blocker treatment after heart attack 89.3 92.9 93.0 92.9

Breast cancer screening 73.9 75.3 74.5 74.0

Cholesterol management

Control 52.9 58.4 62.3 66.7

Screening 70.6 75.5 77.7 81.0

Controlling high blood pressure 46.7 53.6 56.9 61.4

Comprehensive diabetes care

Eye exams 62.8 66.0 68.4 64.9

HbA1c testing 82.5 85.7 85.0 87.9

Lipid control 50.9 57.5 62.6 67.7

Lipid profile 80.5 85.7 87.9 91.1

Monitoring diabetic nephropathy 45.0 51.9 57.3 53.6

Poor HbA1c control* 33.4 26.8 24.5 23.4

Antidepressant medication management**

Acute phase N/A 51.3 52.1 53.3

Continuation phase N/A 36.8 37.7 39.2

Contacts N/A 11.9 10.8 10.5

Follow-up after hospitalization for mental illness

Less than 7 days 37.5 37.2 38.7 38.8

Less than 30 days 59.3 60.6 60.6 60.3

Note: HbA1c (hemoglobin A1c), N/A (not available). Rates refer to patients who received the clinically indicated treatment. 

* Lower rates are better than higher ones for this measure.

** “Acute phase” refers to the percentage of patients who received effective treatment after a new episode. “Continuation” refers to the percentage of patients who 

remained on antidepressants continuously for six months after initial diagnosis. “Contacts” refers to the percentage of patients who received at least three follow-up

office visits in a 12- week acute phase.

Source: National Committee for Quality Assurance 2004.

TABLE

3-2
Data on these HEDIS measures show the rate at which

members who are eligible for the clinical care being

measured receive that care. For example, the measure for

provision of a beta blocker after a heart attack tracks the

number of beneficiaries with a heart attack who received 

a prescription for a beta blocker upon discharge from a

hospital. Care on almost all of the 17 reported measures

improved during the last three years (Table 3-2, p. 69).

Only two measures noticeably declined, and the rest

improved or stayed the same.3 As part of HEDIS, MA

plans also report Health Outcomes Survey (HOS)

measures, which assess MA enrollees’ physical

functioning and mental well-being over time 

(Haffer and Bowen 2004).

As with other measure sets, MedPAC recognizes the

importance of processes that improve and refine quality

measures to ensure that measure sets continuously 

evolve. As performance on some measures reaches a 

high level, CMS needs to support a process that adds 

new dimensions. To avoid unnecessary burdens on plans

and providers, this evolution should use processes that

convene a variety of interested parties to agree on a

standard set of measures. As these new measures emerge,

CMS should also collect them in the FFS program (to the

extent practical).

CMS can also compare quality between Medicare private

plans and FFS by using patient-centered measures of

quality. CMS collects information from beneficiaries on

their perceptions of care while enrolled in MA plans and

in the FFS program through the Consumer Assessment of

Health Plans (CAHPS) survey. Levels of satisfaction with

access, such as getting care when one needs it, are

generally similar for MA and FFS beneficiaries, although

the latter are less likely to report problems in accessing

specialists (Table 3-3). FFS beneficiaries and beneficiaries

enrolled in MA rate their plan and overall health care

similarly. In general, the measures have proven stable 

over time, with the exception that beneficiaries in both

MA plans and the FFS program are reporting declining

overall levels of satisfaction. However, this CAHPS

question is broad and not specific to any type of provider

or service, asking both FFS and managed care participants

to rank their ‘plan’ on a scale of 0 to 10, in which 0 is 

the “worst health plan possible” and 10 is the “best 

health plan possible.”

Comparing quality between FFS 

and MA plans

Although HEDIS measures provide the ability to compare

quality among MA plans, CMS does not routinely publish

the HEDIS measures for the FFS program. Therefore,

apart from the CAHPS survey, quality comparisons

between MA plans and the FFS program are difficult

nationally and locally. CMS does collect information at

the state and national level that permits comparison of 

the FFS program to MA plans on the HEDIS measure,

Access to Ambulatory Health Services (CMS 2005a).

Further, CMS can derive some of the HEDIS measures—

most notably those that PPOs report—from administrative

data. CMS could begin to routinely calculate and publish

HEDIS measures for the FFS program derived from

administrative data. CMS could also explore existing

approaches—and data sources such as those used by

70 The Medicare Advantage p rogram

MA plans and the FFS program have 

similar patient experience scores 

MA plans FFS program

Measure 2001 2002 2003 2001 2002 2003

None or small problem getting care when needed 94% 93% 94% 97% 95% 95%

Usually or always got care quickly 87 81 83 87 81 84

Doctors usually or always communicate well 93 93 93 94 94 94

Rated health care overall 8–10 84 84 84 84 85 86

Rated plan 8–10 77 76 70 78 77 69

None or small problem seeing a specialist N/A 92 92 N/A 95 95

Note: MA (Medicare Advantage), FFS (fee-for-service), N/A (not available).

Source: 2001–2003 Consumer Assessment of Health Plans Survey (CAHPS) data for Medicare Advantage plans and the fee-for-service program from CMS.

TABLE

3-3
quality improvement organizations (QIOs)—that draw

samples of medical records in defined geographic areas in

order to calculate additional HEDIS measures that require

medical record abstraction.

RECOMMENDATION 3B

The Secretary should calculate clinical measures for the

fee-for-service program that would permit CMS to

compare the fee-for-service program to Medicare

Advantage plans.

RATIONALE 3B

In order for beneficiaries to make informed choices

between the FFS program and the array of MA plans, they

need a consistent set of quality measures that they can use

to compare their options. Further, CMS should be able to

compare the two programs’ performance.

IMPLICATIONS 3B

Spending

• This recommendation has no federal budget

implications. CMS should find most measures

relatively easy to implement by using analyses of

existing claims data. Some measures might require

additional resources—particularly if they require 

the creation of new, or the expansion of current,

survey instruments.

Beneficiaries and providers

• Beneficiaries will have an additional set of

comparisons on which to evaluate the FFS program

and MA plans; this new data source will foster

competition between the two programs. 

CMS does not collect the measures that MA plans 

collect as part of the HOS for the FFS program. CMS

administered a version of the HOS to 10 subsamples of 

the Medicare FFS population in 1998 (Pope et al. 2000),

but this was on a pilot basis and the agency has no plans

for further data collection in the FFS program. CMS can

potentially use the HOS as a tool for comparison between

MA plans and the FFS program. However, the HOS also

has limited clinical information, relying on self-reported

measures of health and functional status.

In its March 2005 report, MedPAC recommended that

CMS develop measures of physicians’ processes of care

using claims data (enhanced by pharmacy and laboratory

data) for a physician pay-for-performance program

(MedPAC 2005). As CMS develops these clinical measure

sets for FFS, the agency may learn that these sets allow

better comparison between the quality of care for

Medicare beneficiaries in private plans and for those 

in the FFS program. 

What are the requirements for 

quality programs?

The MMA and related CMS regulations specified certain

quality requirements and measures for the MA program.

In general, the requirements that CMS imposed on MA

plans are considerably less prescriptive than they were

under the old M+C program. Under M+C, plans adhered

to a defined list of requirements that its quality assurance

plan should address and were required to participate in

national or statewide quality assurance and performance

improvement projects. CMS replaced these requirements

with the following new ones:

• Each MA plan (other than a PFFS plan or an 

MSA plan) must have an ongoing quality

improvement program.

• Each quality improvement program must include a

chronic care improvement program.

• Each MA plan must provide for the collection,

analysis, and reporting of data that permit CMS 

to measure health outcomes and other indices 

of quality (CMS 2005a).4

The specific type of quality improvement approach and

the sets of measures that plans will collect will vary by

type of plan (Table 3-4, p. 72). For example, all plans 

must maintain a health information system. But MSA and

PFFS plans do not have to institute a quality (or chronic

care) improvement program. CMS will allow some

variation in measure reporting for HMOs and PPOs, 

at least in the early stages of the MA program. CMS

expects to collect measures from HEDIS, CAHPS, and 

the HOS for both HMOs and PPOs. However, the HEDIS

measures will vary: PPOs will not have to submit HEDIS

measures that require medical record review. CMS

indicates that it expects to move to the same measures

over time, as PPOs build the capacity to report 

measures derived from medical records.

SNPs that target institutionalized beneficiaries will not

report on HEDIS and HOS measures. Instead, these plans

will report on measures similar to those on which longterm care facilities report in the Nursing Home Compare

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 71
database. CMS expects to derive these measures from the

Minimum Data Set (MDS) that the agency requires of

nursing facilities.

Should MA plans have 

pay-for-performance standards?

In its March 2004 report, MedPAC concluded that

Medicare should introduce pay-for-performance

incentives to provide high-quality care in the MA program

because MA meets all the Commission’s criteria for

successful implementation (MedPAC 2004c). CMS

collects standardized, credible performance measures on

all MA plans. Every year, plans collect data on specific

clinical process measures and data that reflect members’

satisfaction with the plan’s service provision. Together,

these data show a widely accepted, broad cross-section 

of plan quality. Most of the process measures in these 

data sets do not require risk adjustment, and CMS has

developed risk adjusters for the satisfaction measures.

Plans have developed various strategies to improve their

scores on these measures by working with providers 

in their networks. 

MedPAC has argued that by including all private plans in

a pay-for-performance program, CMS would maintain a

level playing field between plan types and simultaneously

reward those plans that invest in improving quality. CMS

would not require plans to report on all measures, but the

plans would not receive pay-for-performance funds if they

opted not to do so. Later in this chapter, we discuss how

the mechanics of a pay-for-performance system might

work within the structure of the current bidding system.

Enrollment

The MMA deals with several issues related to enrollment

in MA plans, including:

• implementing an annual open enrollment process; and

• permitting beneficiaries who have ESRD to join

specialized MA plans—should a specialized plan 

exist that covers those who have ESRD—while

continuing to prohibit beneficiaries who have 

ESRD from enrolling in other MA plans.

Coordinated annual open 

enrollment period

The MA program moves private-plan enrollment to an

annual process, starting in 2006. Previously, beneficiaries

could enroll and disenroll on a month-to-month basis—

a provision that could limit a plan’s ability to provide

enrollees with coordinated care. Now, beneficiaries who

elect to enroll in MA plans will generally have only a

single opportunity each year to switch plans or return to

the FFS program. In 2006, beneficiaries will have a sixmonth window at the beginning of the year during which

they may switch plans; in 2007 and thereafter, they will

have a three-month window. If beneficiaries do not elect

to change within this window, they will need to stay in

their current plan until the end of the calendar year.

During the annual open enrollment period, beneficiaries

choose whether to join an MA plan and whether to buy

into Part D for drug coverage. (Later in this chapter, we

72 The Medicare Advantage p rogram

Selected quality requirements and measures 

vary by type of Medicare Advantage plan 

Quality Quality Health

improvement HEDIS improvement information

Type of plan program measures projects system

Local plan: HMO ✓ All ✓ ✓

Local plan: PPO ✓ Some ✓ ✓

Specialized plan ✓ Depends on ✓ ✓

target enrollees

Regional PPO ✓ Some ✓ ✓

PFFS ✗ Some ✗ ✓

MSA ✗✗ ✗ ✓

Note: HEDIS (Health Plan Employer Data and Information Set), MSA (medical savings account), PPO (preferred provider organization), PFFS (private fee-for-service). 

Source: CMS 2005a.

TABLE

3-4
discuss the rules about which types of plans must offer

Part D coverage.) As is the case with Part B, beneficiaries

who do not enroll in Part D during open enrollment will

pay a penalty. This penalty is based on the number of

months they delay enrolling in Part D after they are

eligible and whether they are enrolled in the FFS 

program or in a private plan. Beneficiaries will pay 

this penalty every remaining month in which they are

enrolled in the Part D program.

CMS will need to dedicate resources to explain these 

new enrollment rules to beneficiaries who are making

changes, particularly changes among MA plans. For

example, beneficiaries who choose a private plan will

need to understand that (a) in order to receive the

prescription drug benefit, they will need to enroll in the

MA plan that offers prescription drug coverage and 

(b) they cannot enroll in an MA plan that does not offer

prescription drug coverage (unless they are enrolled in 

a PFFS plan). Beneficiaries will also likely experience

confusion regarding the decreasing window of time in

which they may switch among MA plans.

Medicare beneficiaries who have ESRD 

The MMA generally continues to prohibit beneficiaries

who have ESRD from enrolling in MA plans. However,

CMS does permit beneficiaries who are enrolled in MA

plans and later develop ESRD to remain in their plans.

Beneficiaries who have ESRD are allowed to join

specialized MA plans (which we discussed earlier in 

this chapter) if these plans choose to admit them.

CMS has improved its risk-adjustment system for

beneficiaries who have ESRD: The agency designed a

new risk-adjustment system specifically for ESRD

beneficiaries who are receiving dialysis. This model

should perform much better than the current demographic

risk-adjustment system; therefore, payments to plans will

more accurately reflect the costs of treating these

beneficiaries. Despite CMS’s general prohibition on

enrollment of these beneficiaries in MA plans, evidence

from a recent demonstration showed that quality of care

for ESRD patients in M+C plans was good. Most

participants’ quality of care and outcomes equaled or

exceeded those of ESRD patients enrolled in the FFS

program (The Lewin Group 2002).

MedPAC has recommended that CMS allow ESRD

beneficiaries to enroll in plans once the agency has

implemented adequate risk adjustment. CMS should 

allow all beneficiaries to choose private plans, provided

that payment is accurate. Further, many private plans 

offer care coordination and disease management services

that may benefit these beneficiaries, as they often have

multiple chronic conditions in addition to ESRD—such as

diabetes, congestive heart failure, and hypertension.

Benefits

The MMA added voluntary outpatient prescription drug

coverage for all Medicare beneficiaries, including those

who are enrolled in MA plans. Medicare subsidizes drug

coverage through the combination of a direct subsidy of

the premium and reinsurance, and beneficiaries pay a

portion of the premium that increases with the plan’s 

bid. In this section, we discuss the implications of the

Medicare program paying MA plans to provide

prescription drug coverage.

Coverage of drugs under MA

Most types of local and regional MA plans must offer 

at least one benefit package, including coverage under 

Part D (although they may offer packages that do not

cover Part D, as well). PFFS plans may offer Part D

coverage, and MSA plans may not.

MA plans that offer drug coverage under Part D

(MA–Prescription Drug [MA–PD] plans) must meet the

same program requirements as prescription drug plans

(PDPs). Similar to PDPs, MA–PDs participate in the Part

D bidding process to set their premiums. They may use

any savings they achieve from bidding on the furnishing

of Part A and Part B services (which we detail later in this

chapter) to lower beneficiaries’ Part D premiums or to

enhance the Part D benefit. In enhancing the benefit, 

MA plans might cover drugs that Part D does not, or 

MA plans might reduce the deductible, cost sharing, 

or initial coverage limit.

Some MA plans would like to help their enrollees by

filling in the coverage gap—that is, the portion of drug

spending that falls above the initial coverage limit and

below the catastrophic cap of Part D’s benefit (see 

Chapter 1). For an individual without drug coverage 

that supplements Part D, this coverage gap could amount

to high out-of-pocket spending—up to $2,850 in 2006.

Thus, a benefit that fills in the coverage gap would likely

be attractive to Medicare beneficiaries. But under a feature

of Part D that the Congress designed to direct more federal

subsidies toward beneficiaries who do not have

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 73
supplemental coverage (called the true out-of-pocket

provision), only certain types of spending on behalf of 

the enrollee counts toward the enrollee’s catastrophic

threshold. In particular, most types of supplemental

coverage would not count. In other words, every dollar of

supplemental coverage that an enrollee receives would

raise the level of drug spending at which that individual

would qualify for Part D’s catastrophic protection and

federal reinsurance subsidies.

CMS recently announced that it will conduct a

demonstration allowing both PDPs and MA–PD plans to

fill in the coverage gap and still receive the reinsurance

payments (CMS 2005c). In one option, CMS would allow

either type of plan to receive their estimated reinsurance

payment through a capitated payment. In the other option,

CMS would allow only MA–PD plans to take rebate 

funds from the Part A and Part B bidding process and

apply them to an enhanced drug benefit, then count 

this supplemental coverage toward the out-of-pocket

spending limit. These MA–PD plans then would

presumably receive reinsurance payments following the

usual schedule. CMS will provide additional information

about this demonstration in the future; the agency intends

the demonstration to be budget neutral.

The MA bidding process for 2006

Beginning in 2006, private plans will submit formal 

bids to participate in the MA program. The Medicare

program will pay plans based on their bids rather than on

administratively set rates, although CMS will compare the

bids to administratively set benchmarks to determine how

much of the payment will come from Medicare and how

much will come from beneficiary premiums. The bids are

due to CMS by the first Monday in June each year. 

Components of a plan’s bid

Every plan will submit a separate set of bids to cover

beneficiaries in each of their service areas. Each bid will

consist of up to three separate components:

• The bid for all Medicare Part A and Part B benefits

(except hospice). This portion of the bid must assume

that the plan would collect the standard Medicare cost

sharing from its enrollees. This bid is standardized to a

nationally average beneficiary (a CMS risk factor of

1.0) enrolled in the plan’s service area. 

• The bid for supplemental benefits (if any) that the plan

covers. Supplemental benefits may include lower cost

sharing on Medicare services, as well as benefits that

FFS Medicare does not cover.

• The bid for the Medicare Part D drug benefit 

(if offered).

The first component, the Part A/B bid, is the only

component CMS uses to determine Medicare’s payments

to the plan for the standard Medicare nondrug benefits.

CMS compares each plan’s Part A/B bid with a

benchmark. (See text box for the methods CMS uses 

to set benchmarks.)

How does CMS determine payment? 

CMS will base the Medicare payment for private plans on

the relationship between their bids and the benchmarks. 

If the plan’s bid falls above the benchmark, then the plan

receives the benchmark and the enrollees will have to pay

an additional premium that equals the difference between

the bid and the benchmark. If the plan’s bid falls below the

benchmark, the MMA defines the difference as the plan’s

savings. The Medicare program retains 25 percent of the

savings (if it is a regional plan, CMS places half of this 

25 percent into the regional PPO stabilization fund), and

the plan receives the other 75 percent of the savings as a

rebate. The plan must then return the rebate to its enrollees

in the form of supplemental benefits or lower premiums.

The plan can apply any premium savings to the Part B

premium (in which case the government retains the

amount for that use), to the Part D premium, or to the

premium for the total package that may include

supplemental benefits.

The easiest way to illustrate the effects of the bidding

process on beneficiaries’ choices is to assume that the 

plan returns the entire rebate in the form of a reduction in

the Part B premium (Table 3-6). This example shows the

effects of returning the rebate to beneficiaries. If the rebate

exceeds the Part B premium, which is a possibility, the

plan would have to provide some of the rebate in the form

of supplemental coverage (including reduction of the 

Part D premium).

Payments to regional plans will differ from

payments to local plans

For regional MA plans, CMS bases the regional

benchmark on the number of eligible Medicare

beneficiaries in each county. However, when a regional

74 The Medicare Advantage p rogram
Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 75

How does CMS set benchmarks?

The benchmark is a bidding target. CMS sets 

the benchmarks administratively, but in the 

case of regional PPOs, plan bids influence the

benchmarks. Under MMA, CMS sets the benchmarks

for local plans at the county-level payment rates used to

pay MA plans before 2006. Generally, the law directs

CMS to update the benchmarks each year by the

national growth rate in per capita Medicare spending.5

If a local MA plan serves a multicounty area, the

benchmark against which it bids consists of an average

of the different benchmarks for the counties it serves,

weighted by its projected enrollment from each county.

CMS determines the benchmarks for the MA regional

PPOs by using a more complicated formula that

incorporates the plan bids. A region’s benchmark is 

a weighted average of the average county rate and the

average plan bid. As directed by the MMA, CMS

computes the average county rate as the individual

county rates weighted by the number of Medicare

beneficiaries who live in each county—not by the

plan’s projected enrollment, which CMS uses as the

weighting for local plans. The average plan bid is 

each plan’s bid weighted by each plan’s projected

number of enrollees. CMS then combines the average

county rate and the average bid into an overall average.

In calculating the overall average, the average bid is

weighted by the number of enrollees in all private plans

across the country, and the average county rate is

weighted by the number of all Medicare beneficiaries

who remain in FFS Medicare. 

For example, suppose that 1 million Medicare

beneficiaries live in the region, in one of two local 

MA payment areas (Table 3-5). Local area 1 contains

800,000 beneficiaries and has a local MA payment rate

of $900. Local area 2 has 200,000 beneficiaries and a

rate of $600. Thus, the average county MA rate is $840

(0.8 x 900 + 0.2 x 600). Assume that the average plan’s

Part A/B bid was $715 and that nationally, 20 percent

of Medicare beneficiaries were enrolled in MA plans.

The regional benchmark under these assumptions

would be $815 (0.8 x 840 + 0.2 x 715). 

Example of calculating 

a regional benchmark 

Number of Average

Beneficiaries rate or bid

Local MA payment area 1 800,000 $900 

Local MA payment area 2 200,000 600 

Average MA rate N/A 840 

Average regional plan bid N/A 715

Regional benchmark $815 

Note: MA (Medicare Advantage), N/A (not applicable). This example 

assumes a national Medicare Advantage penetration of 20 percent 

of Medicare beneficiaries.

TABLE

3-5

Example of premium calculations under 2006 bidding process 

Part B Premium Total

Plan Bid Benchmark premium rebate premium

FFS N/A $1,000 $100 $0 $100.00 

Plan 1 $950 1,000 100 37.50 62.50 

Plan 2 900 1,000 100 75.00 25.00 

Note: FFS (fee-for-service), N/A (not applicable).

TABLE

3-6
PPO bids, it takes into account where it projects its

enrollment will originate. Averaging over all members, 

the PPO will receive its bid plus any rebate. As a result,

two regional plans that are bidding the same amount in 

the same region would get different Medicare payments 

in the same county if their enrollment patterns among all

counties in the region differ. The reason is because their

bid is based on their average cost over all beneficiaries

they serve, yet the benchmark is not.

For local plans, CMS bases the benchmarks and plan 

bids on a plan’s projected enrollment. This difference in

treatment between local and regional plans could create a

situation in which local plans are disadvantaged relative to

regional plans in some counties (see text box for example).

Many policy and industry observers thought that the

MMA included a geographic adjustment that would better

align regional plans’ bids to the benchmarks. However, the

final regulation did not include an adjustment for this

issue. Instead, it takes into account differences between

projected and actual enrollment.

To ensure more equal competition among regional plans

and between regional and local plans, the Commission

makes the following recommendation:

RECOMMENDATION 3C

The Congress should clarify that regional plans should

submit bids that are standardized for the region’s

Medicare Advantage–eligible population. 

RATIONALE 3C

The MMA requires that CMS adjust plan payments for

health risk and MA local payment rates. CMS standardizes

the benchmarks for risk and local MA payment rates;

therefore, CMS should require that plans standardize their

bids for risk and local payment rates. In not doing the

parallel adjustment, the payment system may cause

regional plans to have a competitive advantage over 

local plans in certain areas.

IMPLICATIONS 3C

Spending 

• This recommendation would likely decrease Medicare

spending relative to current law by $200 million to

$600 million over one year, and by $1 billion to $5

billion over 5 years. 

Beneficiaries and plans

• This recommendation could lower payments to

regional plans under some circumstances. Therefore,

this recommendation may cause regional plans 

to reduce the generosity of benefits or reduce the

extent of their participation in the MA program.

However, some regional plans (namely those that

have disproportionately high enrollment from 

high-rate areas) would benefit from the payment

recommendation, and the recommendation could

prevent some local plans from leaving certain markets.

Financial neutrality and private plans

The Commission has long supported giving Medicare

beneficiaries a choice in health care delivery systems,

provided that such choices do not increase Medicare

program expenditures. Private plans have the flexibility 

to use care management techniques that FFS Medicare

does not encourage, and they have greater incentive to

innovate. Thus, for some beneficiaries in some parts of 

the country, private plans may provide the same Medicare

benefits with fewer resources, more benefits with the same

resources, or higher quality than the FFS Medicare

program.6 If beneficiaries are able to choose between

Medicare FFS and an array of private plans—and if the

Medicare program pays the same on behalf of the

beneficiaries making the choice—then over time,

beneficiaries will gravitate either to the FFS system or to

the plan that provides the best value in terms of efficiency

and quality. The Medicare program would not subsidize

one choice more than another. The Medicare program

should be financially neutral regarding whether the

beneficiary chooses to remain in the FFS system or enroll

in a plan. This neutrality provides beneficiaries with the

incentive to select the system that they perceive has the

highest value, while maintaining their ability to choose a

more generous plan by paying additional premiums.

With plans competing for Medicare enrollment, individual

providers would want to improve the quality and

efficiency of their services so that these providers can 

stay in the plans’ preferred networks. In addition, if a

provider follows the best practices of one payer, the

provider’s behavior may translate into better practice 

for all payers with which the provider participates.

Previous system was not financially neutral

Through 2005, Medicare will pay plans based on

administratively set rates that are county based and

partially risk adjusted. The formula that governs the rates

76 The Medicare Advantage p rogram
is only loosely based on county FFS costs.7 Although the

formula ensures that plan payments will not fall below

FFS costs, rates in individual counties are as high as 85

percent above FFS cost, as measured by the adjusted

average per capita cost (AAPCC). 

Current plan payment rates average 107 percent of county

FFS costs. The plans’ payment rate advantage has come

primarily from two sources. One is the result of two 

“floor rates” that the Congress created to raise the rates 

in low-rate counties. One floor rate, which mostly applied

in rural areas and small cities, was often well above the

comparable county FFS costs. Only 3 percent of plan

enrollees live in these areas, but rates average 123 percent

of the county FFS costs. Another 26 percent of plan

enrollees live in large metropolitan areas where the

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 77

Payments to local and regional MA plans may differ

I

n this simplified example, two payment areas

exist—one low-rate and one high-rate—with local

MA payment rates of $600 and $900 per month,

respectively. We assume the local plan in each

payment area bids $100 below its benchmark rate 

and gets paid the bid amount plus a $75 rebate.

A regional plan that serves both areas also bids $100

below its benchmark. In the example, 20 percent of 

the eligible population lives in the low-rate area and 

80 percent lives in the high-rate area. The resulting

benchmark is $815 (as computed in the text box on

page 75). Therefore, the regional plan will get, on

average, $715 (the benchmark minus $100) plus 

the $75 rebate—or $790.

The payments to a regional plan in each area will

depend on how its enrollee population splits between

the two areas relative to the benchmark split of 20/80. 

If the projected enrollment for the plan splits evenly

between the low- and high-rate areas (50/50), the

payments for members in the two areas will be $647 

in the low-rate area and $933 in the high-rate area. 

The average will be $790.

Figure 3-5 shows the result. The dark bars represent 

the payment rates for local plans, and the light bars

represent the payment rates for the regional plan

members in the two areas. Note that in both areas, 

the regional plan receives a higher rate, which would

presumably give it a competitive advantage over the

local plans in both areas.

Regional plans that have different mixes of projected

enrollment will see different payments from one

another. The plan in the example above, with the

enrollment split 50/50, has an advantage over local

plans in both areas. A plan that has a 10/90 split would

be disadvantaged in both areas relative to local plans 

and would be disadvantaged more relative to the 

50/50 regional plan shown in the figure. 

A regional plan with a split of 20/80—identical to 

the underlying population mix—would have a slight

advantage in the low-rate area and a slight disadvantage

in the high-rate area. This asymmetry results from a

different cause: The rebate is identical in both areas and

thus constitutes a larger proportion of total plan payment

in the low-rate area than in the high-rate area. 

P

ayment to pl

a

n

$1,000

800

600

400

200

0

Low-rate area High-rate area

Local plan Regional plan 

Rate area definition

$790

Average regional plan payment

Note: In this example, 20 percent of Medicare beneficiaries in the region live

 in low-rate areas and 80 percent live in high-rate areas. The regional 

 plan enrolls 50 percent of its members from low-rate areas and 

 50 percent from high-rate areas.

Example of payments to plans

with different enrollment patterns

FIGURE

3-5
Congress created a higher floor rate. Payments in those

areas averaged 116 percent of the county FFS costs. 

The other main source of higher rates is Medicare’s

treatment of indirect medical education (IME) payment 

to hospitals. For the 40 percent of plan enrollees who live

in counties where the MMA raised the rate to 100 percent

of county FFS costs, the rates actually are higher than the

comparable cost in FFS Medicare. The reason is that the

measure the MMA used in that calculation includes

spending for IME payments to hospitals, even though 

the Medicare program continues to make separate IME

payments to hospitals on behalf of MA enrollees. In effect,

the Medicare program is making IME payments on behalf

of MA enrollees twice: once to the MA plans, and once 

to the teaching hospitals. 

On the other hand, the AAPCC might underestimate 

the cost of Medicare services that beneficiaries receive

because some beneficiaries receive services from

Department of Veterans Affairs’ (VA) facilities that

Medicare would otherwise cover. The Congress instructed

CMS to add the cost of these services when calculating

county AAPCCs, but the agency has not been able to do

so yet. We urge CMS to implement the VA adjustments 

as soon as possible. Note that the Congress had instructed

that the calculation include Department of Defense (DoD)

spending, but because of major changes to DoD

supplemental coverage, we expect very few beneficiaries

with DoD coverage to have lower use of Medicare

benefits due to their use of DoD facilities.

In the future, all local benchmarks will increase at the

same national growth rate (or by 2 percent, if the national

growth rate is lower than 2 percent) using the result of

earlier formulas as the base rate. The exception is that

counties which fall below 100 percent of their AAPCC

will see their rates rise to the 100 percent level.8

Financial neutrality under the 2006

bidding system

The 2006 bidding process will create a hybrid system 

that includes administratively set payment rates and

competitive bidding. Although administratively set plan

payment rates will no longer exist per se (except for MSA

plans), Medicare will still have administratively set

benchmarks, against which the plans will bid. 

This process, as currently configured, will not result in

Medicare making financially neutral payments relative to

FFS cost. As we discussed earlier, the benchmarks are

often well above the AAPCC. Therefore, plans bidding 

at or above the benchmark would often receive payments

in excess of the local cost of FFS Medicare. Plans 

bidding below the benchmark will receive less than the

benchmark, but the resulting payment might be higher or

lower than the local cost of FFS Medicare. One way the

system could be financially neutral is if the benchmarks

were more reflective of the cost of FFS Medicare, and if

Medicare used program savings from bids below the

benchmarks to encourage quality-of-care improvement.

However, Medicare could take other approaches to

adjusting total payments so that payments to plans in 

the aggregate do not exceed FFS Medicare.

Adjusting the bidding system for

consistency with the financial 

neutrality principle

The benchmarks currently average about 107 percent 

of FFS Medicare costs for plan enrollees. About two

points of the seven-point difference are due to the

treatment of IME payment to hospitals. In our 

March 2002 report, MedPAC supported Medicare’s

removal of graduate medical education costs from plan

rates and direct payments to teaching hospitals that treat

plan members. The Commission wanted to help ensure

that plans have incentives to direct enrollees to use

teaching hospitals when appropriate. With that goal in

mind, we recommend removing the effect of IME

payments from the benchmarks to bring the system 

closer to financial neutrality.

RECOMMENDATION 3D

The Congress should remove the effect of payments 

for indirect medical education from the Medicare

Advantage plan benchmarks.

RATIONALE 3D

In removing the effect of these payments from the

benchmarks while continuing to make payments directly to

teaching hospitals on behalf of plan members, the Congress

would bring the system closer to financial neutrality and

would not change plan incentives to use teaching hospitals.

The recommended action would also correct Medicare’s

double payment for these teaching costs.

78 The Medicare Advantage p rogram
IMPLICATIONS 3D

Spending

• This recommendation would decrease Medicare

spending relative to current law by $200 million to

$600 million over one year and would decrease

spending by $1 billion to $5 billion over five years.

Beneficiaries and plans

• This recommendation would lower payments to plans

in some areas. This result, in turn, may cause some

plans to reduce their level of participation in the MA

program—and thus reduce plan choice for some

beneficiaries. Plan incentives to use teaching hospitals

would not change.

Reaching financial neutrality under the

current system

The Commission has previously recommended that

Medicare set plan payment rates at 100 percent of local

FFS costs. In 2006, a parallel recommendation might be 

to set the benchmarks against which plans will bid at 

100 percent of local FFS Medicare costs, to ensure that 

the Medicare program does not pay MA plans more than

the cost of covering the same beneficiaries under FFS

Medicare. However, even this parallel recommendation

would not result in financial neutrality because under the

new bidding system, plans have the incentive to bid lower

than the benchmark—with Medicare keeping part of the

savings. Thus, the payment system would not be

financially neutral because Medicare would pay (to plans

that bid less than the benchmark) less than the county 

FFS rate. MedPAC has also recommended that payment

policy provide stronger incentives for plans to improve 

the quality of care that they provide to Medicare

beneficiaries (MedPAC 2004a). One solution would be to

set benchmarks at 100 percent of FFS costs in each area

and return any Medicare savings from bids below the

benchmarks to the plans. Medicare would return the

savings in the form of pay-for-performance payments

based on quality measures. 

However, financial neutrality is just one goal of payment

policy. The Commission recognizes that the Congress may

not achieve its wish of attracting plans to more areas of 

the country if it immediately begins reducing benchmarks

in many areas. Also, the MA bidding process is just

beginning, and MedPAC does not want to derail the

system with sharp changes in expected payment rates. 

Moreover, the bidding process might produce instructive

results. Perhaps CMS could adjust benchmarks in

response to the level of bidding in such a way that

benchmarks would be at 100 percent of FFS costs, on

average. As long as the result appears stable, Medicare

could maintain overall financial neutrality and fund

performance payments with the savings relative to FFS

costs. Under either scenario, if the bids are substantially

lower than FFS costs, the Commission may suggest that

some of the savings should fund a quality pool and the rest

should return to the Treasury.

The following recommendation strives to achieve financial

neutrality and improve quality through two steps:

• Step 1: Set the benchmarks to 100 percent of the

costs of FFS Medicare, on average. One way 

the Congress can accomplish this part of the

recommendation would be to set the benchmarks 

for each payment area equal to the costs of FFS

Medicare in the area. However, it is possible to use

other formulations or adjustments so that benchmarks

increase in areas that have trouble attracting plans and

decrease in areas where plans are able to bid below the

benchmarks, while keeping the average benchmark at

100 percent of FFS cost.

• Step 2: Reward quality by redistributing savings

from bids below the benchmarks back to the plans in

the form of pay-for-performance payments. 

When a plan bids below the benchmark, the plan

would receive its bid and retain 75 percent of the

difference to rebate to its enrollees. Medicare would

place the remaining 25 percent of the savings in a

quality pool and redistribute it to plans as a reward for

high or improving measures of quality performance.

(The Commission also continues to support placing 

1 to 2 percent of base MA payments into a quality

pool, so that the savings contributions to the pool

would be in addition to the initial 1 to 2 percent.)

RECOMMENDATION 3E

The Congress should set the benchmarks that CMS uses

to evaluate Medicare Advantage plan bids at 100

percent of the fee-for-service costs. 

At the same time, the Congress should also redirect

Medicare’s share of savings from bids below the

benchmarks to a fund that would redistribute the

savings back to Medicare Advantage plans based 

on quality measures. 

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 79
RATIONALE 3E

On average, the Medicare program would pay the same

amount for a beneficiary’s enrollment in an MA plan as

Medicare would expect to pay to cover the beneficiary in

FFS Medicare. Plans would also have increased incentive

to improve their quality scores in order to receive these

quality incentive payments.

IMPLICATIONS 3E

Spending

• If fully implemented for 2006, this recommendation

would decrease Medicare spending by more than $1.5

billion over one year and by more than $10 billion

over five years, relative to current law. More gradual

implementation would decrease savings.

Beneficiaries and plans: 

• This recommendation would decrease the average

payment to MA plans, but some plans may receive

higher payments through pay-for-performance

payments.

• It is likely that some plans would choose not to

participate in some areas, thus leaving some

beneficiaries with fewer choices.

• Plans would have greater incentives to improve

quality, which could then lead to better quality of 

care for beneficiaries.

Concerns about hold-harmless

modifications to payments under 

risk adjustment

Beginning in 2004, CMS has been transitioning from risk

adjusting plan payments based on a demographic model to

adjusting payments based on a health-risk model (see

Chapter 2 for details on the models). For 2004, 2005, and

2006, CMS estimated that aggregate plan payments

adjusted with the health risk model would be lower than

payments adjusted with the demographic model. CMS is

applying proportional increases to county payment rates so

that in aggregate, total plan payments are held harmless

for the effect of switching from the demographic model to

the health-risk model. The net effect of this policy is that

aggregate payments to MA plans are equal to what they

would be if CMS adjusted 100 percent of payments using

the demographic system, although payments to individual

plans will still vary based on their specific risk scores. 

The President’s most recent budget proposal includes a

phase-out of this hold-harmless policy from 2007 to 2010.

The effect of the phase-out would be to increase riskadjusted payments by progressively smaller proportions

from 2007 through 2010, and to completely eliminate the

policy in 2011. Despite the phase-out, this policy increases

payments above levels assumed by the Administration.

The President’s proposed budget indicates that under the

planned phase-out, federal spending from 2006 through

2010 would be $8.3 billion above the level that would

occur if CMS did not increase MA payments above riskadjusted levels.

Whether CMS continues this policy in full force or phases

it out, any policy that increases risk-adjusted payments

prevents risk adjustment from addressing risk-profile

differences between beneficiaries in the MA and FFS

programs. The ultimate effect is that payments for MA

enrollees will be systematically higher than payments for

those same beneficiaries if they enrolled in FFS Medicare. 

MedPAC and its predecessor Commissions have strongly

supported CMS’s adoption of more accurate risk

adjustment as a necessary step toward achieving the goal

of financial neutrality. Increasing plan payments (as CMS

has done) to offset the effect of more accurate risk

adjustment is inconsistent with the Commission’s view on

payment equity. However, at this point, the Commission

recognizes that payment reductions—resulting from

removing the hold-harmless policy immediately—would

be steep. In addition, some plans claim that they have 

not yet fully succeeded in collecting all the diagnostic

information that feeds into the health-risk model, because

some physicians are not accustomed to reporting it to

plans. These plans believe that their payments under the

new system do not reflect their enrollees’ true health 

risk. Therefore, the Commission supports putting the

Administration’s phase-out of the hold-harmless policy

contained in the 2006 budget proposal into law.

RECOMMENDATION 3F

The Congress should put into law the scheduled 

phase-out of the hold-harmless policy that offsets 

the impact of risk adjustment on aggregate payments

through 2010.

RATIONALE 3F

MedPAC and its predecessor Commissions have 

strongly supported CMS’s adoption of more accurate risk

adjustment as an important step toward achieving payment

equity between the Medicare FFS program and private

plans in Medicare. Increasing plan payments to offset the

80 The Medicare Advantage p rogram
effect of more accurate risk adjustment is inconsistent 

with the Commission’s views on payment equity. The

President’s budget indicates an intended phase-out of this

policy from 2007 through 2010, and the Commission

supports that schedule. 

IMPLICATIONS 3F

Spending

• This recommendation would decrease Medicare

spending by more than $10 billion over five years

relative to current law.

Beneficiaries and plans

• Because the President’s budget includes this holdharmless policy, plans are likely to expect the

resulting per member payment levels and should not

change their offerings to beneficiaries. 

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 81
1 The PFFS program allows private plans to offer Medicare

benefits to enrollees without restricting them to a network of

providers. PFFS plans reimburse providers using the same

payment rates that apply in the traditional Medicare FFS

program (MedPAC 2004a).

2 Balance billing refers to the practice of making patients pay

for any difference between a provider’s full charge and a

health plan’s (in this case, Medicare’s) payment. 

3 The eye exam and kidney screening measures had

specification changes in 2003 that required more frequent

screening for certain patients. These changes are likely

responsible for the observed decreases in the measure rates.

4 The health information system requirements for the 

MA plans are very general: Plans must maintain health

information systems that collect, analyze, and integrate data

necessary to implement their quality improvement programs;

ensure that the information they receive from providers is

reliable and complete; and make all collected information

available to CMS.

5 CMS must rebase the county benchmarks at least every three

years. Rebasing will lift those benchmarks that are below the

AAPCC to the county AAPCC.

6 As discussed earlier, CMS does not provide measures that

permit comparison of private MA plans with the FFS

Medicare system.

7 Medicare uses the adjusted average per capita cost (AAPCC)

as its formal measure for setting rates (see Chapter 2 of this

report for further discussion of this measure). The AAPCC

rate is a risk-adjusted county-level measure and hence

directly reflects local per capita spending in the FFS sector. 

8 As noted earlier (endnote 5), CMS may not compare rates to

the AAPCC every year.

82 The Medicare Advantage p rogram

Endnotes
Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 83

Centers for Medicare & Medicaid Services, Department of Health

and Human Services. 2005a. Medicare program: Establishment of

the Medicare Advantage program. Final rule. Federal Register

70, no. 18 (January 28): 4588–4741.

Centers for Medicare & Medicaid Services, Department of Health

and Human Services. 2005b. Medicare beneficiaries to see bigger

savings with Medicare Advantage plans than ever before.

http://www.cms.hhs.gov/media/press/release.asp?Counter=1411.

Centers for Medicare & Medicaid Services, Department of Health

and Human Services. 2005c. Advance notice of methodological

changes for calendar year (CY) 2006 Medicare Advantage (MA)

payment rates. Baltimore: CMS. February 18.

Centers for Medicare & Medicaid Services, Department of Health

and Human Services. 2004. Principles for establishing Medicare

Advantage regions to maximize access to high-quality regional

plans. http://www.cms.hhs.gov/medicarereform/mmaregions/

prinma.pdf.

Haffer, S. C., and S. Bowen. 2004. Measuring and improving

health outcomes in Medicare: The Medicare HOS program.

Health Care Financing Review 24, no. 4: 1–3.

Inside Washington Publishers. 2005. Most PPO regions receive

plan applications, including key mid-west area. Inside CMS 8, 

no. 8: 1.

Medicare Payment Advisory Commission. 2005. Report to the

Congress: Medicare payment policy. Washington, DC: MedPAC.

Medicare Payment Advisory Commission. 2004a. A data book:

Health care spending and the Medicare program. Washington,

DC: MedPAC.

Medicare Payment Advisory Commission. 2004b. Report to the

Congress: Medicare payment policy. Washington, DC: MedPAC.

Medicare Payment Advisory Commission. 2004c. Report to the

Congress: Benefit design and cost sharing in Medicare

Advantage plans. Washington, DC: MedPAC.

Medicare Payment Advisory Commission. 2003. Report to the

Congress: Social health maintenance organization (S/HMO):

Recommendations for the future of the demonstration.

Washington, DC: MedPAC.

Medicare Payment Advisory Commission. 2001. Report to the

Congress: Medicare in rural America. Washington, DC:

MedPAC. 

Medicare Payment Advisory Commission. 2000. Report to the

Congress: Medical savings accounts and the Medicare program.

Washington, DC: MedPAC. 

National Committee for Quality Assurance. 2004. The state of

health care quality: Industry trends and analysis. Washington,

DC: NCQA.

Pope, G. C., and M. Griggs, and N. McCall. 2000. Comparison of

the health status of Medicare fee-for-service and managed care

enrollees using the Health Outcomes Survey. Waltham, MA:

Health Economics Research, Inc. 

The Lewin Group. 2002. Final report on the evaluation of CMS’s

ESRD Managed Care Demonstration. Falls Church, VA: The

Lewin Group.

References

Payment for dialysis

CHAPTER 4
RECOMMENDATIONS

4A The Congress should direct the Secretary to:

• eliminate differences in paying for composite rate services between hospital-based and 

freestanding dialysis facilities; and 

• combine the base composite rate and the add-on adjustment.

COMMISSIONER VOTES: YES 16 • NO 0 • NOT VOTING 0 • ABSENT 1

 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4B The Secretary should:

• eliminate differences in paying for injectable drugs between hospital-based and 

freestanding dialysis facilities; and 

• use average sales price data to base payment for all injectable dialysis drugs that are 

separately billable in 2006.

COMMISSIONER VOTES: YES 16 • NO 0 • NOT VOTING 0 • ABSENT 1

 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4C The Congress should give the Secretary the authority to periodically collect average

acquisition cost data from dialysis providers and compare it with average sales price data.

The Secretary should collect data on the acquisition cost and payment per unit for

drugs—other than erythropoietin—that hospital-based providers furnish.

COMMISSIONER VOTES: YES 16 • NO 0 • NOT VOTING 0 • ABSENT 1
Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 87

hrough the Medicare Prescription Drug, Improvement,

and Modernization Act of 2003 (MMA), the Congress

improved payment for dialysis services—for example,

by adding a case-mix adjuster to the payment system.

But Medicare continues to pay dialysis providers differently based on site of care and type of drug. MedPAC 

recommends a series of changes to improve current payment policies. The Congress should eliminate differences

in paying for composite rate services between freestanding and hospital-based facilities and should combine the

composite rate and the add-on adjustment. The Secretary should use the same payment method—average sales

price (ASP)—to pay for all dialysis drugs provided by both facility types. The Congress should require that the

Secretary implement these recommendations so that aggregate payments in 2006 are equal to what payments

would have been under pre-MMA policies. The Secretary should also collect acquisition cost data from dialysis

providers to determine whether ASP represents the purchase price that providers incur. However, rationalizing

payment for composite rate services and dialysis injectables serves only as an interim solution; broadening the

payment bundle would modernize this payment system. 

4

In this chapter

• Improving the current 

payment system

• Modernizing the outpatient 

dialysis payment system

CHAPTER

T

Payment for dialysis
End-stage renal disease (ESRD) is a chronic illness

characterized by permanent kidney failure. This illness

occurs at the last stage of progressive impairment of

kidney function and is a consequence of a number 

of conditions, including diabetes, hypertension,

glomerulonephritis, and cystic kidney disease. Most

individuals with ESRD undergo chronic dialysis 

treatment to stay alive. The 1972 amendments to the

Social Security Act extended Medicare benefits to 

people with ESRD. In 2003, the Medicare program

covered about 300,000 patients, representing nearly 

93 percent of all dialysis patients in the United States.1

The Medicare Prescription Drug, Improvement, and

Modernization Act of 2003 (MMA) and regulations that

CMS issued to implement the new law substantially

changed the outpatient dialysis payment system by:

• paying acquisition cost for most (but not all)

separately billable injectable drugs;

• shifting some of the profits previously associated with

payments for separately billable drugs through an addon payment to the prospective payment rate for

outpatient dialysis services (the composite rate); and

• adjusting the composite rate for differences in case

mix.2

However, the MMA does not change the basic structure of

the dialysis payment system—separate payment for

dialysis treatments and injectable drugs. Providers will

continue to receive the composite rate for each dialysis

treatment provided in dialysis facilities (in-center) or in

patients’ homes.3 In 2005, the base composite rate for

hospital-based facilities is $132—on average, $4 more

than for freestanding facilities. This difference stems from

the Omnibus Budget Reconciliation Act of 1981, by which

the Congress mandated separate rates for the two types of

facilities. 

The Commission has considered whether current payment

policies achieve MedPAC’s payment policy objectives,

which include providing cost-effective, quality care to

patients using the most suitable modality in the most

suitable setting; promoting access to services; and 

giving dialysis providers incentives to control costs. 

This chapter explores these issues in two sections.

The first section discusses how Medicare pays for

outpatient dialysis services. We find that the MMA has

improved payment for dialysis in some respects—for

example, by adding a case-mix adjustment to the payment

system. But the MMA continues to pay freestanding and

hospital-based facilities differently for providing the 

same services. This payment method is not consistent 

with MedPAC’s principle of paying the costs incurred 

by efficient providers who furnish appropriate care,

regardless of the care setting. In addition, the new law

makes the payment system more complex by creating an

add-on adjustment to the composite rate. Consequently,

MedPAC’s recommendations advise the Congress and 

the Secretary to: 

• pay the same amount for composite rate services and

injectable drugs furnished by freestanding and

hospital-based providers, and 

• simplify the composite rate by combining the base rate

and the add-on adjustment.

In the second section of this chapter, we review

MedPAC’s past recommendations that the Congress 

(a) broaden the dialysis payment bundle to include

commonly furnished services that are not currently in 

the bundle and (b) account for factors that affect

providers’ costs, including dialysis method, dose, and

patient case mix. We also discuss potential issues that 

the Commission may explore in the future. 

Finally, MedPAC has concluded that an annual review of

rates—for the current payment system and one in which

the Congress establishes a larger bundle—is essential for

dialysis, especially given the current low margins

(MedPAC 2005). The Congress and the Secretary should

not assume, as they did in the 1990s, that regular rate

increases are not necessary because of large margins. 

Improving the current payment system

MedPAC recommends that the Congress and the 

Secretary equalize the composite rate for hospital-based

and freestanding providers, combine the composite rate

with the add-on adjustment, use the same methodology 

to pay for all drugs regardless of setting or type, and

periodically check the data on drug payment rates. The

following two principles underlie these recommendations: 

• Medicare should pay the same rate for the same

services across different settings; 

88 Payment for dialysis
• Payment should reflect the costs of efficient providers

and should be adjusted to reflect the effects on costs of

factors that are beyond providers’ control. 

The intent of these changes is to rationalize the system in

the interim, but a better system would combine payment

for composite rate services and drugs into a broader

bundle.

Paying for composite rate services

The new law does not change Medicare’s policy of 

paying hospital-based facilities $4 more, on average, 

for composite rate services than it pays freestanding

facilities. This difference began with the Omnibus 

Budget Reconciliation Act of 1981, which mandated

separate rates for the two types of facilities. In the 1983

rule implementing the composite rate, the Secretary

attributed this $4 difference to overhead, not to patient

complexity or case mix. 

Some stakeholders have raised concerns that hospitalbased providers employ more nurses to deliver care and,

consequently, should receive a higher level of payment.

MedPAC analyzed staffing levels using 2003 cost report

data submitted by freestanding and hospital-based

providers. We also analyzed dialysis quality using CMS’s

Dialysis Compare database. This online database contains

information, by facility, on the proportion of patients in

2002 who received adequate dialysis (i.e., having a urea

reduction ratio greater than or equal to 65 percent) and the

proportion of patients who had their anemia under control

(i.e., having a hematocrit greater than or equal to 33

percent). 

MedPAC’s analysis of these two data sources did find 

that hospitals reported higher labor costs and employed

more nurses, but quality did not differ between the two

types of facilities. MedPAC concludes that Medicare

should reward facilities based on quality—rather than 

pay a higher rate simply because the facilities employ

more nurses, which may lead to better quality. Pay-forperformance programs hold providers more accountable

by rewarding those providers who furnish high-quality

care and who improve the care that they furnish. 

As Table 4-1 shows, hospitals rely more heavily on

registered nurses—who are more highly educated and

paid—than on dialysis technicians. The opposite is true 

for freestanding facilities. Hospital-based providers are

also less productive than freestanding providers in terms

of (a) the total treatments per patient-care staff and 

(b) in-center hemodialysis treatments per station. This

productivity difference relates more closely to the volume

of dialysis treatments that a facility provides rather than

the facility’s location. Analysis of CMS’s facility survey

shows that hospital-based facilities provided about 20

percent fewer annual dialysis treatments than freestanding

facilities (7,800 versus 9,800 treatments, respectively).

MedPAC found about the same percentage difference

when comparing the number of annual dialysis treatments

provided by hospital and freestanding providers in rural

areas (5,300 versus 6,600 treatments, respectively) and in

urban areas (9,100 versus 11,100 treatments, respectively).

MedPAC’s analysis of dialysis quality shows little

difference in the proportion of patients who are receiving

adequate dialysis and are not anemic (Figure 4-1, p. 90).

For both provider types, about 91 percent of all patients

received adequate dialysis and about 89 percent of all

patients had their anemia under control. 

Figure 4-1 also shows few differences in the levels of

quality achieved by for-profit versus nonprofit providers;

by facilities that are affiliated with one of the four largest

chains versus those that are not; and by urban versus rural

providers. For each provider type, the proportion of

patients who received adequate dialysis is more than 90

percent, and the proportion of patients who had their

anemia under control is more than 87 percent.

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 89

Staffing and productivity vary

between freestanding and 

hospital-based providers

Freestanding Hospital-based

providers providers

Technicians as a percentage 

of patient-care staff 49% 30%

Registered nurses as a 

percentage of patient-care staff 31 50

Total treatments per 

patient-care staff 711 461

In-center hemodialysis 

treatments per station 587 522

Note: Patient-care staff comprises registered nurses, licensed practical nurses, 

nurses’ aides, dialysis technicians, dieticians, and social workers.

Source: MedPAC analysis of cost reports submitted by freestanding and hospitalbased dialysis providers in 2003.

TABLE

4-1
Many investigators have reported differing results about

whether dialysis quality varies based on facilities’

ownership and profit status. Previous work by MedPAC

showed no association between freestanding facilities’

quality of care and their profit status (MedPAC 2003).

CMS investigators found no association between profit

status and quality measures (that is, adequacy of dialysis,

anemia, and nutritional status) (Frankenfield et al. 2000).

Port and colleagues (2001) concluded that the risk of

mortality does not differ based on facilities’ profit status.

By contrast, Garg and colleagues (1999) reported higher

mortality rates and lower rates of wait-list placement 

for a kidney transplant for patients who received care 

at freestanding for-profit facilities than for those who

received care at freestanding nonprofit and hospital-based

facilities. Other researchers also have found a correlation

between facilities’ profit status and rates of mortality and

transplantation (Devereaux et al. 2002, Ebben et al. 2000,

McClellan et al. 1998). 

In addition to the different rate that Medicare pays to

freestanding and hospital-based providers, the MMA

increases the payment system’s complexity by creating the

add-on adjustment for injectable drugs. The Congress

required that the Secretary derive the add-on adjustment

by moving dollars associated with the profit margin for the

following injectable drugs to the composite rate payment:

• erythropoietin and all other separately billable drugs

that freestanding facilities provide, which CMS

estimates to be $385 million in 2005, and 

• erythropoietin that hospital-based facilities provide,

which CMS estimates to be $5 million in 2005. 

The resulting add-on adjustment to the composite rate is

8.7 percent.

If the Congress’s objective of creating the add-on

adjustment is to address how providers subsidize relatively

low payments for composite rate services with excessive

payments for injectable drugs, combining the base

90 Payment for dialysis

Dialysis adequacy and anemia status 

did not differ among providers in 2002

FIGURE

4-1

Note: A total of 3,791 facilities reported information about dialysis adequacy, and 3,831 facilities reported information about anemia status.

Source: MedPAC analysis of data from CMS’s Dialysis Compare database. Percent

age of p

atients

100

80

60

40

20

0

Type of provider

Receiving adequate dialysis Anemia under control

Freestanding HospitalbasedFor-profit Nonprofit One of 

largest 

four chains

Not one of

largest 

four chains

All Urban Rural

facilities
payment rate and the add-on adjustment is the best way to

realize this objective. 

In addition, we have concerns about the mechanism 

that the MMA lays out for recalibrating the add-on

adjustment. Beginning in 2006, the new law updates 

the value of the add-on adjustment—which CMS has

currently set at $11.17 for freestanding facilities and

$11.52 for hospitals—based on the growth in separately

billable drug expenditures. CMS has not yet indicated 

how it will implement this section of the MMA. Linking

the value of the add-on adjustment to post-MMA spending

for separately billable drugs may give providers incentives

for inappropriate use of the drugs. Linking the add-on

adjustment to pre-MMA spending also presents problems

because previous payment policies provided incentives for

the inappropriate use of drugs.

RECOMMENDATION 4A

The Congress should direct the Secretary to: 

• eliminate differences in paying for composite rate

services between hospital-based and freestanding

dialysis facilities; and 

• combine the base composite rate and the add-on

adjustment.

RATIONALE 4A

This recommendation aims to implement a uniform

payment policy across settings. Doing so will ensure that

Medicare pays the same amount for the same services

across different settings. Further, by combining the base

composite rate and the add-on adjustment, Medicare will

simplify the outpatient dialysis payment system.

IMPLICATIONS 4A

MedPAC considers the implication of this

recommendation on spending, beneficiaries, and 

providers together with the implications of

recommendation 4B (pp. 94–95). 

It is not clear whether the composite rate and add-on

adjustment together form the appropriate level of payment

for a dialysis treatment. Dialysis care has changed since

1983, but the Secretary has not rebased the composite

rate.4 Similar to other prospective payment bundles, the

product has changed: New technologies have replaced

older technologies, and the bundle now includes services

that were not available in 1983. As we discuss later in 

this chapter, when broadening the payment bundle the

Secretary will need to identify the medications, services,

and equipment that will increase the efficiency of patient

care and improve patient outcomes. 

In addition, for the current payment system and for one in

which Medicare establishes a larger bundle, MedPAC has

concluded that an annual review of rates is essential for

dialysis, especially given the current low margins

(MedPAC 2005). The Congress and the Secretary should

not assume, as they did in the 1990s, that regular rate

increases are not necessary because of high margins. 

Paying for dialysis injectable drugs

Under current law, which reflects both the MMA and

previous policy, the Secretary pays dialysis providers

differently depending on the specific drug and the site 

of care. All the payment policies we discuss in this 

sub-section relate to injectable drugs that CMS pays

separately from the composite rate. MedPAC recommends

rationalizing payment policy by (a) paying for all 

dialysis drugs using the same methodology (that is, the

same method used for other Part B providers) and 

(b) periodically checking the ASP data to verify its

appropriateness.

Before the MMA, payment for injectable drugs also varied

depending on the site of care and on the specific drug.5

The payment methods—a rate for erythropoietin set in the

statute and average wholesale price (AWP) for drugs other

than erythropoietin—generated excessive profits for these

drugs. Through the MMA, the Congress addressed this

overpayment issue by requiring a new payment approach.

Payment methods vary by site of care and

type of drug

Under current law created by the MMA, Medicare pays

three different ways for dialysis drugs. 

Paying for the “top 10 drugs” in freestanding

facilities For the 10 injectable drugs that make up the

highest share (98 percent) of volume, Medicare now pays

freestanding providers using a method called average

acquisition payment (AAP).6 To calculate the AAP, CMS

used the acquisition costs that the Office of Inspector

General (OIG) collected in a 2003 survey of freestanding

providers (OIG 2004).7 CMS derived the 2005 rates for

these drugs by updating the 2003 values using the

producer price index (PPI).

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 91
Paying for other drugs in freestanding facilities

For all other injectable drugs, Medicare pays freestanding

providers using a different method—ASP. This method

uses prices that manufacturers report to CMS every

quarter. CMS set the 2005 rates for these drugs at ASP

plus 6 percent. 

Paying for drugs in hospital-based facilities Unlike

freestanding providers, hospitals’ payment for most

dialysis drugs uses a third approach—reasonable cost—

with one exception: erythropoietin, for which Medicare

pays the same AAP rate as that of freestanding providers.

CMS derives reasonable cost from a hospital’s cost report;

the agency calculates this payment by reducing hospitalset charges, including overhead, to costs using a cost-tocharge ratio. Researchers do not yet clearly understand the

relationship between payment based on reasonable cost

and payment based on hospital-incurred acquisition cost. 

What is the best way for Medicare to pay

dialysis facilities for drugs?

Through the MMA, the Congress intended that the

payment rates for dialysis drugs more closely approximate

the costs that providers incur. Results from a MedPACsponsored survey and the OIG suggest that different types

of providers use different approaches to purchase drugs,

and this sometimes results in different prices. However,

the prices that freestanding and hospital-based facilities

pay do not vary much based on an analysis of pricing 

data that MedPAC obtained from IMS Health. 

The three different approaches—ASP, AAP, and

reasonable cost—all try to estimate the above costs.

Paying reasonable costs is probably the least accurate

approach, as it may reflect the facilities’ charging and

accounting practices. In our discussion below, we contrast

the two other methods and find that they attempt to

measure the same concept. However, ASP shows several

advantages over AAP in that the Secretary already collects

ASP data for all drugs and ASP data are more up to date. 

How do different providers acquire drugs?

The Commission sponsored a series of interviews with

hospital-based and smaller freestanding dialysis providers

to understand their purchasing strategies for dialysis

injectables. Our objective was to better understand how

smaller dialysis providers acquire injectable drugs—

including whether they purchase drugs directly or through

other agents (such as a parent company or hospital

pharmacy) and how they negotiate prices with

manufacturers. The text box describes how we constructed

the sample and the characteristics of the participating

dialysis providers. 

We found that the smaller providers try to competitively

negotiate to obtain dialysis drugs, but manufacturers

generally give direct discounts only to the largest volume

facilities—those typically affiliated with chains.

Respondents to our survey usually acquire drugs from: 

• Wholesalers—the primary source used by smaller

non-chain–affiliated freestanding facilities. It is

common for facilities to obtain drugs from more than

one wholesaler. Facilities that agree to purchase most

of their drugs from one wholesaler often receive a

better price from that wholesaler. Respondents to our

survey reported it was difficult to find a wholesaler for

drugs not routinely used. 

• Group purchasing organizations (GPOs)—an

important source for facilities seeking lower prices

that GPOs make available through volume purchases.

For a fee, the GPO functions as a buying unit for a

group of facilities that can take advantage of discounts

that manufacturers might offer to volume purchasers. 

• Manufacturers—the primary source for facilities that

are members of regional chains that can negotiate

volume discounts. Providers that purchase directly

from manufacturers avoid fees that wholesalers

charge.

Respondents indicated that they attempt to negotiate:

• Price—Respondents reported that they can better

negotiate for drugs in which clinical substitutes are

available. Of the top 10 dialysis injectables, only one

has generic alternatives. However, alternative

therapies exist among two classes of drugs—those

used to treat bone disease and iron deficiency.

• Volume—Providers that purchase larger volumes of

drugs can obtain lower prices through discounts and

rebates. However, patient needs and cash flow limit

the volume of drugs that providers can inventory at

any given time. 

By contrast to the smaller providers, we learned that the

large national chains generally negotiate directly with

manufacturers.

92 Payment for dialysis
How do prices vary by type of facility?

Findings from the OIG’s report suggest that the price

dialysis facilities pay varies between the largest

freestanding providers—that is, those affiliated with one

of the four largest dialysis chains—and all other

freestanding facilities (OIG 2004). The average

acquisition cost for the three leading drugs, in terms of

Medicare payments, was 8 to 22 percent lower for the

largest providers compared with other freestanding

providers in 2003.8 The largest providers reported drug

acquisition costs that were 6 percent lower than the ASP

of the top 10 drugs; by contrast, other freestanding

facilities reported drug acquisition costs that were 4

percent above the ASP. The OIG based its report on data

collected from each of the four largest dialysis providers

and a sample of all other freestanding facilities. The OIG

did not include hospital-based providers in its report. 

To compare the purchasing strategies of freestanding and

hospital-based providers, MedPAC obtained data from

IMS Health on the national average purchase prices for 

the top 10 dialysis injectables during the fourth quarter 

of 2004. This database included the national average

purchase prices for “clinics,” which include sales to

freestanding dialysis providers, and “nonfederal

hospitals,” which include sales to hospital-based dialysis

providers.9 Because IMS collects data from sales 

invoices and these sales invoices do not include offinvoice discounts or rebates, the average purchase price

overstates the amount that providers actually pay for

drugs. In addition, the average purchase price includes

purchases by both dialysis and nondialysis providers.

Our analysis suggests that the purchase prices for the top

dialysis injectables do not vary substantially between

freestanding providers and hospitals. The weighted

average purchase price for all of the study drugs was, on

average, 4 percent greater for “nonfederal hospitals”

compared with “clinics.” We calculated the weighted

average purchase price by weighting the average purchase

price for each drug by its proportion of total Medicare

payments. 

How do AAP and ASP compare?

Ideally, Medicare should arrive at the same payment rate

for a particular dialysis injectable by using either ASP or

AAP data. Both data sources aim to determine the

purchase price of drugs—that is, the net of all rebates and

discounts. CMS derives AAP data from a special survey

of dialysis providers. By contrast, CMS collects ASP data

from all manufacturers for all drugs, updates ASP data

quarterly, and uses this data source to pay for injectables

that other Part B providers furnish.10

The most important difference between the two methods is

the frequency by which CMS will update AAP data to

reflect actual transaction prices. AAP data may not

accurately reflect providers’ acquisition costs in 2006 and

beyond if the negotiating process changes the price that

manufacturers charge. In 2005, the OIG will determine the

prices of new drugs (which did not have a billing code

before 2004). Otherwise, the update may include an

inflation factor (such as the PPI). In addition, AAP does

not provide information on all injectable drugs that

dialysis facilities currently use. Finally, AAP does not

provide information about the prices that hospitals pay. 

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 93

Survey of small freestanding and hospital-based dialysis providers 

On behalf of MedPAC, the National Opinion

Research Center (NORC) and Georgetown

University conducted a series of interviews

with a small sample of hospital-based dialysis providers

and freestanding providers who were not affiliated with

the four largest chains. Beginning in March 2005, our

contractors conducted interviews by telephone using a

semistructured interview guide. NORC and Georgetown

University interviewed respondents—including directors

of purchasing, directors of pharmacy, and other facility

administrators—about how they negotiate prices and

acquire dialysis drugs. To date, our contractors have

completed 11 interviews with freestanding providers 

and 4 interviews with hospital-based providers. MedPAC compared the payment rate under AAP to the

corresponding rate for each of the top 10 dialysis drugs if

ASP plus 6 percent were the reference price (that is, the

rate used to pay other Part B providers [Table 4-2]). This

comparison shows similar rates for some drugs but shows

that for others, notably erythropoietin, the ASP rates have

been falling over the last quarter.11 The more recent ASP

data will more likely reflect current negotiations between

manufacturers and purchasers rather than the AAP rates.

Based on our analysis of how different providers acquire

and receive payment for injectable drugs—and of the

similarities and differences between ASP and AAP—

MedPAC concludes that: 

• Medicare’s current method of paying for separately

billable drugs should not vary between provider types.

• Both ASP and AAP aim to determine the purchase

price of drugs (which is the net of all rebates and

discounts); thus, CMS should derive a similar price

from either data source. 

• Similar incentives exist for providers to obtain the best

possible purchase price under both ASP and AAP. 

• CMS regularly collects ASP data and uses it to pay for

other Part B injectables. By contrast, CMS does not

regularly collect AAP data and does not use this data

source to pay for other Part B injectables.

• CMS updates ASP data regularly to reflect actual

transaction prices; thus, ASP data would better reflect

the prices paid by dialysis providers over time than

would AAP data. 

RECOMMENDATION 4B

The Secretary should: 

• eliminate differences in paying for injectable drugs

between hospital-based and freestanding dialysis

facilities; and

• use average sales price data to base payment for all

injectable dialysis drugs that are separately billable

in 2006.

RATIONALE 4B

This recommendation would make a uniform payment

policy across settings. In contrast to AAP data, ASP data

are already collected by the Secretary, are regularly

updated by the agency, and include data for all drugs. 

94 Payment for dialysis

AAP and ASP for dialysis injectables 

vary somewhat in 2005

ASP plus ASP plus

AAP 6 percent 6 percent

2005 (1st quarter 2005) (2nd quarter 2005)

Erythropoietin $9.76 $9.32 $9.25

Calcitriol 0.96 0.71 0.86

Doxercalciferol 2.60 2.80 2.78

Iron dextran 10.94 11.06 11.22

Iron sucrose 0.37 0.36 0.37

Levocarnitine 13.63 14.65 11.12

Paricalcitol 4.00 4.02 3.97

Sodium ferric gluconate complex 4.95 4.83 4.73

Alteplase, recombinant 31.74 30.15 30.09

Vancomycin 2.98 2.42 3.19

Note: AAP (average acquisition payment), ASP (average sales price). Average acquisition payment for 2005 reflects the average acquisition cost for 2003 updated by 

the producer price index.

Source: CMS 2005.

TABLE

4-2
IMPLICATIONS 4A AND 4B

Spending

• Through recommendations 4A and 4B, MedPAC

intends to maintain overall budget neutrality with 

pre-MMA spending in 2006.

Beneficiary and provider

• Some facilities could receive higher payments 

or lower payments. We do not expect this

recommendation to affect providers’ willingness 

and ability to provide quality care to Medicare

beneficiaries. These recommendations do not

substantially change beneficiary cost sharing, nor

should they have a negative effect on beneficiary

access to quality care. 

At what level should Medicare set ASP?

At issue is the level that Medicare should set ASP for

dialysis drugs. By setting the initial payment rate at ASP

plus 6 percent, the Secretary will account for the variation

in the purchase price for dialysis injectables across

different types of providers. Our analysis of data from the

OIG and IMS—and our survey of smaller providers—

suggests that some providers can negotiate larger

discounts for drugs than others. Together, these data

sources suggest that the four largest freestanding dialysis

chains obtain the lowest purchase price for injectable

drugs, followed by hospital-based and smaller

freestanding providers.

Over the long term, the Secretary should set a payment

rate that reflects efficient providers’ costs. In the next

section, we recommend that the Secretary periodically

collect acquisition cost data from a sample of providers

and compare it to the ASP data. By periodically collecting

data on providers’ costs, the Secretary can make

adjustments as necessary in the ASP level.

Improving data on paying for drugs

Although the Commission recommends using ASP data to

pay for all dialysis drugs, we caution that these data do

have some limitations. ASP data may deviate from AAP

data because: 

• The Secretary derives ASP on pricing data that

manufacturers submit for all “channels” (that is, types

of purchasers of a particular dialysis drug, not just

dialysis providers). Thus, ASP reflects the purchase

price of dialysis providers as well as that of other

providers, such as physicians, nursing facilities,

hospitals, and home health providers. The Secretary’s

calculation of ASP includes all sales except those that

are exempt from Medicaid’s best price calculations. 

However, the effect of basing the ASP calculation 

on nearly all sales may not be large. According to

stakeholders, medical professionals use the top 10

dialysis drugs, except for vancomycin, primarily to

care for renal patients.

• ASP may, in fact, understate the price that providers

pay because ASP does not include wholesalers’

service fees. 

Because ASP and AAP might deviate over time, MedPAC

recommends that the Secretary periodically collect

acquisition cost data from both freestanding and hospitalbased dialysis providers and compare it to ASP data. In

doing so, the Secretary will better understand the effect of

including nearly all sales in the calculation of ASP data.

By monitoring the comparability of both data sources over

time, the Secretary will be able to set the payment rate to

reflect efficient dialysis providers’ costs. 

The Secretary will need additional data to assess the

impact of using ASP data for hospitals. Such an

assessment is necessary in order to carry out the MMA’s

intent—that is, to modify the composite rate so that it

accounts for any profit associated with the previous

payment method and to maintain budget neutrality with

pre-MMA payment levels.

To conduct the assessment, the Secretary will need to

obtain data to estimate hospitals’ costs and Medicare’s

payment per unit for these drugs. No published source

identifies the unit payment for these drugs because

Medicare pays hospitals their reasonable costs. We

attempted to calculate the unit payment from 2003 claims

data, but the accuracy of the data fields we needed to make 

this calculation was unclear, particularly the number of

units furnished and Medicare’s payment to the hospital. 

As mentioned earlier, the OIG will be conducting a 

second study on the difference between (a) the Medicare

payment amount for separately billable dialysis drugs for

which a billing code did not exist prior to January 1, 2004,

and (b) the acquisition costs of such drugs. The OIG could

also collect hospitals’ payment and cost data for the top

10 dialysis injectables (other than erythropoietin). The

Secretary also might collect data on hospitals’ cost and

payment per unit for drugs in the agency’s demonstration

study of a broader bundle, which will begin in 2006. 

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 95
RECOMMENDATION 4C

The Congress should give the Secretary the authority to

periodically collect average acquisition cost data from

dialysis providers and compare it with average sales

price data. The Secretary should collect data on the

acquisition cost and payment per unit for drugs—other

than erythropoietin—that hospital-based providers

furnish. 

RATIONALE 4C

By collecting data on dialysis providers’ acquisition 

cost, the Secretary will be able to assess that data’s

comparability, over time, to ASP data. 

IMPLICATIONS 4C

Spending

• This recommendation will not increase federal

program spending relative to current law.

Beneficiary and provider

• Some facilities could receive higher payments 

or lower payments. We do not expect this

recommendation to affect providers’ willingness 

and ability to provide quality care to Medicare

beneficiaries.

Smaller facilities that are not affiliated with a dialysis

chain cannot purchase drugs as inexpensively as the

largest chain providers. To protect beneficiaries’ access to

these smaller facilities, policymakers might consider

extending to dialysis providers the competitive acquisition

program for outpatient drugs and biologicals. Beginning in

2006, the MMA gives physicians the choice of either

obtaining certain Part B injectables from contractors (who

would then bill Medicare) or continuing to purchase the

drugs and receive ASP plus 6 percent from Medicare. 

Impact of implementing MedPAC’s

recommendations 

We assessed the impact of implementing our

recommendations that refine payment policies for

composite rate services and dialysis injectables by

modeling 2006 spending under pre-MMA policies 

and under MedPAC’s recommendations (Table 4-3). 

This analysis also includes our recommendation to update

the payment for composite rate services in 2006 (MedPAC

2005). This analysis serves illustrative purposes only. 

If the Congress and the Secretary adopt MedPAC’s

recommendations, the Secretary will need to determine 

96 Payment for dialysis

Estimated impact of MedPAC's recommendations to refine 

outpatient dialysis payment policies, 2006

Freestanding Hospital-based Total

Payments in millions Payments in millions Payments in millions

Pre- Post- Percent Pre- Post- Percent Pre- Post- Percent

Service MMA MMA change MMA MMA change MMA MMA change

EPO $2,229 $2,146 –4 $216 $208 –4 $2,445 $2,354 –4

All other drugs 1,022 648 –37 157 157 0 1,179 805 –32

Total: Drugs 3,251 2,794 –14 372 364 –2 3,624 3,158 –13

Composite rate 4,239 4,626 634 670 4,872 5,296

B–N factor 0 36 0 5 0 41

Total: Composite rate 4,239 4,662 10 634 675 6 4,872 5,338 10

Drugs and

composite rate 7,490 7,456 –0.5 1,006 1,040 3 8,496 8,496 0

Note: MMA (Medicare Prescription Drug, Improvement, and Modernization Act), EPO (erythropoietin), B–N (budget neutrality). The column titled “Post-MMA” reflects 

MedPAC’s recommendations to change payment policies in 2006. MedPAC’s recommendations are estimated based on the average sales price plus 6 percent 

reported by CMS in April 2005 and inflated to 2006 prices. The aggregate composite rate represents the base rate and the add-on adjustment as implemented in 

CMS's final rule, updated by 2.5 percent, which was MedPAC's most recent recommendation for composite rate services (MedPAC 2005). Spending for aggregate

composite rate services includes a budget-neutral factor of $41million in order for MedPAC's recommendations to maintain budget neutrality with pre-MMA 

spending levels. See text box for a complete description of the methods. Sums may not total correctly due to rounding.

Source: MedPAC analysis of 2003 claims data submitted by freestanding and hospital-based providers. 

TABLE

4-3
the impact of these changes on different provider types

using the most current data available.

For the pre-MMA payment scenario, we updated the base

composite rate by 2.5 percent—MedPAC’s most recent

update recommendation for composite rate services. To

model the effect of our recommendations, we set the

payment rate for dialysis injectables at ASP plus 6 percent

and updated the aggregate composite rate by 2.5 percent.

The text box contains a complete description of the

methods. 

Through these recommendations, we intend to maintain

overall budget neutrality with pre-MMA spending levels.

We do so by including a budget neutrality factor with

spending for composite rate services. Using the most

current data available and updating it to represent 2006

spending and prices, we estimate a budget neutrality factor

of about $41 million. Total 2006 spending estimates for

composite rate services and for drugs under both scenarios

adds to $8.5 billion. 

The impact on aggregate spending for composite rate

services under MedPAC’s recommendations reflects: 

• The Secretary implementing the single add-on

adjustment. This action, mandated by the MMA,

resulted in transferring dollars from freestanding to

hospital-based facilities. The Secretary estimates that

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 97

Impact analysis of MedPAC’s recommendations to refine 

outpatient dialysis payment

Our impact analysis illustrates payments under

pre-Medicare Prescription Drug, Improvement,

and Modernization Act of 2003 (MMA)

policies and payments under MedPAC’s

recommendations, the latter of which (a) eliminate

differences in composite rate and drug payment policies

between the two provider types and (b) combine the

base composite rate and add-on adjustment. To the

extent possible, we used methods similar to those that

the Secretary used in the Part B final rule. 

As we show in Table 4-3, all spending is expressed in

terms of 2006 dollars. For both scenarios, we applied

MedPAC’s most recent update recommendation (2.5

percent) for composite rate services. For the pre-MMA

scenario, we applied the update factor to the base

composite rate. For the scenario modeling MedPAC’s

recommendations, we applied the update factor to the

base composite rate and add-on adjustment.

We could not model the impact of changing drug

payment policies for injectables other than

erythropoietin provided by hospitals. Thus, payment for

these drugs remains unchanged when we modeled the

impact of our recommendations. Because hospitals

receive reasonable cost for these drugs, the Secretary

has no data source from which to obtain the per-unit

payment for these drugs. By contrast, the Secretary 

used the Single Drug Pricer for January 2004 to derive

freestanding providers’ pre-MMA per-unit payment. 

MedPAC attempted to derive the payment per unit 

data from 2003 claims that hospital-based providers

submitted. However, after thoroughly reviewing these

data, we were unsure of their accuracy because

Medicare does not pay according to the number of 

units reported on the claim. Validating the claims data

to data reported on patients’ medical records would

demand more resources and time than available. Thus,

we took a conservative approach: When modeling the

effect of our recommendations, we maintained preMMA spending levels for these drugs.

To put this omission in perspective, Medicare’s

payments for drugs other than erythropoietin to

hospital-based providers account for a small proportion

of total payments for dialysis drugs. In 2003, payments

for these drugs accounted for 2 percent of all payments

and 5 percent of all drug payments to freestanding and

hospital-based providers. 

Lastly, our impact analysis does not reflect the case-mix

adjustment implemented by CMS on April 1, 2005.

Although this adjustment might affect the two types 

of providers differently, it would not affect overall

spending because the MMA mandated that the

Secretary implement the case-mix adjustment budget

neutral. total payments for freestanding facilities decreased by

0.6 percent and payments for hospital-based providers

increased by 5.2 percent. 

• The Congress eliminating the $4 difference between

freestanding and hospital-based providers. This

action, recommended by MedPAC, would result in 

an estimated aggregate composite rate of $143.58 

in 2006. If the Congress does not eliminate the $4

difference, we estimate the aggregate composite rate

would be $143.00 and $147.53 for freestanding and

hospital-based providers, respectively. Thus, by

eliminating the $4 difference, Medicare would

increase the composite rate by 0.4 percent for

freestanding providers and decrease the rate for

hospital-based providers by 2.7 percent. This impact

stems from the fact that freestanding providers 

furnish a much larger share of all dialysis treatments

than do hospital-based providers (87 percent versus 

13 percent, respectively).

• The Congress requiring that the Secretary

implement the Commission’s recommendations so

that aggregate payments in 2006 are equal to what

payments would have been under pre-MMA policies.

In doing so, Medicare would increase the aggregate

composite rate by 0.8 percent to $144.70 for both

facility types.

Compared with pre-MMA payments, we estimate that

aggregate erythropoietin payments will decrease by 3.7

percent for both provider types under MedPAC’s

recommendations. This decline reflects the difference in

the payment rate under pre-MMA policies and the ASP

plus 6 percent that MedPAC estimated in 2006.12

For freestanding providers, we estimate that aggregate

payments under MedPAC’s recommendations for all other

drugs will decrease by more than one-third compared to

pre-MMA levels. This decrease reflects the pre-MMA

policy of paying 95 percent of the AWP. We estimate that

payments for freestanding providers for all dialysis

injectables will decrease by 14 percent. 

Because of data limitations, our analysis assumes that

hospitals are receiving constant payments for drugs other

than erythropoietin. Consequently, we estimate that

hospitals’ total payments for all drugs will decrease by 2

percent. 

Considering spending for both composite rate services and

drugs together, we estimate that freestanding providers’

payments will decline slightly (by 0.45 percent) and that

hospital’s payments will increase (by 3.4 percent). 

Modernizing the outpatient dialysis

payment system

Improving current payment for composite rate services

and dialysis injectables serves only as an interim solution;

the Congress should also broaden the payment bundle in

order to modernize this payment system. Medicare could

provide incentives for controlling costs and promoting

quality care by broadening the payment bundle to include

dialysis injectables and laboratory services that are not

separately billable and by linking payment to quality. 

Facilities have stronger incentives to control the costs 

of services included in the payment bundle compared 

with services that fall outside it—that is, services that 

are separately billable. Under pre-MMA payment policy,

drug spending per patient varied among different provider

types, perhaps reflecting providers’ differing incentives to

furnish drugs under different payment systems. For

example, per patient per month spending varied from 

$453 to $530 for erythropoietin, $69 to $93 for injectable

iron, and $67 to $166 for vitamin D analogues across 

the four major for-profit chains and hospital-based

facilities (USRDS 2004). In addition, an earlier MedPAC

analysis showed that dialysis quality of care (a) did not

significantly differ among facilities with lower and higher

costs for composite rate services and (b) was poorer for

facilities with higher-than-average costs for composite 

rate services and for injectable drugs (MedPAC 2003).

Differences in case mix may also partly account for these

findings. Together, these findings suggest that certain

facilities might less efficiently furnish injectable drugs

than other facilities, and this inefficiency may in turn

reflect less than optimal patient care. 

The new law creates incentives for facilities to more

appropriately use dialysis injectables, because Medicare

pays acquisition cost for most drugs. However, because

some providers can negotiate steeper discounts than the

acquisition cost and because the payment system pays on a

per-unit basis, the new law does not eliminate the

incentive for inappropriate use. 

98 Payment for dialysis
Both facility types showed substantial spending for

dialysis injectables—$2.8 billion for drugs compared with

$4.2 billion for composite rate services in 2003. Spending

for drugs accounts for a similar proportion of all dialysis

spending for both facility types—39 percent of all

spending for hospital-based providers and 41 percent of 

all spending for freestanding providers in 2003. If the

Congress had not implemented the MMA, we estimate

that drug spending would have increased to about 44

percent of all spending in 2006. 

Spending for laboratory services outside the payment

bundle may also be significant. Researchers at the

University of Michigan recently estimated that spending

for laboratories outside the composite rate was $249

million in 2003. The Government Accountability Office

(GAO) previously found that clinically similar ESRD

patients received laboratory tests at widely disparate rates.

The GAO also concluded that at one extreme, Medicare

may be paying for an excessive number of tests; at the

other, patients may not be receiving the tests needed to

adequately monitor their condition (GAO 1997).

MedPAC has recommended that the Congress should

—as soon as possible—refine the outpatient dialysis

payment system by broadening the dialysis payment

bundle to include commonly furnished services that

Medicare currently excludes. The Congress should also

account for factors that affect providers’ costs, including

dialysis method, dose, and patient case mix (MedPAC

2001). MedPAC has also recommended that the Congress

implement pay-for-performance for both facilities and

physicians who treat dialysis patients (MedPAC 2004). In

addition, to promote the delivery of clinically appropriate

care, the Secretary needs to continue to develop quality

measures and to monitor and improve dialysis care.

Together, these recommendations should improve the

efficiency of the payment system, better align incentives

for providing cost-effective care, and reward providers and

physicians for providing high-quality care.

The new law begins to consider expanding the payment

bundle. Starting on January 1, 2006, the Secretary must

conduct a three-year demonstration of a sample of dialysis

providers to test a broader payment bundle. 

Future MedPAC issues

MedPAC plans to continue analyzing the following

outpatient dialysis payment issues:

• Wage index adjustment to the composite rate. In the

MMA, the Congress gave the Secretary discretionary

authority to revise the wage index that the Secretary

currently uses in the dialysis payment system. When

CMS implemented other changes to dialysis payment

required by the MMA, the agency chose not to make

changes to the wage index. The agency argued that 

(a) new statistical area definitions recently published

by the Office of Management and Budget will affect

payment distribution and (b) the evaluations of the

impact of these new statistical areas are necessary

before changes to the wage index are made. MedPAC

is exploring the implications of more current wage

indexes on providers’ spending. 

• Payment for home dialysis. One issue for the

Congress to consider when modernizing the payment

system is whether to maintain the same payment rate

for in-center and home dialysis. Currently, the

composite rate is the same for in-center hemodialysis

and dialysis that is administered in patients’ homes—

that is, peritoneal dialysis and hemodialysis. In 1981,

the Congress mandated that payment not differ in

order to encourage patients’ use of home dialysis.

Historically, providers incurred lower costs for

providing home dialysis than in-center dialysis.

Despite this cost difference, the use of home dialysis

has declined during the past 10 years. Issues that

remain to be explored include a comparison of the

current use of dialysis injectables by at-home and incenter patients, the impact of the pre-MMA payment

system on the use of home dialysis, the impact of preESRD care on the use of home dialysis, and the use of

quality incentives to promote home dialysis.

• Case-mix adjustment. As we mentioned earlier, 

CMS has recently adjusted the composite rate for age

and body mass. Some stakeholders are concerned 

that this adjustment results in payments that are

greater for younger adult patients than for older

patients. MedPAC’s preliminary analysis confirms

CMS’s findings. The association between patients’

age and providers’ cost is “U”-shaped, with pediatric

patients, young adults (18 to 44 years of age), and

elderly patients (greater than 80 years of age)

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 99
100 Payment for dialysis

incurring higher costs than those of other age groups

(patients who are 45 to 59 and 70 to 79 years of age).

MedPAC plans to explore factors that may be

affecting providers’ costs, such as patient compliance

and dialysis time. We also plan to evaluate different

ways in which the Secretary can case-mix adjust a

broader payment bundle.

• Part B and Part D coverage for drugs. CMS may be

considering paying for dialysis injectables under both

the Part B and Part D payment systems. MedPAC will

be following this issue closely because it can affect

beneficiaries’ cost sharing under the current payment

system of paying separately for dialysis injectables,

and because this issue would also complicate the

implementation of a broader payment bundle. Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 101

1 To qualify for the ESRD program, individuals must be

insured under the Social Security or Railroad Retirement

program, be entitled to monthly benefits under the Social

Security or Railroad Retirement program, or be the spouse or

dependent child of an eligible beneficiary.

2 As of April 2005, CMS uses the following measures to

adjust the composite rate for differences in case mix: 

• age (<18, 18–44, 45–59, 60–69, 70–79, >80 years), and 

• two body measurement variables—body surface area

and body mass index—calculated from patients’ height

and weight when they develop ESRD. As of January

2005, CMS requires that dialysis facilities report

patients’ height and weight on dialysis claims.

CMS does not use the body measurement variables to

calculate payments for patients under age 18.

3 In 1981, the Congress mandated that the composite rate

include all nursing services, supplies, equipment, and

selected drugs associated with a single dialysis session. 

4 Although the Secretary has not rebased the composite rate,

the Congress updated it twice during the past five years (in

2000 and 2005). 

5 Under pre-MMA policies, the payment rate for

erythropoietin was the same for freestanding and hospitalbased facilities—$10 per 1,000 units. For drugs other 

than erythropoietin, Medicare paid freestanding facilities 

95 percent of the AWP; by contrast, Medicare paid 

hospital-based facilities reasonable cost for these drugs. 

6 The top 10 drugs are erythropoietin, calcitriol,

doxercalciferol, iron dextran, iron sucrose, levocarnitine,

paricalcitol, sodium ferric gluconate complex, alteplase

recombinant, and vancomycin.

7 The OIG is mandated to conduct two studies on the pricing

of dialysis drugs. The first study, published in May 2004,

examined the pricing of drugs that had a billing code before

2004. The second study, due to the Congress by April 2006,

will examine the pricing of drugs that did not have a billing

code in 2004.

8 The three leading drugs—in terms of Medicare payments in

2003—for freestanding facilities were erythropoietin ($1.7

billion), paricalcitol ($323 million), and iron sucrose ($153

million). 

9 IMS Health collects purchase price data from manufacturers

and drug wholesalers.

10 The Secretary derives ASP from sales data that

manufacturers submit to the agency no later than 30 days

after the close of each quarter. The term manufacturer 

means any entity engaged in the following activities: 

(1) production, preparation, propagation, compounding,

conversion, or processing of prescription drug products, 

or (2) packaging, repackaging, labeling, relabeling, or

distribution of prescription drug products. The term

manufacturer does not include a wholesale distributor of

drugs or a retail pharmacy licensed under state law. The 

ASP for a given product is the volume-weighted average 

of the manufacturers’ average sales prices reported to the

Secretary across all drugs assigned to a HCPCS code. ASP is

the net of all price concessions, including volume discounts,

prompt pay discounts, cash discounts, free goods that are

contingent on any purchase requirement, chargebacks, and

rebates. The Secretary estimates total price concessions using

a 12-month rolling price concession. Medicare payment

allowances for the first quarter of 2005 are based on

submissions from the third quarter of 2004. 

11 CMS has not announced any changes to the ASP values for

the second quarter of 2005. The agency did revise the ASP

values of a few drugs for the first quarter of 2005 to correct

technical errors. 

12 MedPAC estimated the 2006 average sales price plus 6

percent for erythropoietin by inflating the rate used by CMS

in the second quarter of 2005 by an update factor of 4.1

percent. We derived this factor using a combination of

historical data on producer prices for prescription drugs and

CMS’s projections of future growth in nationwide drug

spending per person.

Endnotes
102 Payment for dialysis

Centers for Medicare & Medicaid Services, Department of Health

and Human Services. 2005. April 2005 ASP pricing file and ASP

NOC file. http://www.cms.hhs.gov/providers/drugs/asp.asp.

Devereaux, P. J., H. J. Schunemann, N. Ravindran, et al. 2002.

Comparison of mortality between private for-profit and private

not-for-profit hemodialysis centers. Journal of the American

Medical Association 288, no. 19 (November 20): 2449–2457.

Ebben, J. P., F. Dalleska, J. Z. Ma, et al. 2000. Impact of disease

severity and hematocrit level on reuse-associated mortality.

American Journal of Kidney Diseases 35, no. 2 (February):

244–249. 

Frankenfield, D. L., J. R. Sugarman, R. J. Presley, et al. 2000.

Impact of facility size and profit status on intermediate outcomes

in chronic dialysis patients. American Journal of Kidney Diseases

36, no. 2 (August): 318–326.

Garg, P. P., K. D. Frick, M. Diener-West, et al. 1999. Effect of

the ownership of dialysis facilities on patients’ survival and

referral for transplantation. New England Journal of Medicine

341, no. 22 (November 25): 1653–1660.

Government Accountability Office. September 1997. Medicare

dialysis patients: Widely varying lab test rates suggest need for

greater HCFA scrutiny. Washington DC: GAO. 

McClellan, W. M., J. M. Souci, and W. D. Flanders. 1998.

Mortality in end-stage renal disease is associated with facility-tofacility differences in adequacy of hemodialysis. Journal of the

American Society of Nephrolology 9, no. 10 (October):

1940–1947.

Medicare Payment Advisory Commission. 2005. Report to the

Congress: Medicare payment policy. Washington, DC: MedPAC. 

Medicare Payment Advisory Commission. 2004. Report to the

Congress: Medicare payment policy. Washington, DC: MedPAC. 

Medicare Payment Advisory Commission. 2003. Report to the

Congress: Variation and innovation in Medicare. Washington

DC: MedPAC. 

Medicare Payment Advisory Commission. 2001. Report to the

Congress: Medicare payment policy. Washington, DC: MedPAC. 

Office of Inspector General, Department of Health and Human

Services. 2004. Medicare reimbursement for existing end-stage

renal disease drugs. Washington, DC: OIG.

Port, F. K., R. A. Wolfe, T. E. Hulbert-Shearon, et al. 2001.

Mortality risk by hemodialyzer reuse practice and dialyzer

membrane characteristics: Results from the USRDS dialysis

morbidity and mortality study. American Journal of Kidney

Diseases 37, no. 2 (February): 276–286.

United States Renal Data System, National Institute of Diabetes

and Digestive and Kidney Diseases. 2004. USRDS 2003 annual

data report. Bethesda, MD: NIDDK.

References
Payment for post-acute care

CHAPTER 5

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 105

roviders should base their decisions about where beneficiaries receive post-acute care services on patient characteristics and resource needs, not on Medicare payments.

Given the potential overlap in services and lack of criteria

delineating the appropriate treatment setting, post-acute care decisions

are sensitive to payment system incentives. Where overlap exists, the

tradeoffs between cost and quality often are unknown. In this chapter, we

report on the results of one study comparing patient characteristics, 

outcomes, and spending in different post-acute settings for beneficiaries

who had a hip or knee replaced. Next, to examine how well policymakers and researchers could compare patients

across settings, we report on the various patient assessment tools currently required in three post-acute settings.

Finally, we discuss the reasons that the payment systems for skilled nursing facilities and home health services

may not be paying appropriately for all types of patients. We discuss ways to correct problems with payments in

these settings to ensure that payments better track the resource needs of different patients.

5

In this chapter

• Comparing outcomes and 

spending for beneficiaries 

who have had a hip or 

knee replaced

• Comparing the patient 

assessment tools used in 

post-acute care settings

• Assessing the skilled 

nursing facility PPS

• Assessing the home 

health PPS

CHAPTER

P

Payment for 

post-acute care
Post-acute care generally follows an acute hospitalization

and is provided in four settings—skilled nursing facilities

(SNFs), inpatient rehabilitation facilities (IRFs), long-term

care hospitals (LTCHs), and the home. Post-acute care

includes services such as physical or speech therapy,

wound care, skilled nursing care for chronic conditions,

and care for patients who use ventilators. Eligible

beneficiaries who are referred from the community 

and who use home health services without a prior

hospitalization also use post-acute care. 

In 2002, one-third of Medicare beneficiaries discharged

from acute hospitals used post-acute care within one day

of leaving the hospital (Figure 5-1). SNFs are the most

frequently used setting, with home health the next most

frequently used.

Services provided in the four post-acute settings are 

often similar, but coverage rules, service intensity, 

and payments differ for the four post-acute settings.

Medicare’s eligibility criteria for beneficiaries using postacute care vary by setting. The program’s conditions of

participation (COPs) for providers, staffing ratios, and

even types of staff differ by setting. Medicare pays for

care in each setting using a distinct payment system. The

differences among the settings in COPs, staffing ratios,

and intensity of care have contributed to the historical

costs on which the payment system in each setting is

based. Pronounced geographic differences in the supply 

of post-acute services also exist. 

Some observers maintain that beneficiaries can use postacute care as a continuum of care, where patients use

multiple types of post-acute care consecutively as their

need for care decreases. Evidence indicates that although it

may be a continuum for some, relatively few beneficiaries

use more than one post-acute setting: In 2002, 4 percent of

the beneficiaries discharged from the hospital used more

than one post-acute setting. Most beneficiaries who used

more than one setting used home health services after a

SNF stay (97 percent). 

Several studies have explored whether care in one setting

can be appropriately substituted for care in another by

looking at whether similar patients have experienced

similar outcomes in different settings. In one study,

researchers found that the potential for substitution varied

by diagnosis, with little potential for substitution among

stroke patients but more potential for congestive heart

failure patients (Gage 1999). Other studies provided 

mixed evidence of substitution, which sometimes varied

by diagnosis (Deutsch et al. 2005, Kane et al. 2000, Keith

et al. 1995, Kramer et al. 2000, Kramer et al.1997, 

Manton et al. 1994). For example, Kramer (1997) found

that SNFs and IRFs had equivalent functional outcomes

for hip fracture patients, but Kane (2000) found that hip

fracture patients experienced better outcomes in IRFs 

and at home compared with SNFs. In the only study that

used data collected after the SNF and IRF prospective

payment systems (PPSs) began, researchers found that 

hip fracture patients who used IRFs experienced better

functional outcomes than patients who used SNFs 

(Munin et al. 2005). 

106 Payment for p ost-acute care

Note: LTCH (long-term care hospital), IRF (inpatient rehabilitation facility),

 IPF (inpatient psychiatric facility), PAC (post-acute care). “None” indicates

 patients who used no post-acute care following their hospital stay.

 This chart shows the share of patients who used post-acute care within 

 one day of discharge from the hospital. 

Source: Hogan 2004.

Skilled nursing

facility

Home health

services

LTCH,

IRF, IPF

Multiple

PAC settings

None

13%

11%

5%

4%

67%

One-third of beneficiaries 

discharged from hospitals

use post-acute care

FIGURE

5-1
Comparing outcomes and spending for

beneficiaries who have had a hip or

knee replaced

One criterion that distinguishes IRFs from acute hospitals

is the so-called 75 percent rule. This rule requires that 

an IRF admit 75 percent of patients for one or more

conditions from a list of conditions that CMS specifies,

such as stroke or hip fracture. In 2004, after several 

years of not enforcing the rule, CMS revised the list of

conditions for the first time since 1983. Specifically, CMS

eliminated “polyarthritis”—the most frequent diagnosis

for beneficiaries who used IRFs in 2002—from the list

and replaced it with four arthritis-related conditions. 

These conditions include (a) patients with polyarthritis

who have bilateral joints replaced, are aged 85+, or have 

a body mass index (BMI) of 50+; (b) patients who have

two major weight-bearing joints with severe osteoarthritis 

(not counting replaced joints); (c) rheumatoid arthritis;

and (d) systemic vasculidities with joint inflammation.

The last three conditions must not have improved after 

an appropriate, aggressive, and sustained course of

outpatient therapy services (or services in less intensive

rehabilitation settings) immediately preceding the IRF

admission or must result from a systemic disease

activation immediately before admission. CMS is phasing

in the changes in the 75 percent rule, beginning in July

2005, over a period of four years—50 percent the first

year, 60 percent the second year, 65 percent the third year,

and 75 percent in successive years. CMS maintains that

polyarthritis—the diagnosis for hip and knee replacement

patients—does not require the intense rehabilitation

provided by IRFs, except in select cases. 

In effect, the change in the 75 percent rule means that

fewer beneficiaries with a single hip or knee replacement

will likely use IRF care. IRFs that previously have

admitted a substantial proportion of joint replacement

patients are expected to change their behavior in order to

comply with the new rule as it phases in. As a result, under

the new 75 percent rule, some beneficiaries with a hip or

knee replacement who need rehabilitation but do not meet

the new criteria will not go to an IRF but instead will have

a longer acute hospital stay, be referred to SNFs, or be sent

home with home health or outpatient therapy. Other such

beneficiaries may continue to use IRFs; the rule provides

for 25 percent of IRF patients to have conditions not on

the list. The research we discuss in this section is the first

study comparing outcomes and spending for joint

replacement patients across settings. 

To determine the potential effect of the change in the 

75 percent rule, we convened a physician panel of

orthopedic surgeons and specialists in physical medicine

and rehabilitation in which they could discuss their views

of differences among patients that influence the setting

beneficiaries use. We also contracted with RAND to

compare outcomes and Medicare spending across settings

for beneficiaries who have had a hip or knee replaced.

This information can help policymakers better understand

the impact of the new 75 percent rule on beneficiaries and

Medicare’s costs. 

Physician panel

We convened a panel of six orthopedic surgeons who

perform many hip and knee replacements and five

specialists in physical medicine and rehabilitation who 

are familiar with the rehabilitation of these types of

patients. Generally our panelists were affiliated with large

academically oriented health care institutions located in

various parts of the nation. We asked this panel to discuss

where beneficiaries who have had a hip or knee replaced

should be rehabilitated after surgery. We also asked the

panel to discuss whether they had observed any change in

practice or referral patterns since the publication of the

new 75 percent rule. 

The orthopedic surgeons told us that patients who have

had a hip or knee replaced ideally should go home 

with either home health care or outpatient therapy

services—between 50 percent and 85 percent of their

Medicare patients go home from the hospital in two to

four days following surgery. (These estimates are higher

than the national rate [Table 5-1, p. 109].) The panel said

that characteristics of patients who require rehabilitation 

in an institutional setting (IRF or SNF) are those who:

• are limited in weight-bearing ability or cannot walk

100 feet,

• are obese,

• have impairment of one or more joints (other than the

one replaced),

• have diminished presurgery functioning, 

• have comorbidities, such as congestive heart failure or

post-operative dementia, 

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 107
• have architectural barriers at home, or

• have no informal caregiver. 

Weight-bearing ability is an important predictor of how

fast patients recover after surgery, and it may even

determine whether the patient makes progress. Obesity

also affects a patient’s ability to bear weight. The panel

unanimously questioned the appropriateness of a BMI of

50 as a criterion for joint replacement patients who are

obese to be counted in the 75 percent rule. The panelists

thought that beneficiaries with a BMI of 50 or more would

not be able to tolerate the intense rehabilitation provided in

IRFs. Thus, in the panelists’ opinion, the standard

excluded all obese persons who might benefit from IRF

care. Some panelists thought a BMI of 38 was a more

appropriate standard. 

Regarding the question of whether patients with the need

for rehabilitation in an institutional setting should go to 

an IRF or a SNF, the orthopedic surgeons felt that joint

replacement patients could go to SNFs, although SNFs

would not rehabilitate patients as quickly as IRFs. The

panelists also agreed that certain circumstances cause IRFs

to be more appropriate. For example, when a patient has

comorbidities, he may benefit from the extra medical

attention that an IRF provides. However, if a patient

cannot stand the intense therapy provided at an IRF, or 

if he has a weight-bearing constraint, the convalescent 

care of a SNF may be more appropriate. 

Orthopedic surgeons in some communities decide on 

an IRF versus a SNF based on the characteristics of the

specific facilities available. The surgeons suggested that

their comfort level with facilities may reflect the level 

and type of staffing at the facility, whether the facility

follows protocols, or even the surgeon’s convenience. 

For example, because physicians in SNFs are usually 

not involved in frequent supervision of patients while

physicians in IRFs are integrally involved with patients,

orthopedic surgeons may prefer IRFs because they can

hand off patients to an IRF’s physicians with confidence

that those patients would continue to receive close

monitoring. One surgeon said that his practice area had

neither SNFs nor IRFs. In general, surgeons said that 

they did not know the outcomes of patients being

rehabilitated in SNFs. 

The panelists maintain that the publication of the new rule

defining IRFs has already affected referral patterns. They

reported that some IRFs will no longer accept joint

replacement patients and that acute hospital lengths of stay

(LOSs) have increased slightly as a result. Panelists told 

us that IRFs with a large referral base would have fewer

problems meeting the new criteria, but IRFs with a smaller

referral base may have greater difficulty complying. Some

orthopedic surgeons also reported having developed

protocols for home health agencies, so that these agencies

could provide more intensive rehabilitation services to

patients after hip or knee replacement. 

Results from the empirical study

We contracted with researchers to study outcomes and

Medicare spending for all beneficiaries who had hip or

knee replacements and who were discharged from an

acute hospital between January 2002 and June 2003 (see

text box on p. 113 for study methods) (Beeuwkes Buntin

et al. 2005).1

The research questions in this study were:

• What are the differences among hip or knee

replacement patients who use IRFs, SNFs, or go home

following surgery?

• What are the differences in outcomes for these

patients?

—What are the differences in functional status?

—What are the differences in patients residing in 

the community at 120 days?

• What are the differences in Medicare spending for

these patients?

Differences in patient characteristics

The study found: 

• About 30 percent of patients who had hip or knee

replacements used SNF care following surgery, 

35 percent used IRF care, and the remaining 

35 percent returned home (with home health care,

outpatient therapy, or no care) (Table 5-1).

• On average, patients who go home following 

surgery are younger, have fewer comorbidities and

complications, and are less likely to be eligible for

both Medicare and Medicaid than IRF patients.

Compared with IRF patients, SNF patients are

significantly older, have more comorbidities and

complications, and are more likely to be eligible 

for both Medicare and Medicaid (Table 5-1). 

108 Payment for p ost-acute care
Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 109

Selected characteristics of patients with hip or knee replacement

Site of care after surgery

Characteristics Home IRF SNF

Number of observations 149,000 149,000 128,000

Percentage 35% 35% 30%

Demographic characteristics

Age (years) 72.7 75.0 76.3**

Female 54.3% 70.2% 72.2%**

White 94.2 89.9 93.3**

Black 3.3 6.8** 4.1

Medicaid coverage 5.2 9.2 10.1**

Complications

Postoperative pulmonary compromise 0.3 0.5 0.8**

Postoperative GI hemorrhage or ulceration 0.2 0.2 0.3** 

Cellulitis or decubitis ulcer 0.3 0.5 0.8**

Septicemia 0.0 0.0 0.1**

Mechanical complications due to device or implant 0.9 1.2 1.7**

Shock or cardiorespiratory arrest 0.1 0.1 0.2**

Postoperative heart attack 0.3 0.4 0.6**

Venous thrombosis or pulmonary embolism 0.5 0.7** 0.6

Iatrogenic complications 3.4 4.0 4.7**

Comorbidities

Acute renal failure 0.3 0.7 0.8**

Delirium 0.7 1.4 2.0**

Chronic pulmonary disease 9.1 11.2 11.8**

Congestive heart failure 3.4 5.8 7.1**

Chronic renal failure 0.1 0.2 0.2**

Nutritional deficiencies 0.1 0.2 0.4**

Dementia 0.5 0.9 2.3**

Pneumonia 0.6 0.8 1.2**

Type of joint replacement

Hip replacement 31.2 36.1 40.0**

Total 25.8 30.1 31.0**

Partial 0.6 1.3 2.7**

Hip revision 4.8 4.8 6.3**

Knee replacement 68.5 63.9** 60.0

Total 62.5 60.0** 55.8

Bilateral procedure 1.8 6.2** 4.0

Note: IRF (inpatient rehabilitation facility), SNF (skilled nursing facility), GI (gastrointestinal). Patients who were in a custodial nursing home before or after their acute stay,

who used acute rehabilitation (DRG 462), used long-term care hospitals, or died in the first 30 days after their acute discharge are excluded from this analysis. This 

excludes < 3% of the sample. Patients in the sample were hospitalized from January 2002 through June 2003.

** Indicates significant t-test for differences between IRF and SNF values at the 0.0001 level. 

Asterisks are placed next to the higher of the values for SNF and IRF.

Source: Beeuwkes Buntin et al. 2005.

TABLE

5-1
• Of beneficiaries who use institutional settings, those

who have had hip replacements are more likely to go

to a SNF, while beneficiaries who have had knee

replacements are more likely to go to an IRF 

(Table 5-1, p. 109).

• On average, IRF patients come from acute hospitals

that are larger, have a higher case-mix index, and are

more likely to be teaching hospitals (Table 5-2).

• Distance to a facility may be a factor in determining

site of care. On average, patients who use an IRF 

have one that is relatively close to their residence 

(Table 5-2).

Differences in outcomes

In this section, we discuss differences in functional status

for SNF and IRF patients, mortality, and residence in the

community. IRFs and SNFs measure functional status

close to or at admission for their patients. Patients who go

home with outpatient therapy or with no care do not have

their functional status assessed. 

The preferred outcome—improvement in functional

status—is not assessed for most SNF patients. Because

SNFs do not assess patients’ functional status at discharge,

researchers compared functional status at admission and

discharge (or at 14 days) for patients who stayed in the

IRF or the SNF at least 14 days.2 Researchers created a

measure of functional status similar to the Barthel Index

(Mahoney and Barthel 1965) and mapped from the SNFs

and IRFs assessment tools to the index. As discussed in

the section on patient assessment instruments, clinicians

use these tools to ask different questions and assess

patients at different times during their post-acute stay, so

the quasi-Barthel Index may not be comparable. As a

result, researchers also examined patients’ independence

in walking and in transfer (for example, from a bed to a

chair). 

Descriptive analysis Based on descriptive statistics that

do not control for differences in patient characteristics and

potentially measure IRF and SNF patients at different

points in their stay, SNF patients have a higher functional

status score at admission than IRF patients. But SNF

patients with a 14-day or longer stay have lower functional

status scores than IRF patients discharged from the facility

at 14+ days (Table 5-3). 

Walking—Of patients who were discharged at 14+ days

after admission, 1 percent of IRF patients were walking

independently at admission but 76 percent were walking

independently at discharge. For SNF patients in the 

facility at 14+ days after admission, 9 percent were

walking independently at admission but 31 percent 

were walking independently at 14 days (Table 5-3). 

110 Payment for p ost-acute care

Characteristics of discharging

hospitals and proximity to 

facilities for patients with hip 

or knee replacement

Site of care after surgery

Home IRF SNF

Number of observations 149,000 149,000 128,000

Percentage 35% 35% 30%

Discharging hospital's 

characteristics

Nonprofit hospital 78% 76 % 79 %**

Government hospital 10 9 10 **

Percentage of: 

Low-income patients 12 13 ** 12

Medicare days 47 47 49 **

Hospital's ADC 204 235 ** 191

Resident–to–ADC ratio 0.118 0.144 ** 0.110

Case-mix index 1.532 1.548 ** 1.469

Patient's proximity 

to facility

Average number of

IRFs within travel radius 11 13 ** 11

SNFs within travel radius 39 43 46 **

No SNFs within 

travel radius 0.001 0.001 ** 0.001

Distance to nearest 

SNF in miles 3 2 2 **

Distance to nearest 

IRF in miles 18 11 18 **

Note: IRF (inpatient rehabilitation facility), SNF (skilled nursing facility), 

ADC (average daily census). Patients who were in a custodial nursing 

home before or after their acute stay, used acute rehab (DRG 462), used 

long-term care hospitals, or died in the first 30 days after their acute 

discharge are excluded from this analysis. This excludes < 3% of the 

sample. Patients in the sample were hospitalized from January 2002 

through June 2003.

** Indicates significant t-test for differences between IRF and SNF values at

the 0.0001 level. 

Asterisks are placed next to the higher of the values for SNF and IRF. 

Travel radius is defined as the 90th percentile of the distance traveled to a 

type of provider by beneficiaries living in that type of area.

Source: Beeuwkes Buntin et al. 2005.

TABLE

5-2
Transferring—Of patients who were discharged at 

14+ days after admission, 2 percent of IRF patients were

transferring independently at admission but 79 percent

were transferring independently at discharge. For SNF

patients in the facility at 14+ days after admission, 

8 percent were transferring independently at admission 

but 30 percent were transferring independently at 

14 days (Table 5-3). 

Multivariate analysis As noted in the descriptive

analyses, there is a great deal of selection of patients 

into the three settings (IRF, SNF, and home). Thus it 

is critically important to control for both observed and

unobserved selection. The importance of controlling 

for selection effects is demonstrated by the results from 

an unadjusted regression model that shows that SNF

patients are 2.7 percentage points more likely to be dead 

or institutionalized at 120 days after discharge from an

acute hospital as compared with patients going home

(Table 5-4, p. 112). The difference declines to 1.2

percentage points in the model adjusted for observable

patient characteristics. The difference declines further 

to 0.46 percentage points in an instrumental variable (IV)

model that is designed to capture unobserved 

selection effects.

Using IV models, researchers found that compared with

patients who went home after surgery, patients who 

used IRFs and SNFs are more likely to be dead or

institutionalized 120 days after discharge from an acute

hospital by 0.18 and 0.46 percentage points, respectively

(Table 5-4, p. 112). It is important to note that neither

IRFs nor SNFs have a significant statistical effect when

mortality by itself is the outcome; therefore, the effect

appears to be operating through institutionalization alone. 

The IV models provide the best estimates of the causal

effect of post-acute care on outcomes, but the researchers

were unable to rule out the possibility that some selection

remains in these estimates. Outcomes depend on many

factors, including patients’ physical and cognitive abilities,

underlying medical conditions, sensory and emotional

factors, willingness to participate in care, and supportive

environments. No risk adjustment approach can control for

every factor affecting outcomes of care (Iezzoni 2003).

The choice of IVs was carefully considered to address this

problem, but the estimates could be biased if the

instruments are invalid. Another limitation of the study is

that the outcomes analyzed are not the ideal outcomes for

patients who have had hip or knee replacements. The

preferred outcomes analysis would examine changes in

patients’ functional status, but the data are not available

for all patients.

Differences in Medicare payments 

Instrumental variable analyses show that IRF patients cost

Medicare more than patients who go home and more than

patients who use SNFs. Patients who use IRFs cost about

$8,000 more in Part A spending than those who go home

after surgery, and patients who use SNFs cost about

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 111

Functional status outcomes 

for patients with hip or 

knee replacement

Site of care after surgery

IRF SNF

Functional status for all patients

Mean score on Barthel Index

at admission (0–90) 46 55 **

Percentage of patients:

Walking independently 

at admission 10 % 20 %**

Transferring independently 

at admission 11 16 **

Functional status for patients 

with 14+ day stay✝

Mean score on Barthel Index (0–90):

at admission 35 47 **

at discharge 65** 58

Percentage of patients:

Walking independently 

at admission 1% 9 %**

Walking independently at 

discharge/14+ days 76** 31

Transferring independently 

at admission 2 8 **

Transferring independently 

at discharge/14+ days 79** 30

Note: IRF (inpatient rehabilitation facility), SNF (skilled nursing facility). 

Patients who were in a custodial nursing home before or after their acute 

stay, used acute rehabilitation (DRG 462), used long-term care 

hospitals, or died in the first 30 days after their acute discharge are 

excluded from this analysis. This excludes < 3% of the sample. Patients in 

the sample were hospitalized from January 2002 through June 2003.

** Indicates significant t-test for differences between IRF and SNF values at

the 0.0001 level. Asterisks are placed next to the higher of the two values. 

Barthel Index (Mahoney and Barthel 1965) created by mapping functional

status items from assessment instruments used in SNFs and IRFs. Higher 

scores on Barthel Index mean greater independence in functional status.

✝ Indicates discharge from IRFs; 14+ days means SNF patients assessed

at 14 days.

Source: Beeuwkes Buntin et al. 2005.

TABLE

5-3
$3,600 more in Part A spending than those who go home

after surgery (Table 5-4).3 Payment rates differ widely for

patients who are rehabilitated in IRFs versus SNFs.

Medicare pays IRFs on a per-case basis but pays SNFs on

a per-diem basis. Because of these different payment units,

it is not straightforward to compare, but in general,

Medicare pays IRFs more. The costs reported here are

incomplete because we do not include payments to

physicians or payments for outpatient therapy in the

spending comparisons. These results also highlight the

importance of controlling for selection effects, although

controlling for selection had a small effect in the payment

models compared with the outcome models. 

Discussion

We undertook this study to determine the impact the new

75 percent rule might have on beneficiaries and the

Medicare program. The evidence is not definitive. Some

descriptive and multivariate results suggest that marginal

patients may be institutionalized more frequently when

they use SNFs rather than IRFs, and more frequently in

both of these settings compared with those going home.

But the fact that patients going home after surgery do

better than those in either SNFs or IRFs suggests that

patient selection is strongly present in these data and we

cannot fully discount its effects. (See text box for a

description of study methods.)

In general, the results from the models show that in terms

of Part A costs, episodes in an IRF or SNF are much more

costly for Medicare than for episodes of care among

patients going home. The results also show that payments

for episodes of care involving IRF care are much higher

than episodes of care involving SNF care, even after

controlling for characteristics of patients and discharging

acute hospitals. 

112 Payment for p ost-acute care

Outcomes for patients with hip or knee replacement

Unadjusted Adjusted for Instrumental

model patient characteristics variable model

Marginal Marginal Standard Marginal Standard

Outcome effect effect error P-value effect error P-value

Dead or institutionalized at 

120 days after discharge

IRF vs. home after surgery 0.0058 0.0043 0.0004 0.00** 0.0018 0.0009 0.04*

SNF vs. home after surgery 0.0267 0.0120 0.0005 0.00** 0.0046 0.0008 0.00**

Dead at 120 days 

after discharge

IRF vs. home after surgery 0.0030 0.0020 0.0003 0.00** 0.0016 0.0012 0.18

SNF vs. home after surgery 0.0089 0.0038 0.0003 0.00** 0.0023 0.0012 0.06

Part A PAC payments

IRF vs. home after surgery $9,959 $9,050 $31 0.00** $8,298 $68 0.00**

SNF vs. home after surgery 6,028 4,685 33 0.00** 3,704 61 0.00**

Part A payments (PAC

payments + acute stay)

IRF vs. home after surgery $10,204 $8,871 $33 0.00** $8,023 $70 0.00**

SNF vs. home after surgery 6,116 4,590 35 0.00** 3,578 63 0.00**

Notes: IRF (inpatient rehabilitation facility), SNF (skilled nursing facility), PAC (post-acute care). Marginal effect is the change in predicted probability associated with 

changes in the explanatory variables. Post-acute payments are accumulated for 120 days after discharge from the acute hospital. Patients in the sample were 

hospitalized from January 2002 through June 2003.

* Indicates significance at the 0.05 level. ** Indicates significance at the 0.0001 level. 

Source: Beeuwkes Buntin et al. 2005.

TABLE

5-4
Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 113

Study methods for multivariate analyses

I

n this study sample, RAND included all elderly

Medicare beneficiaries who underwent a hip or

knee replacement with no preceding hip fracture

and who were discharged from an acute hospital

between January 2002 and June 2003 (Beeuwkes

Buntin et al. 2005). Researchers defined “post-acute

location” as the first Medicare-covered site in which 

the patient received care within 30 days of discharge

from an acute hospital. Excluded from the sample were

the following types of patients, who made up less than 

3 percent of the total:

• patients who died in the hospital or within 30 days

of discharge (<1 percent);

• patients who received custodial care in nursing 

homes before or after their admission to the acute 

hospital;

• patients discharged to long-term care hospitals from

acute hospitals;

• beneficiaries who enrolled in HMOs within four 

months of discharge; and

• patients who had incomplete personal information

or missing discharge hospital characteristics.

Independent variables

Researchers at RAND included a wide array of

independent variables that they expected would affect

beneficiaries’ choice of post-acute care. Examples of

individual predictors are age, gender, race, Medicaid

enrollment, and place of residence. To capture the

complexity of patients at the time of hospital discharge,

researchers included a large set of comorbidities and

complications tailored to joint replacement patients. To

capture factors that may influence post-acute use,

researchers used variables from the acute hospital, such

as average daily census, teaching status, ownership,

Medicare share, case-mix index, and low-income

patient percentage. Researchers defined availability of

post-acute care based on how close inpatient

rehabilitation facilities (IRFs) and skilled nursing

facilities (SNFs) were to patients’ homes and how many

of each type of facility were located within reasonable

distances of patients’ homes.

Outcomes

Researchers examined descriptive statistics on health

outcomes: residency in a nursing home at 60 days and

120 days; and death within 60 days and 120 days of

their acute hospital discharge. Researchers combined

the institutionalization and mortality variables into

composite measures to avoid the bias associated with

using variables for survivors only. 

Payments

Researchers adjusted payments for area wage

differences. They created summary variables for total

post-acute care payments and total episode payments.

The total episode payments combined payments for the

acute hospital stay and total post-acute payments.

Multivariate analyses

Researchers used multivariate analyses to estimate how

the site of care affected outcome measures. Multivariate

analysis controls for observable differences in the

patient population at each site of care—differences 

that might confound estimates of the site’s effect on

outcomes. In all models, researchers control for the

individual predictors, clinical predictors, and

characteristics of discharging hospitals.

Instrumental variables analyses

Researchers frequently use instrumental variable (IV)

methods to remove the estimates of confounding due to

unobservable characteristics. RAND used measures of

post-acute care availability as instruments. Because

these factors are not correlated with beneficiaries’

clinical needs, researchers use them to predict use of

IRFs and SNFs, and thus to infer the effect on outcomes

for a marginal patient. Researchers typically use IV

methods to control for the effects of selection bias, but

these methods do not always capture all these effects.

Beeuwkes Buntin and colleagues (2005) provide more

information on methods. As discussed above, functional status is the ideal measure

of outcomes for patients who have had a hip or knee

replaced. To determine the effect—on beneficiaries and 

on the program—of using different sites of care for

rehabilitation after hip or knee replacement, we would

need to compare functional status, walking, and transfer

across settings. One major problem in comparing these

measures is that SNFs do not assess patients’ functional

status at admission and discharge. For this and other

reasons, we recommended in our March 2005 Report to

the Congress that CMS collect information on functional

status at admission and discharge.

Comparing the patient assessment tools

used in post-acute care settings 

Policymakers need uniform data to monitor and evaluate

the quality of care and patient outcomes across post-acute

settings. Comparing post-acute patients across settings 

will likely require CMS to construct a new assessment 

tool that includes valid and reliable measures that use

consistent definitions, timeframes, and scales across the

post-acute settings. 

Common information across the post-acute sites is

currently not available. Medicare requires three of the 

four settings—home health agencies (HHAs), SNFs, and

IRFs—to use tools to assess patients, but each setting uses

a different tool. LTCHs are not required to use a tool to

assess patients. Because the information gathered by

clinicians differs across settings, it is not possible for CMS

to (a) compare the care needs or outcomes of patients who

are treated by different types of providers or (b) consider

this information when designing an integrated post-acute

care payment system. 

In this section, we compare the information gathered by

clinicians using each patient assessment tool. For

dimensions that are similar, we assess the aspects and

definitions of the care that the tools evaluate, the time

periods that the tools cover, and the measurement scales

that the tools use. We found that although the tools have

four aspects of care in common, the definitions of care

included in the measures, the timeframes covered, and the

scales used to differentiate patients vary considerably. The

differences among the tools limit how easily and

meaningfully we can consolidate these data and whether

we can evaluate patient outcomes across settings. 

Conducting the patient assessments

Medicare requires that clinicians in three post-acute

settings evaluate patients using specific assessment tools

(Table 5-5):

• The Minimum Data Set (MDS) must be used in SNFs.

• The Outcome and Assessment Information Set

(OASIS) must be used in HHAs. 

• The IRF–Patient Assessment Instrument (IRF–PAI)

must be used in IRFs. 

Medicare does not require LTCHs to use a patient

assessment tool. However, many LTCHs assess their

patients’ care needs using the Acute Physiology and

Chronic Health Evaluation (APACHE) and the 

Functional Independence Measure (FIMTM). Last year, 

the Commission discussed the need for all LTCHs to 

use the same patient assessment tool as part of a review

process for all admissions (MedPAC 2004). 

CMS developed the three instruments independently and

for different purposes. The IRF–PAI, the shortest

instrument, was designed to evaluate and monitor

outcomes of rehabilitation. The OASIS was originally a

quality measurement instrument. Because clinicians

furnish home health care in a noninstitutional setting, the

OASIS also assesses a patient’s ability to function at

home. CMS developed the MDS to ensure that each

beneficiary regularly received a comprehensive

assessment and care plan designed specifically for him or

her. Originally designed as a care-planning tool for longstay patients, many of MDS’s elements are not useful for

classifying and assessing short-stay SNF patients

(MedPAC 2003). 

Partly reflecting these different purposes, the tools vary

considerably in how frequently clinicians administer them

and the time period that the assessment covers; the type of

clinician who conducts the assessment, the method they

use, and how long the assessment takes; and the scales that

the tools use to differentiate patients. 

Assessment timeframes vary

The tools differ in terms of when a clinician conducts the

assessment during a patient’s course of treatment. SNFs

conduct patient assessments within five days of admission

and at specific intervals thereafter, but not necessarily on

the day of admission or discharge. In contrast, clinicians 

114 Payment for p ost-acute care
in HHAs and IRFs conduct the assessments primarily 

at admission and discharge. SNFs’ lack of assessments 

at admission and discharge poses particular problems for

evaluating these patients’ outcomes. Most SNF patients do

not stay long enough (14 days minimum) to be assessed 

a second time, making it impossible to measure patient

outcomes. In March, MedPAC recommended that CMS

collect information about activities of daily living (such as

the ability to walk)—one of the common measures used 

to assess patients—at admission and discharge in SNFs

(MedPAC 2005). 

The period of time reflected in the measures varies

considerably across the instruments. The time period

covered by many of the functional status measures in the

MDS is the previous seven days, compared with a single

point in time captured in the IRF–PAI and the OASIS. As

a result, even identical aspects of a patient could reflect

differing patient characteristics or abilities at a given point

in time. For example, an assessment of a wound infection

in a beneficiary at a SNF could mean that the patient had a

wound infection within the past seven days, whereas in an

IRF, this assessment would mean that the infection was

present at time of admission. 

Assessment methods vary

The tools also differ in terms of the types of caregivers

who may conduct the patient assessments and how the

assessor gathers the information. As a result, clinicians

may assess similar patients differently. In the MDS,

clinicians may gather information from direct observation,

interviews with multiple caregivers (including nurses,

aides, and therapists), and review of patient care

documentation. Direct patient observation is the preferred

method of gathering information for the OASIS and

IRF–PAI‚ but both instruments allow a combination of

direct observation and reported performance (including

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 115

Frequency, time period covered, and measurement scales differ 

across post-acute patient assessment tools required by Medicare

Inpatient 

Skilled nursing Home health rehabilitation Long-term

Dimension facilities agencies facilities care hospitals

Tool MDS OASIS IRF–PAI None

Frequency of assessments Initial (day 1–8); Initial at admission; At admission

day 14; day 30; every 60 days and discharge.

and every 30 days, thereafter; and

up to day 100. at discharge.

Time period covered Generally 7–day Status of patient Status on day 3

look-back. on day of assessment. (for admission) 

and at discharge.

Method of assessment Information gathered Direct observation Direct observation

from multiple caregivers’ preferred, but also often preferred but can

descriptions and used interviews with patient, be combined with 

documentation. Direct in-home caregiver. reported performance. 

observation not required.

Minutes to complete 90 minutesa 90 minutesb 25 minutesc

Note: MDS (Minimum Data Set), OASIS (Outcome and Assessment Information Set), IRF–PAI (Inpatient Rehabilitation Facility–Patient Assessment Instrument). a CMS 2002. 

b St. Pierre 2005.

c Buchanan et al. 2003.

Source: MedPAC analysis of patient assessment tools.

TABLE

5-5
patient interviews). The IRF–PAI requires that facilities

train their assessors to use the instrument; this training

may increase the reliability of different assessors’ ratings. 

The tools also require very different amounts of staff time

to complete. The IRF–PAI is the shortest form (taking an

estimated 25 minutes), while the OASIS and the MDS

take an estimated 90 minutes.4 A shortened version of the

MDS can be submitted to update a beneficiary’s condition,

but a full MDS must be completed within 14 days of

admission.

Assessment scales differ

The measurement scales used by the different tools vary in

several ways, making it difficult to compare the

information gathered with the tools. First, the number of

points on the scales varies, thus resulting in differing

distinctions between patients. For example, the MDS uses

a four-point scale to evaluate many aspects of functional

status, whereas the IRF–PAI uses a seven-point scale.

Even for a task such as bathing, which is relatively similar

in definition across settings, each tool codes the degree of

assistance that patients require differently. For example,

the MDS defines “independent” patients as those who use

assistive devices without help while walking or eating. In

contrast, the OASIS instrument distinguishes between

“complete” and “modified” independence. If categories

were collapsed, some of the detail currently collected

would be lost. 

Second, the scales can measure different aspects of a 

task, such as independence in performing an activity. 

For example, in the task of dressing, the gradations in the

IRF–PAI scale refer to the share of the individual tasks

that the patient performs, whereas the MDS scale

measures the number of times a patient needs assistance

and whether assistance involves any weight bearing. 

Third, the scorings across settings do not always

distinguish between verbal cues (such as encouragements

or reminders) and physical assistance (such as guided

maneuvers or weight-bearing support needed to

accomplish a task). The MDS and the IRF–PAI 

generally differentiate the types of help needed, but 

the OASIS typically does not. 

Only one of the tools—the MDS—separately records 

(a) the typical amount of help that patients need and 

(b) the most help that patients need in their most

dependent state. In contrast, the IRF–PAI and OASIS

instruments capture a patient’s status at one point in 

time, which neither MDS measure captures. 

Common dimensions of care assessed

differ across tools 

The tools that Medicare requires have four common

dimensions that clinicians assess for every patient: 

(1) diagnoses, (2) comorbidities, (3) functional status,

and (4) cognitive status. But within each dimension, the

aspects of care that clinicians evaluate vary considerably

across the three tools. 

Diagnoses and comorbidities

Of the four dimensions, researchers generally find

diagnoses and comorbidities the simplest to compare

across settings. Yet little consistency exists in the

recording of diagnostic information. MDS currently 

does not gather International Classification of Diseases,

116 Payment for p ost-acute care

Patient assessment tools do not consistently use diagnosis codes 

Dimension MDS OASIS IRF–PAI

ICD–9–CM codes Not used 3 digits 5 digits

Number of diagnoses reported Unlimited items can Primary +5 Impairment category 

be checked off a set list secondary diagnoses +10 comorbidities

Note: ICD–9–CM (International Classification of Diseases, Ninth Revision, Clinical Modification), MDS (Minimum Data Set), OASIS (Outcome and Assessment Information 

Set), IRF–PAI (Inpatient Rehabilitation Facility–Patient Assessment Instrument). Impairment categories are broad clinical categories used by the prospective payment 

system for inpatient rehabilitation facilities. Examples include traumatic and nontraumatic spinal cord injuries, stroke, and traumatic and nontraumatic brain injuries. 

Source: MedPAC analysis of patient assessment tools.

TABLE

5-6
Ninth Revision, Clinical Modification (ICD–9–CM) 

codes and instead uses checkoff lists for diagnoses and

health problems (Table 5-6). The OASIS requires that

only three of the five digits of the ICD–9–CM codes be

completed (where the first three digits refer to a broad

condition and the last two digits add specificity), thus

limiting patient comparisons. In administering the

IRF–PAI, clinicians may collect up to 10 comorbid

conditions using ICD–9–CM codes, but the basic patient

classification system requires a special “look-up” table to

match “impairment groups” to ICD–9–CM codes. Before

patients treated in IRFs can be compared with patients

treated in other settings, the impairment group for each

IRF patient needs to be mapped to an ICD–9–CM code. 

The lack of uniform ICD–9–CM coding also limits the

comparison of the severity of patients treated in different

settings. Severity measurement systems, such as the all

patient refined diagnosis related group (APR–DRG),

require five-digit ICD–9–CM coding to differentiate

among patients. Because SNFs do not gather ICD–9–CM

codes, the severity of their patients’ diseases cannot be

assessed. Furthermore, although the OASIS does not

gather complete ICD–9–CM code information, it asks

clinicians to rate each diagnosis on a four-point severity

scale. While these ratings can assess the severity of

patients within HHAs, they do not help with comparisons

across settings. 

Functional status

Despite many similarities in the aspects of functional

status that are assessed by the tools, the definitions of 

the activities vary considerably. All three tools assess a

patient’s ability to walk, transfer (e.g., the ability to move

between bed and chair), eat, dress, use a toilet, and do

personal grooming. Yet within each category of care, the

definition of the care the clinician evaluates varies across

the tools—this variation could translate into meaningful

differences in the patient’s care needs (Table 5-7). For

example, in assessing a patient’s ability to walk, the

IRF–PAI rates the distances the patient walks, whereas 

the MDS evaluates the amount of assistance the patient

needs to walk within his or her room, down the hall, or to

a different part of the facility. In assessing toilet use, one

tool considers only the patient’s ability to get to and from

the toilet, while another considers other aspects of toilet

use but specifically excludes this one. The OASIS is 

the only tool that assesses the beneficiary’s ability to

perform instrumental activities of daily living (such as

housekeeping and meal preparation), reflecting the

noninstitutional setting of this care. 

Researchers who compared the functional status

dimensions of MDS, OASIS and the FIMTM (which

formed the basis of the IRF–PAI) found that although 

each measure was well suited for measuring patient status

within its setting, none was well equipped to monitor 

the quality and outcomes across post-acute settings 

(Jette et al. 2003). 

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 117

Examples of the differences in functional status measures included in 

post-acute patient assessment tools required by Medicare 

Dimension MDS OASIS IRF–PAI

Walking Amount and type Ability to walk or Distance walked. 

(e.g., weight bearing to use a wheelchair 

or encouragement) on a variety

of assistance required. of surfaces.

Toilet use Various aspects of toileting Ability to get Various aspects of 

including transfer on and to and from toilet. toileting but excludes

off toilet. No mention of transfer on and off

getting to/from toilet. toilet. No mention of 

getting to and from toilet.

Note: MDS (Minimum Data Set), OASIS (Outcome and Assessment Information Set), IRF–PAI (Inpatient Rehabilitation Facility–Patient Assessment Instrument). 

Source: MedPAC analysis of patient assessment tools.

TABLE

5-7
Cognitive status

The cognitive status of patients is the assessment item that

varies most across the three tools. Not only does the range

of measures vary considerably, but measures of the same

dimension of cognitive ability are also quite different

(Table 5-8). For example, the MDS evaluates 13 aspects

of cognitive status, including 6 measures for delirium and

16 for depression. The OASIS records information about 

5 indicators of depression, while the IRF–PAI does not

directly ask about it. The tools do not consistently require

clinicians to separately record behaviors (such as

wandering, or physically or verbally disruptive behavior)

that may influence the amount of staff assistance required.

Three measures in the IRF–PAI—short-term memory,

social interaction, and problem solving—are broad and

could span considerable differences in patients and their

resource requirements. 

In addition to differences in measurement, differences in

the definitions of cognitive status across the tools also

exist. Although each tool evaluates the patient’s ability 

to make decisions, examples of the types of decisions

patients should be able to make to be considered

“independent” vary widely across the tools. For example,

the MDS assesses a patient as independent if she can 

make decisions to organize her daily routine (such as

knowing when to go to lunch and picking out clothing).

By comparison, the IRF–PAI distinguishes between

complex and routine decisions. The IRF–PAI assesses a

patient as independent if she can solve complex problems

such as managing a checking account. 

118 Payment for p ost-acute care

Wide range in cognitive status measures evaluated by patient assessment tools

MDS OASIS IRF–PAI

Comatose

• Comatose (yes/no) • Comatose not reported • Comatose (yes/no)

Memory

• Memory: short– and long–term • Cognitive functioning • Short–term memory

• Memory recall ability (includes alertness, orientation, • Problem solving

• Cognitive skills for daily decision making concentration, and immediate • Delirium (yes/no)

• Indicators of delirium (6 elements) memory for simple commands)

• Frequency of confusion

Communication

• Making oneself understood • Ability to express oneself • Expression

• Ability to understand others • Ability to hear and understand • Comprehension

spoken language

Depression

• Indicators of depression, • Depressive feelings reported • Social interaction

anxiety, sad mood (16 elements) or observed (5 elements) 

• Mood persistence • Frequency of anxiety 

• Behavioral symptoms • Behavior demonstrated (includes

(such as wandering, or verbally verbal disruption, physical

or physically abusive behavior) aggression, socially inappropriate 

behavior) and frequency. 

Other

• Sense of involvement

• Unsettled relationships

• Past roles

Note: MDS (Minimum Data Set), OASIS (Outcome and Assessment Information Set), IRF–PAI (Inpatient Rehabilitation Facility–Patient Assessment Instrument). 

Source: MedPAC analysis of patient assessment tools.

TABLE

5-8
Building a uniform patient 

assessment tool

MedPAC’s analysis shows that the current assessment

tools that Medicare requires do not collect information 

that is easily and meaningfully integrated. If CMS were 

to build on the existing patient assessment tools, the data

would still not be consistent due to the large differences 

in timeframes, scales, and many of the definitions.

Furthermore, the current post-acute PPSs together 

require considerable information to establish payments

(see text box). 

In designing a new patient assessment tool, data elements

should be selected so that CMS can establish payments

and evaluate patient outcomes across all four post-acute

settings. CMS has started this process (see text box, 

p. 120). Data elements need to predict resource use;

capture relevant clinical data; be reliable, valid, and well

accepted; and minimize the burden to providers and 

CMS. In addition to evaluating elements of the patient

assessment tools currently required by Medicare, the

merits of other assessment tools (such as the Mini-Mental

State Examination, the APACHE, and the Nursing

Severity Index) should be considered. 

Ideally, hospital discharge planners would use a uniform

patient assessment tool to assess patients (and whether

they can go home safely) prior to discharge from the acute

hospital, identify the most appropriate post-acute

setting(s), and discuss the placement option(s) with the

beneficiary. Until a uniform tool is routinely collected, the

Commission will consider the idea of using site-specific

admission criteria to place patients in the most appropriate

post-acute settings. In 2004, MedPAC recommended that

CMS develop patient and facility criteria to ensure that

patients treated in LTCHs are medically complex and 

have a good chance of improvement (MedPAC 2004). 

In 2005, the Government Accountability Office (GAO)

recommended that CMS develop more specific

descriptions of the patients appropriate for IRFs (GAO

2005). Expanding on these ideas, establishing settingspecific criteria could delineate the service capabilities 

and staffing levels for the provider, and could identify 

the clinical characteristics (including functional status) 

and resource needs of the patients.

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 119

Extensive data collection required to classify patients in 

Medicare’s post-acute PPSs

Medicare’s four prospective payment systems (PPSs)

for post-acute care use many data elements to classify

patients into payment groups.

Diagnoses and clinical characteristics

International Classification of Diseases, Ninth Revision,

Clinical Modification (ICD–9–CM) codes;

rehabilitation impairment codes; change in weight;

urinary and bowel incontinence; impaired vision;

frequency of pain; skin condition (surgical

wounds/lesions, number and stage of pressure ulcers);

age; sex

Functional status

Activities of daily living—dressing, bathing,

transferring, toileting, ambulation and locomotion, bed

mobility, grooming, bladder and bowel control

Cognitive status

Comatose, memory, decision making, comprehension,

communication, social interaction, depression,

verbal/physically abusive or disruptive behavior,

hallucinatory/delusional/paranoid

Services provided

Rehabilitation therapy, intravenous/infusion therapy,

total parenteral nutrition, intravenous feeding, daily

injections for diabetes, chemotherapy, dialysis,

respirator/ventilator support, tracheostomy care,

oxygen therapy, suctioning, transfusions, radiation

therapy, amputation and prosthesis care, range of

motion, physician visits

Other

Preceding inpatient hospital, rehabilitation facility, or

skilled nursing facility stay; total charges; discharge

status Assessing the skilled nursing facility PPS

In this section, we review concerns with the resource

utilization group, version III (RUG–III) system. We begin

by explaining how the classification system functions as 

a case-mix system to adjust SNF payments for patients

with higher- and lower-than-average resource use. We

then discuss problems with the payment system that stem

from how the case-mix system (1) does not adequately

distribute payment for nontherapy ancillary (NTA)

services and (2) categorizes patients based on the amount 

of services SNFs provide or expect to provide. Next, we

discuss payment system concepts that may address each 

of these problems. We conclude with a description of

possible directions for future work to improve the SNF

payment system. 

How does the current PPS buy SNF

services?

Medicare’s SNF benefit covers SNF care for beneficiaries

who, following an inpatient hospital stay of three or more

days in the month preceding the SNF admission, need

skilled nursing care. The SNF payment system pays

hospital-based and freestanding SNFs a case-mix adjusted

daily rate for up to 100 days of care per beneficiary.

However, almost 60 percent of SNF stays lasted just 20 or

fewer days in 2001, and only about 9 percent of covered

SNF stays were longer than 60 days (Figure 5-2). The

mean covered LOS for all Medicare-covered SNF stays

was about 24 days. In 2003, Medicare paid $14 billion for

about 57 million days of SNF care.

120 Payment for p ost-acute care

CMS activities to develop a uniform assessment tool 

The Medicare, Medicaid, and State Children’s

Health Insurance Program Benefits

Improvement & Protection Act of 2000 (BIPA)

instructed the Secretary to report by January 2005 on

the development of an instrument to assess the health

and functional status of beneficiaries who use postacute services. BIPA required developers to create 

an instrument that would collect data that are readily

comparable and to gather only the information

necessary to meet program objectives. To date, 

CMS has not developed the instrument. 

Although CMS has not focused on the development of

an assessment tool, it has pursued the more fundamental

task of examining the consistency of the definitions and

terms used to evaluate the quality of post-acute care.

With an eye toward adopting standard terminology to

encourage the use of clinical information technology,

CMS and the Office of the Assistant Secretary for

Planning and Evaluation (ASPE) of the Department 

of Health and Human Services have collaborated to

examine the consistency of vocabulary terms and

definitions that describe key aspects of patient

condition, such as “functional status.” In a recent 

study, ASPE found that one medical terminology

system—Systematized Nomenclature of Medicine—

included many of the terms experts said were needed to

assess the quality in nursing homes in three domains:

pain management, incontinence, and pressure ulcers

(ASPE 2003). However, this study also found that the

Minimum Data Set (MDS)—the only tool examined—

did not adequately gather the data elements the experts

said were necessary to evaluate these aspects of care. In

addition, the researchers of the study reported that most

of the information the MDS gathered was not covered

by any of the three medical terminology languages

examined—this lack of coverage would seriously limit

the meaningful integration or exchange of these data.

An ASPE-led group of federal agencies involved with

disability (such as the Veterans Administration and the

Social Security Administration) also concluded that no

standardized terminology provided sufficient coverage

of the functional status concepts needed by the federal

government, including the functional status concepts

reflected in the three post-acute assessment instruments.

In a separate study, ASPE also examined the use of

advanced electronic health records (EHRs) in skilled

nursing facilities (SNFs). In a set of site visits to SNFs

that have state-of-the-art electronic health records,

ASPE found that SNFs typically did not integrate

information stored in the EHR and the patient

assessment tools. As a result, the detailed clinical

information housed in the EHR was not available 

to the patient assessment tool, and vice versa. The SNF daily rate consists of two component base

rates—one for nursing and one for therapy—that are

case-mix adjusted up or down depending on the patient’s

relative resource use. Under a PPS, adjusting the base

payment rates for case mix gives providers equal

incentives to treat patients who require different levels 

of resources. CMS developed the nursing and therapy

base rates from 1995 SNF costs inflated to 1998 (the first

year of the PPS phase-in for SNFs) according to rules

prescribed in the Balanced Budget Act of 1997 (BBA). 

Medicare’s payment system adjusts SNF nursing and

therapy base rates for expected resource use employing

weights associated with the each of 44 RUG–III

categories. The 44 groups fall into 7 major categories: 

(1) rehabilitation, (2) extensive services, (3) special 

care, (4) clinically complex, (5) impaired cognition, 

(6) behavior only, and (7) reduced physical function. 

For rehabilitation groups, the payment system applies

associated nursing and therapy indexes to the nursing and

therapy base payment rates to adjust for relative resource

use of each category (Figure 5-3). The nonrehabilitation

groups have a constant component for therapy instead of

an adjusted therapy base rate. All RUG–IIIs also have a

constant “non-case-mix component” to cover costs that 

the payment system considered to be uniform across all

patients, such as room and board. Once the base rates have

been adjusted for case mix, the payment system adjusts a

portion of the payment for geographic differences in labor

costs using the hospital wage index.

The payment system’s assignment of a beneficiary to a

RUG–III category is based on the number of minutes 

of therapy (physical, occupational, or speech) that the

patient has used or is expected to use; the need for certain

services (e.g., respiratory therapy or specialized feeding);

the presence of certain conditions (e.g., pneumonia or

dehydration); an index based on the patient’s ability to

perform independently four activities of daily living

(ADLs) (eating, toileting, bed mobility, and transferring);

and in some cases, signs of depression. As we discussed

earlier in this chapter, the payment system’s assignments

of SNF patients to case-mix groups are determined by the

SNFs’ required periodic patient assessments using the

MDS. SNF staff assess patients using the MDS at the 

5th, 14th, 30th, 60th, and 90th day of their stay. The

assessment at day 5 determines Medicare payment for

days 1 through 14 of the stay; assessment at day 14

determines Medicare payment for days 15 through 30 

of the stay, and so on. 

The first decision that determines a patient’s RUG–III

assignment is whether that patient receives or is expected

to receive at least 45 minutes of therapy per week 

(Figure 5-4, p. 122). If patients meet this therapy

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 121

Note: SNF (skilled nursing facility).

Source: MedPAC analysis of SNF stay file for SNF admissions in 2001.

14%

1–5 days

31%

6–14 days

14%

15–20 days

15%

21–30 days

17%

31–60 days

6%

61–90 days

3%

91–100 days

Distribution of SNF stays,

by length of stay, in 2001

FIGURE

5-2

Determining case-mix adjusted 

SNF payment rate 

FIGURE

5-3

Case-mix adjusted SNF per diem rate

Nursing base rate

x nursing index

Therapy base rate

x therapy index

OR

Therapy non-case-mix

base rate

Non-case-mix

base rate

Note: SNF (skilled nursing facility).

+ +
threshold, the classification system places them into one 

of 14 rehabilitation RUG–IIIs based on the number of

therapy minutes per week, types of therapy, and ADL

score. On the first MDS assessment, a patient can be

categorized into a high, medium, or low rehabilitation

group using an estimate of the amount of therapy that 

will be provided, rather than the actual amount provided,

during the first two weeks. To be classified into one of the

ultra high or very high rehabilitation groups on the first

MDS assessment, patients must actually have received 

the minimum amount of therapy for a given group at the 

time that the SNF completes the patient assessment. 

For all subsequent assessments, the beneficiary must 

have already received the minimum amount of therapy

that defines a group in order to be categorized in that

group (GAO 2002).

The classification system categorizes patients who do not

receive 45 minutes of therapy per week—but who have

certain characteristics and still require skilled care—into

the extensive services, special care, or clinically complex

groups. Medicare typically does not reimburse SNFs 

for patients in the bottom three RUG–III categories

because they usually do not require skilled care. CMS

decides to reimburse for patients in these categories on 

a case-by-case basis. 

The RUG–III system is hierarchical; beneficiaries may

qualify for multiple categories, but the classification

system assigns them to the highest payment category for

which they qualify. For example, a patient could meet the

criteria for being classified in an extensive-care RUG–III

but could also receive enough therapy to be classified into

122 Payment for p ost-acute care

RUG–III classification scheme

FIGURE

5-4

Note: RUG–III (resource utilization group, version III).

Source: Figure adapted from GAO 2002.

Patients 

receive 

at least 

45 minutes 

of therapy 

per week

Patients 

do not

receive 

at least 

45 minutes 

of therapy 

per week

Ultra high (over 720 minutes)

Very high (500–719 minutes)

High (325–499 minutes)

Patients 

require skilled 

or extensive

services

Patients 

typically do not

require skilled

nursing care

Rehabilitation

patients

Medium (150–324 minutes)

Low (45–149 minutes)

Extensive services

Special care

Clinically complex

Impaired cognition

Behavior only

Reduced physical function

3 RUGs

3 RUGs

3 RUGs

3 RUGs

2 RUGs

3 RUGs

3 RUGs

6 RUGs

4 RUGs

4 RUGs

10 RUGs

All

patients
a high-rehabilitation RUG–III.5 In such a case, the patient

would be categorized into the high-rehabilitation RUG–III

that corresponded to his or her score on an ADL index,

and Medicare would pay the SNF the high rehabilitation

RUG–III rate. 

A review of SNF PPS problems and

potential improvements

MedPAC, GAO, CMS, and the SNF industry have

identified and discussed several shortcomings of the

classification system since the implementation of the SNF

PPS (CMS 2000a; Fries et al. 2000; GAO 1999; Kramer 

et al. 1999; MedPAC 2000, 2001, 2002; White 2003;

White et al. 2002). Among the problems researchers 

have identified for improvements are the system’s

payment for nontherapy ancillary services and payment

for rehabilitation services according to the amount of

service provided rather than patient characteristics.

Various revisions to the PPS potentially can address

current problems, but additional research is needed to

assess the merits of any payment system alternative.

Payments for nontherapy ancillary services

not adequately addressed by case-mix

system

The BBA required that Medicare’s prospective payment

bundle for SNFs include payment for NTAs, such as

prescription drugs and respiratory therapy. In compliance

with this mandate, CMS included the cost of NTAs as part

of the total costs used to develop Medicare’s SNF base

payment rates. However, NTA costs were not used to

develop the RUG–III case-mix indexes that adjust the base

payment rates according to patients’ resource use. Instead,

the payment system distributes payments for NTAs using

the weights that are used to allocate payment for nursing

care. As a result, the payment system does not distribute

payments for NTAs according to variation in expected

NTA costs across different patient types. 

The dispensing of medications is one service that

illustrates the possible disconnect between staff time to

provide a service and the cost of that service. For example,

two medications may differ substantially in cost, but the

staff time it takes to dispense the expensive drug and 

the inexpensive drug may be the same. In this case, the

payment system does not adjust payments to the SNF

dispensing the expensive drug to reflect the higher cost of

the medication; instead payments are distributed equally

according to staff time. SNFs that treat a higher-thanaverage share of patients with higher-than-average NTAs

will be disadvantaged by the payment system relative to

facilities that treat a lower-than-average share of these

patients. In addition, facilities may have an incentive to

systematically avoid patients expected to have high NTA

use or to stint on the provision of NTA services.

The current classification system may exacerbate the

problem of the lack of case-mix adjustment for NTA

resource use by assigning patients to the highest category

for which they qualify in the RUG–III hierarchy. This

classification method categorizes SNF patients with

heterogeneous resource needs into the same groups 

and pays the same rate for them. For example, the

classification system classifies patients with extensive

service needs who also qualify for a rehabilitation

RUG–III into a rehabilitation group. Similar to patients 

in the extensive services category, these extensive

service/rehabilitation patients have, on average, higher

staff time costs and much higher NTA and total costs 

than rehabilitation patients who do not also qualify for an

extensive services category (White et al. 2002). However,

the current SNF case-mix system does not recognize this

variation because it does not adjust for case mix based 

on these NTA-related patient differences within payment

groups. Failure to adequately differentiate among patients

with varying resource needs means that Medicare is not

paying accurately for patients, causing some patients to 

be more or less profitable for facilities than others.

Since CMS implemented the SNF PPS, researchers and

CMS have given considerable attention to the failure 

of the case-mix system to account for variations in 

NTA costs (CMS 2000a). Researchers estimate that NTA

costs represent, on average, about 16 percent of total costs

(GAO 2000, White et al. 2002), but these NTA costs vary

widely across patients (White et al. 2002). Researchers

using 1995 data found that the RUG–IIIs predict

approximately 40 percent of the variance in staff time 

but only 4 percent of the variance in per diem ancillary

charges (Fries et al. 2000).6 They also found that the

RUG–IIIs accounted for 10 percent of the variance 

in total costs. 

Current payment system allows higher

payments for providing additional services 

Another criticism of the SNF PPS is that it determines the

payment rate based on the amount of services the patient

uses, or is expected to receive, rather than on patient

characteristics and clinical appropriateness (MedPAC

2004, GAO 2002). However, those in favor of this feature

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 123
of the SNF PPS assert that categorizing and paying for 

the amount of therapy provided counters incentives in 

the PPS for SNFs to stint on therapies. The system has 

two incentives related to the provision of therapy. The first

incentive is for SNFs to provide additional therapy to

achieve a higher payment category even though the 

patient may not benefit from additional therapy. Second,

because the payment system pays a fixed rate for ranges 

of therapy minutes provided—45 to 149 minutes (low),

150 to 324 minutes (medium), 325 to 499 minutes (high),

500 to 719 minutes (very high), and more than 720

minutes (ultra high)—providers face an incentive to

provide the fewest number of minutes in the highest

achievable payment category because therapy times at 

the bottom of the categories have the lowest cost relative

to revenue (Wodchis 2004, White 2003). 

Several studies have found evidence that SNFs may have

responded to therapy-related payment incentives in the

PPS. Consistent with the incentive to classify patients into

rehabilitation groups since implementation of the PPS,

more patients were categorized into high and medium

rehabilitation groups and fewer into the highest and lowest

categories at patients’ initial assessments (GAO 2002,

OIG 2003). Providers’ payments for these high and

medium rehabilitation groups reportedly had the highest

payment relative to costs (GAO 2002, White 2003). White

also found that the proportion of residents receiving no

rehabilitation therapy also declined between 1997 and

2000. Consistent with incentives to provide minutes of

therapy at the low end of the range for a given payment

category, patients in the medium and high rehabilitation

categories—upon their initial assessment—received at

least 30 fewer minutes of therapy per week in 2001 than 

in 1999; half of the patients initially categorized into these

two groups did not actually receive the minimum minutes

to be classified in these groups (GAO 2002). GAO

explained this latter finding, in part, by more patients

being classified using estimated rather than actual therapy

minutes (GAO 2002). Changes in patient characteristics

could have contributed to these changes, but the Office of

Inspector General (OIG) did not find substantial shifts in

the gender, race, age, or reason for eligibility of Medicare

beneficiaries who used SNFs from January 1999 to

December 2002 (OIG 2003).

Refining the RUG–III system to address 

NTA payment

Recognizing the problem of the payment system’s failure

to properly distribute payments for NTAs, CMS undertook

research “to review the RUG–III classification system

with particular emphasis on the care needs of medically

complex Medicare beneficiaries and the variation in

nontherapy ancillary services within RUG–III categories”

(CMS 2000a). To evaluate potential improvements to, but

not replacement of, the RUG–III system, CMS awarded 

a contract to Abt Associates, Brown University Center 

for Gerontology and Health Care Research, and the

University of Michigan’s Institute of Gerontology in 1999

(Fries et al. 2000). These researchers found, among other

things, that patients in the extensive services category had

higher NTA costs than patients in other categories. 

In their final report in 2000, the contractors recommended

that CMS consider adding 14 new groups to the top of 

the RUG–III hierarchy for SNF patients who qualify for

the rehabilitation and extensive services category. This

proposal was called the “RUG–III+ model,” which had 

58 payment groups instead of 44. However, this change

alone did not directly address the NTA payment issue. 

To address the failure of the case-mix system to distribute

payment for NTA costs, the contractors also proposed

applying a weighted or unweighted nontherapy ancillary

index model to the new RUG–III+. Researchers developed

these indexes from MDS items (e.g., suctioning,

tracheostomy care, IV medication) that were found to 

be significantly related to per diem nontherapy ancillary

(drug, respiratory therapy, and other ancillaries) costs. 

The index would determine an additional payment for

nontherapy ancillary care for each day of SNF care. 

Based on the contractors’ findings that this refined case-mix

system had improved ability to predict variance in total and

NTA costs, CMS issued a proposed rule in April 2000 to

refine the case-mix system using the RUG–III+ and the

unweighted index model (CMS 2000a). But in the July 

final rule, CMS announced the results of testing the models

on post-PPS national-level data (CMS 2000b). CMS found

that these models did not improve the ability of the casemix system to explain cost variance enough to warrant

changing the SNF payment system. Therefore, CMS did 

not implement the refinements in the proposed rule. 

Although this specific model proved less successful when

tested on later, national-level data, an index that is similar

in concept could again be developed from national-level

data to explain NTA costs. Additional research to identify

variables that better predict NTA costs would be required. 

124 Payment for p ost-acute care
Outlier policy may not be optimal way to

address NTA payments

Some have suggested that the Medicare PPS for SNFs

should have an outlier policy to pay for high-cost patients.

Many Medicare PPSs for other settings include an outlier

policy that recognizes the extraordinary costs of certain

cases and defrays some of these costs that exceed certain

cost thresholds. Ideally, such a policy does not undercut

incentives to be efficient but at the same time encourages

providers not to avoid especially costly cases and 

protects providers from unpredictable and unavoidable

financial risks. An outlier payment can be a desirable

policy in a PPS to prevent a provider from trying to avoid

excessively costly patients and to protect providers from

extreme financial losses. But the problem of consistent

underallocation of payment for certain types of costs—

such as NTAs in the SNF PPS—may argue more strongly

for fundamentally refining the case-mix system to better

distribute payments according to these costs rather than

imposing an outlier policy.

Another feature of the SNF PPS—although not an 

outlier policy per se—may diminish the need for a 

SNF outlier policy. Certain high-cost, infrequently

provided services such as ambulatory surgery performed

in operating rooms, certain chemotherapy agents, and

customized prosthetic devices are currently excluded 

from the SNF payment bundle and paid for separately

(GAO 2001). This policy mitigates for providers the

financial risk of treating patients who need these excluded

services. By excluding high-cost, infrequently provided

services from the payment bundle, CMS may reduce the

number of cost outlier cases that might otherwise occur if

these services were included in the per diem rate. 

Alternative classification system using SNF

patient characteristics

One potential option that CMS could explore to improve

the SNF PPS is replacing the RUG–III classification

system with an entirely different classification scheme

based on patient characteristics that are correlated with 

all SNF resource use. Before CMS implemented the SNF

PPS, Cotterill tested the ability of a diagnosis related

group (DRG)–based case-mix index to predict Medicare

SNF patient resource use at the facility level (Cotterill

1986). Because a SNF stay follows a hospitalization, 

using the same classification method used to pay hospitals

was appealing because, at the time, this method would 

not have required the development of a SNF-specific 

case-mix measure. 

However, Cotterill also noted that DRGs may not be 

good predictors of care needs for SNF patients because 

of evidence that “diagnosis is not a strong predictor of

differential use of nursing home resources for Medicare

SNF patients.” A significantly positive relationship 

existed between SNF costs and the SNF diagnosis-based

index, but the explanatory power in the SNF setting was

weaker than the relationship between hospital costs and

the hospital index. However, the diagnosis-based index

was a better predictor of costs in SNFs that had a high

share of Medicare patients than in facilities that had a 

low share of Medicare patients. One explanation for 

the DRGs’ relatively weak prediction of SNF patients’

resource use is that DRGs do not measure functional

status, which researchers have found to be an important

factor predicting post-acute resource use (Clauser and

Bierman 2003).

A DRG-based case-mix index or a similar diagnosis-based

case-mix system may hold some promise and appeal as 

an alternative payment classification system to RUG–III.

A classification system based on patient characteristics

may be less influenced by provider behavior than a

classification system based on the amount of services

provided. Similar to what Abt and colleagues proposed 

in their RUG refinement research, other variables such 

as measures of SNF patients’ functional status could

possibly be added to a diagnosis-based system to predict

SNF patients’ resource use. Again, additional research is

needed to determine what variables explain cost variation

in SNF patients and whether valid data are currently

available to develop these variables. Such research could

explore whether distinct, identifiable subgroups of patients

exist in SNFs—subgroups that the current payment

classification system does not capture. Examples of these

subgroups include patients who have short stays and are

recovering from acute conditions versus those who 

have longer SNF stays and become (or resume being) 

a nursing home resident.

SNF PPS revisions should address

current shortcomings

CMS should improve the PPS for SNFs to better 

distribute payments for patients with different resource

needs. To accomplish this task, CMS would need to

address the current shortcomings of the SNF PPS by

better distributing payment for NTA costs and paying 

for care based on patients’ needs and characteristics 

rather than on the services SNFs provide. 

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 125
CMS’s report on the study—mandated in the Medicare,

Medicaid, and SCHIP Benefits Improvement and

Protection Act of 2002—of “the different payment

systems for categorizing patients in Medicare skilled

nursing facilities in a manner that accounts for the relative

resource utilization of different patient types” should

evaluate potential alternative systems for classifying

patients and how those alternatives compare to the current

system. The report on this study was due to the Congress

on January 1, 2005, but as this MedPAC report was 

going to press, CMS had not provided their report to the

Congress. It is not clear when CMS will release their

report. However, MedPAC expects CMS to release a

proposed rule that addresses potential payment system

refinements in May 2005, and MedPAC will comment 

on any proposed payment system changes. We will also

pursue analyses of different SNF payment system

options— including refinements to the current RUG–III

case-mix system, alternative patient classification systems,

and various state-level nursing home payment systems—

to determine the potential for any of these options to

improve the SNF payment system.

Assessing the home health PPS

CMS implemented the home health PPS on October 1,

2000. We began our assessment of the home health PPS in

2004 with an analysis of the PPS outlier provision. Our

findings from that analysis, combined with other evidence,

suggest that the current PPS may not be working

optimally. This section expands upon that analysis. We

briefly describe the current PPS, focusing on how the

case-mix classification works; review some of the current

problems with the PPS; and conclude with plans to further

investigate the PPS. 

How does the current PPS buy home

health services?

Medicare pays for home health service in 60-day units

called episodes. Episodes begin when home health

agencies admit patients to home health care. Most patients

complete their course of care, and agencies discharge

them, before 60 days have passed. If agencies do not

complete patients’ care within 60 days, another episode 

of payment may start without a break in their care. 

Agencies receive a base payment of $2,268 per episode 

for home health services in 2005. The base payment is

case-mix adjusted to account for differences in patients’

expected resource needs, as reflected by their clinical and

functional severity, recent use of other health services, 

and therapy use. Nurses or therapists record patients’

conditions using OASIS, a standardized home health

patient assessment tool, to score patients’ health on

admission. Figure 5-5 illustrates the OASIS items 

that describe the patient and the possible scores. The 

80 case-mix groups—called home health resource 

groups (HHRGs)—in the home health PPS represent all

combinations of the scores in the three domains (4 clinical

✕ 5 functional ✕ 4 service = 80 case-mix groups). 

Payment also is adjusted for differences in local prices by

the hospital wage index. Adjustments for several other

special circumstances, such as unusually high costs or

very short episodes, can also modify the payment.

Some problems with the 

home health PPS

All PPSs are likely to suffer from several “pathologies”

(Newhouse 2002). Among them is the failure to account

for economies of scale. Also, if small providers draw an

unfavorable mix of patients, they may be disadvantaged

by a system that depends on relatively more profitable

patients “subsidizing” the costs of relatively less-profitable

ones to pay appropriately on average. Furthermore, the

case-mix system within a PPS frequently fails to account

for variations within case-mix groups. These problems

lead to a mismatch of payments and costs at the patient

and agency level. Evidence suggests that the home health

PPS shows symptoms of each of these pathologies.

Finally, Medicare’s PPSs pay the same amounts 

regardless of quality.

The PPS does not account for economies of scale; 

smaller agencies have higher per-episode costs because

they spread their overhead costs over fewer episodes. 

The GAO found evidence that fixed overhead costs had 

a significant impact on agencies’ performance under 

the PPS (GAO 2004). Home health agencies’ overhead

includes legal, accounting, and data processing services;

taxes; malpractice insurance; and office and equipment

rental. Agencies with poor financial performance spent

more than twice as much as well-performing agencies on

overhead, and poorly-performing agencies had 25 percent

fewer visits. GAO concluded that agencies’ small size

caused some of the difference in overhead costs per visit;

however, additional factors appeared to be at work

because nearly 20 percent of well-performing agencies

were also small in size. 

126 Payment for p ost-acute care
Small agencies could also have more difficulty with a PPS

because it pays on the basis of averages. The greater the

number of cases an agency has in a given case-mix group,

the more likely the agency’s average cost for that case-mix

group will equal the national standard upon which the

payment for the case-mix group is based. If a small agency

has only one or two cases in a given case-mix group, then

the agency’s average costs for that group will likely be

higher or lower than the national standard. If agencies do

not have enough patients with lower-than-average costs in

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 127

Clinical, functional, and service information from OASIS

determines patients’ home health case-mix classification

FIGURE

5-5

Note: OASIS (Outcome and Assessment Information Set), IV (intravenous), IRF (inpatient rehabilitation facility), SNF (skilled nursing facility).

Source: CMS 2000c.

Add the scores from each of these factors:

Primary home care diagnosis

IV/infusion or 

 parenteral/enteral therapy

Vision limitation

Pain

Wound/lesion

Multiple pressure ulcers

Most problematic 

 pressure ulcer stage

Add the scores from each of these factors:

Stasis ulcer status

Surgical wound status

Shortness of breath

Urinary incontinence

Bowel incontinence

Bowel ostomy

Behavioral problems

Clinical

Dressing

Bathing

Add the scores from each of these factors:

Toileting

Transferring

Locomotion

Functional

No hospital discharge

 past 14 days

IRF/SNF discharge

 past 14 days

10 or more therapy visits

Service utilization

Min.

Low

Mod.

High

Min.

Low

Mod.

High

Max

Min.

Low

Mod.

High

Case-mix

classification

(80 groups)

Clinical score

Functional score

Service utilization score
some case-mix groups to offset the patients with higherthan-average costs in others, then they could be underpaid.

Researchers noted the potential for difficulties for small

agencies (Phillips et al. 1992). When testing several casemix models for the PPS, the developers found that small

agencies (ones with 200 or fewer episodes in a year) 

under a PPS would be somewhat more likely than 

medium agencies to be under- or overpaid in a given 

year by at least 5 percent. Furthermore, small agencies

would be more than twice as likely to be under- or 

over-paid than large agencies (ones with more than 

925 episodes). 

Another PPS pathology is the failure to account for large

variations of costs within case-mix groups. In the March

2005 report, MedPAC noted the wide variation in the

number of minutes that nurses, therapists, aides, or social

workers spent with patients during an episode in the same

case-mix groups. We measured the average number of

minutes of service per episode for each case-mix group, 

as well as the amount of variation around each of those

averages. In more than half of the 80 case-mix groups in

this system, the coefficient of variation for minutes per

episode was greater than 1. A coefficient of variation of 

1 or greater implies that the standard deviation is equal to

or greater than the average, indicating very wide variation.

Although the congruence between costs and minutes of

service may not be one-for-one, the weak relationship

between minutes and case mix suggests that the home

health PPS case-mix system may fail to fully account for

variation in costs within payment groups. 

The handful of HHRGs with very small numbers of

patients may compound the problem. As noted earlier, the

80 HHRGs represent every combination of each level of

clinical and functional severity and service use; the

HHRGs for maximum clinical severity and minimum

functional limitation are populated only by a few patients

each year (one such HHRG had only 45 patients

nationwide in 2001; another had only 100 patients). Such

small numbers of patients contribute to inconsistency in

the average service use and cost of care for the HHRG.

Perhaps CMS should consider merging these small

HHRGs into larger, similar HHRGs. 

The home health PPS pays the same amount for high- and

low-quality care, as do all of Medicare’s payment systems.

MedPAC recommended in March 2005 that CMS should

align the incentives of payment systems with incentives

for quality (MedPAC 2005). We found that the home

health setting was ready for pay for performance and 

that a portion of the payments should be linked to

achieving a high level of patient outcomes or improving

the proportion of patients who achieve good outcomes.

Pay for performance is especially important in the home

health setting because the product definition is not strong;

under pay for performance, some dollars are linked

directly to what Medicare truly wants to buy: better 

health for beneficiaries.

Home health product has changed since CMS

designed the case-mix system

Substantial changes in the home health care product that

have occurred since the system was designed could limit

the system’s ability to account for current differences

among agencies and for differences among case-mix

groups. Abt Associates designed the case-mix system

under contract with CMS in 1999 (Goldberg et al.) using

claims from October 1997 through April 1998. At that

time, the payment system was cost based; agencies 

could generate more revenue by providing more visits.

HHAs had an incentive to deliver more visits and 

were responding to that incentive in 1996 and 1997,

admitting more beneficiaries and providing more visits

than ever before. 

Since the contractors developed the case-mix system, 

the PPS has substantially changed agencies’ incentives.

First, the prospective payment limits an agency’s ability 

to increase revenue by increasing visits because payment

is mostly determined by patients’ conditions rather than

the amount of service delivered. The case-mix system has

reversed the incentive for more visits. Second, the portion

of the PPS payment that is not based strictly on patients’

conditions is the additional payment for delivering at 

least 10 therapy visits. Meeting the therapy threshold

produces substantially higher payments for otherwise

similar patients. For example, an episode for a patient 

with moderate clinical severity and moderate functional

limitation would be paid $2,440 (base payment ✕ case

weight 1.08) if the episode did not meet the therapy

threshold and $4,420 (base payment ✕ case weight 1.95) 

if the patient did meet the therapy threshold. In this

example, the difference between the two patients could 

be minimal; they may have the same diagnosis and the

same level of functional limitation, but one patient may

have received 9 therapy visits and the other may have

received 10. This may be a strong incentive to shift the

mix of visits toward therapy to meet the 10-visit threshold

for higher payment.

128 Payment for p ost-acute care
Agencies have decreased the number of visits per 

episode and increased the amount of therapy delivered as 

a proportion of those services, thus substantially changing

the product of home care from the one that Abt used to

calculate the case-mix weights. These changes are fairly

substantial: Visits declined 47 percent, minutes declined

37 percent, and therapy increased as a proportion of all

visits by 17 percentage points (Table 5-9). The relative

resource needs calculated for each HHRG in 1999 are

probably not correct today because it seems unlikely 

that these substantial changes to the home health product

occurred evenly in each HHRG. Some HHRGs probably

changed more than others, which could affect their

resource intensity relative to those HHRGs that were 

less affected.

These changes in the product have led many to wonder

whether quality of care has declined as a result. Older

studies found small but significant benefits from higher

numbers of visits; newer results seem to challenge that

conclusion. The text box on the next page discusses some

evidence on this point.

Plans for future research

The evidence we have cited in this chapter suggests

problems with the home health PPS. To accurately

identify the source of the problem, we need to conduct

more research. If the case-mix system is not working well,

we may be able to detect patterns in the costs and claims

data. MedPAC will pursue the following questions in

future research:

• How well do the relative weights match the minutes of

service in each HHRG?

• How well do the relative weights match the reported

costs of care in each HHRG? We will explore several

different models for cost.

• Does the case-mix adjustment work better for some

types of beneficiaries than others? Specifically, are

there subgroups of beneficiaries whose care needs are

not well anticipated by the current case-mix system?

We will explore groups of users who are post-hospital

and non-post-hospital, who are with and without an

informal caregiver, who are qualified for both

Medicare and Medicaid, who have multiple markers

of frailty, who have cognitive disabilities, or who are

young and have disabilities. 

CMS may wish to consider a recalibration of the weights

as the first step in improving the current PPS. CMS

recalibrates the weights of the inpatient acute-care 

hospital PPS on a regular basis to maintain their accuracy.

Alternatively, more substantial changes to the system

could be considered, such as mixing prospective payment

with retrospective payment or limiting agencies’ profits

and losses or paying differently for different types 

of care. 

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 129

The home health product changed

between 1997 and 2002

1997 2002

Average visits per episode 36 19

Average minutes per episode 1,500 940

Percentage of therapy visits 9% 26 %

Source: Goldberg, H. B., D. Delargy, R. J. Schmitz, et al. 1999; MedPAC 

analysis of 20 percent of CMS Datalink file; and MedPAC analysis of 

5 percent Standard Analytic File of home health claims.

TABLE

5-9
130 Payment for p ost-acute care

Is more home health service better?

Early research suggested small but significant

differences between the quality of outcomes for

patients who received more home health care

and patients who received less. However, more recent

studies appear to challenge that conclusion. Research 

by Baker, Gill, and others links inactivity and decline 

in older adults; perhaps too much care, especially aide

care, for homebound patients may promote inactivity on

the part of the patient and thereby worsen the patient’s

condition (Gill et al. 2002). 

Schlenker, Shaughnessy, and Hittle (1995) found feefor-service beneficiaries received more visits, had

higher costs, and achieved better functional outcomes

than beneficiaries in managed care plans. This would

suggest that more home health care is better for 

patient outcomes.

More recent evidence is mixed. Hadley and colleagues

(2000) used an instrumental variable approach to

estimate a very small but statistically significant

difference between the functional outcomes of home

health users and nonusers in the six months following

hospitalizations. After controlling for the differences

between users and nonusers, they found that home health

users improved their functional status by 219 points on a

5,363-point scale, compared to nonusers (all patients had

an average score of 875 points). The authors note that

more research is needed about home health care that

does not follow a hospitalization and home health care

that is long term; it may not be appropriate to generalize

the results to those populations.

In their study of eight states, 44 HHAs, and more than

700 episodes, Brega and colleagues (2002) conclude:

“Patients receiving more frequent visits experienced

marginally better outcomes of home care than did

patients with less frequent visits.” Their outcomes

included 27 measures of improvement in activities of

daily living. 

An examination of the relationship between the amount

of home health service and patient satisfaction found

that decreasing amounts of home health service did not

decrease beneficiaries’ satisfaction with the agency,

their discharge, or nursing or therapist care (McCall et

al. 2004). The researchers did find a decrease in

satisfaction with fewer personal care services, though

they note that “there was concern [before the decrease

in services] that the benefit was increasingly being used

to provide personal care services for beneficiaries

having no skilled care need.” 

Since the implementation of the PPS and the attendant

decline in the average number of visits, patient outcomes

of care have shown a slight improvement, as measured

by CMS’s Home Health Compare (MedPAC 2005).

More home health patients have improved their ability 

to dress themselves, walk, and conduct other activities 

of daily living even though they are receiving a lower

number of visits than they did in the past. Also, Hogan

(2004) found that from 1996 to 2002, “there was a

statistically significant decline in re-admission and an

increase in percent of episodes ending in return to the

community.” The Hogan study made some adjustments

to account for changes in the patient population; the

Home Health Compare data do not. The latter study 

also found that potentially avoidable hospitalizations 

as a fraction of all readmissions also declined, further

suggesting that quality of care did not decline as the

number of visits per episode fell. Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 131

1 A small number of patients (about 17,000 out of 426,000)

included in the study sample had bilateral (both knees or

both hips) replacements.

2 Fourteen percent of IRF patients are discharged at 14+ days;

31 percent of SNF patients have a 14-day assessment.

3 RAND standardized the rates for IRFs and SNFs to remove

the effect of differences in area wages.

4 The MDS estimate was made by CMS (2002). One study

found that the MDS for Post-Acute Care, a tool that is

similar to the MDS, took an average of 85 minutes to

complete once 10 or more assessments had been done

(Buchanan et al. 2003). The OASIS estimate was made by

the National Association for Home Care (St. Pierre 2005).

The IRF–PAI estimate was done by researchers at Harvard

University (Buchanan et al. 2003). 

5 To qualify for the extensive services category, patients must

have, in the past 14 days, received IV medications, received

tracheostomy care, required a ventilator/respirator, required

suctioning, or must have received IV feeding in the past 7

days. In addition, the patients assigned to this category must

have a minimum ADL score of 7.

6 The study conducted by Fries and colleagues used staff 

time data from CMS Staff Time Measurement studies as a

measure of staff time costs (Fries et al. 2000). Studies that

attempt to measure the variance in costs explained by the

RUG–III case-mix system must define the dependent

variable (cost) using available, but limited, administrative

data. Specifically, facility-level nursing and other cost data

are not directly available from the Medicare cost reports, 

and data are not available for determining costs at the

individual beneficiary level. 

Endnotes
132 Payment for p ost-acute care

Beeuwkes Buntin, M., N. Sood, P. Deb, et al. 2005. Comparison

of Medicare spending and outcomes for beneficiaries with lower

extremity joint replacements. Working paper, RAND

Corporation, Arlington, VA.

Brega, A. G., R. E. Schlenker, K. Hijjazzi, et al. 2002. Study of

Medicare home health practice variations: Final report. Office 

of Disability, Aging, and Long-Term Care Policy, Office of the

Assistant Secretary for Planning and Evaluation, Department of

Health and Human Services. August. 

Buchanan, J., P. L. Andres, S. M. Haley, et al. 2003. An

assessment tool translation study. Health Care Financing 

Review 24, no. 23: 45–60.

Centers for Medicare & Medicaid Services, Department of Health

and Human Services. 2002. Medicare streamlines paperwork

requirements for nursing homes to allow nurses, other caregivers

to spend more time with patients. http://www.cms.hhs.gov/

media/press/release.asp?Counter=462.

Centers for Medicare & Medicaid Services, Department of Health

and Human Services. 2000a. Medicare program; prospective

payment system and consolidated billing for skilled nursing

facilities. Update, proposed rule. Federal Register 65, no. 69

(April): 19188–19236.

Centers for Medicare & Medicaid Services, Department of Health

and Human Services. 2000b. Medicare program; prospective

payment system and consolidated billing for skilled nursing

facilities. Update, final rule. Federal Register 65, no. 147 (July):

46769–46496.

Centers for Medicare & Medicaid Services, Department of Health

and Human Services. 2000c. Medicare program; prospective

payment system for home health agencies. Final rule. Federal

Register 65, no. 128 (July): 41194.

Clauser, S. B., and A. S. Bierman. 2003. Significance of

functional status data for payment and quality. Health Care

Financing Review 24, no. 23: 1–12.

Cotterill, P. G. 1986. Testing a diagnosis-related group index for

skilled nursing facilities. Health Care Financing Review 7, 

no. 4: 75–85. 

Deutsch, A., C. V. Granger, R. C. Fiedler, et al. 2005. Outcomes

and reimbursement of inpatient rehabilitation facilities and

subacute rehabilitation programs for Medicare beneficiaries with

hip fracture. Medical Care 43 (forthcoming).

Fries, B. E., K. Lapane, T. Moore, et al. 2000. Variation in

prescribed medication and other non-therapy ancillary costs 

in skilled nursing facilities: Potential RUG–III refinements.

Cambridge, MA: Abt Associates.

Gage, B. 1999. Impact of the BBA on post-acute utilization.

Health Care Financing Review 20, no. 4 (Summer): 103–126.

Gill, T. M., D. I. Baker, M. Gottschalk, et al. 2002. A program to

prevent functional decline in physically frail, elderly persons who

live at home. New England Journal of Medicine 347, no. 14

(October): 1068–1074.

Goldberg, H. B., D. Delargy, R. J. Schmitz, et al. 1999. Case-mix

adjustment for a national home health prospective payment

system: Second interim report. Cambridge, MA: Abt Associates.

Government Accountability Office. 2005. Medicare: More

specific criteria needed to classify inpatient rehabilitation

facilities. GAO–05–366. Washington, DC: GAO.

Government Accountability Office. 2004. Medicare home health

care: Payments to most freestanding home health agencies more

than covered their costs. GAO–04–359. Washington, DC: GAO.

Government Accountability Office. 2002. Skilled nursing

facilities: Providers have responded to Medicare payment system

by changing practices. GAO–02–841. Washington, DC: GAO.

Government Accountability Office. 2001. Skilled nursing

facilities: Services excluded from Medicare’s daily rate need to be

reevaluated. GAO–01–816. Washington, DC: GAO.

Government Accountability Office. 2001. Medicare home health

care: OASIS data use, cost, and privacy implications.

GAO–01–205. Washington, DC: GAO. 

Government Accountability Office. 2000. Medicare home health

care: Prospective payment system will need refinement as data

become available. GAO/HEHS–00–9. Washington, DC: GAO.

Government Accountability Office. 1999. Skilled nursing

facilities: Medicare payments need to better account for

nontherapy ancillary cost variation. GAO/HEHS–99–185.

Washington, DC: GAO.

Hadley, J., D. Rabin, A. Epstein, et al. 2000. Posthospitalization

home health care use and changes in functional status in a

Medicare population. Medical Care 38, no. 5: 494–507.

Hogan, C. 2004. Medicare beneficiaries’ use of post-acute care

trends, 1996 to 2002. Draft working paper developed for

MedPAC contract, Direct Research, LLC, Vienna, VA.

References
Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 133

Iezzoni, L. I., ed. 2003. Risk adjustment for measuring health care

outcomes, 3rd ed. Chicago, IL: Health Administration Press.

Jette, A. M., S. M. Haley, and P. Ni. 2003. Comparison of

functional status tools used in post-acute care. Health Care

Financing Review 24, no. 3 (Spring): 13–24. 

Kane, R. L., Q. Chen, M. Finch, et al. 2000. The optimal

outcomes of post-hospital care under Medicare. Health Services

Research 35, no. 3 (August): 615–661.

Keith, R. A., D. B. Wilson, and P. Gutierrez. 1995. Acute and

subacute rehabilitation for stroke: A comparison. Archives of

Physical Medicine and Rehabilitation 76, no. 6 (June): 495–500.

Kramer, A. M., J. C. Kowalsky, M. Lin, et al. 2000. Outcome and

utilization differences for older persons with stroke in HMO and

fee-for-service systems. Journal of American Geriatrics Society

48, no. 7 (July): 726–734. 

Kramer, A. M., T. B. Eilertsen, M. K. Ecord, et al. 1999. A

prospective study of new case-mix indices for subacute care.

Final report to National Subacute Care Association and the

American Health Care Association. Denver, CO: Morrison

Informatics and University of Colorado Health Sciences 

Center. June.

Kramer, A. M., J. F. Steiner, R. E. Schlenker, et al. 1997.

Outcomes and costs after hip fracture and stroke: A comparison

of rehabilitation settings. Journal of the American Medical

Association 277, no. 5 (February 5): 396–404.

Mahoney, F. I., and D. W. Barthel. 1965. Functional evaluation:

The Barthel Index. Maryland State Medical Journal 14

(February): 61–65.

Manton, K. G., E. Stallard, and M. A. Woodbury. 1994. Home

health and skilled nursing facility use: 1982–1990. Health Care

Financing Review 16, no. 1 (Fall): 155–186.

McCall N., J. Korb, A. Petersons, et al. 2004. Decreased home

health use: Does it decrease satisfaction? Medical Care Research

and Review 61, no. 1 (March): 64–88.

Medicare Payment Advisory Commission. 2005. Report to the

Congress: Medicare payment policy. Washington, DC: MedPAC.

Medicare Payment Advisory Commission. 2004. Report to the

Congress: New approaches in Medicare. Washington, DC:

MedPAC.

Medicare Payment Advisory Commission. 2003. Comment letter

to Centers for Medicare & Medicaid Services on Minimum Data

Set, version 3.0. May 30. http://www.medpac.gov/publications/

other_reports/053003_mds_letter.pdf.

Medicare Payment Advisory Commission. 2002. Report to the

Congress: Medicare payment policy. Washington, DC: MedPAC. 

Medicare Payment Advisory Commission. 2001. Report to the

Congress: Medicare payment policy. Washington, DC: MedPAC.

Munin, M. C., K. Seligman, M. A. Dew, et al. 2005. Effect of

rehabilitation site on functional recovery after hip fracture.

Archives of Physical Medicine and Rehabilitation 86, no. 3

(March): 367–372. 

Newhouse, J. P. 2002. Pricing the priceless: A health care

conundrum. The Walrus-Pareto Lectures at the École des Hautes

Études Commerciales, Université de Lausanne. London: The

MIT Press.

Office of Disability, Aging and Long-Term Care Policy, Assistant

Secretary for Planning and Evaluation, Department of Health and

Human Services. 2003. Toward a national health infrastructure:

A key strategy for improving quality in long-term care.

Washington, DC: HHS.

Office of the Inspector General, Department of Health and

Human Services. 2003. Trends in the assignment of resource

utilization groups. OEI–01–03–00180. Washington, DC: OIG.

Phillips, B. R., R. S. Brown, J. L. Schore, et al. 1992. Case-mix

analysis using demonstration data: Home health prospective

payment demonstration. Princeton, NJ: Mathematica Policy

Research, Inc. 

St. Pierre, M., National Association for Home Care. 2005.

Personal communication with author.

Schlenker, R. E., P. W. Shaughnessy, and D. F. Hittle. 1995.

Patient-level cost of home health care under capitated and FFS

payment. Inquiry 32, no. 3: 252–270. 

Schore, J. 1994. Patient, agency, and area characteristics

associated with regional variation in the use of Medicare home

health services. Princeton, NJ: Mathematica Policy Research, Inc.

White, C. 2003. Rehabilitation therapy in skilled nursing

facilities: Effects of Medicare’s new prospective payment system.

Health Affairs 22, no. 3 (May/June): 214–223. 

White, C., S. D. Pizer, and A. J. White. 2002. Assessing the

RUG–III resident classification system for skilled nursing

facilities. Health Care Financing Review 24, no. 1: 7–15.

Wodchis, W. P. 2004. Physical rehabilitation following Medicare

prospective payment for skilled nursing facilties. Health Services

Research 39, no. 5: 1299–1318.

Payment for pharmacy 

handling costs in hospital 

outpatient departments

CHAPTER 6
RECOMMENDATIONS

6A The Secretary should establish separate, budget-neutral payments to cover the costs that

hospitals incur for handling separately paid drugs, biologicals, and radiopharmaceuticals.

COMMISSIONER VOTES: YES 16 • NO 0 • NOT VOTING 0 • ABSENT 1

 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

6B The Secretary should:

• define a set of handling fee APCs that group drugs, biologicals, and 

radiopharmaceuticals based on attributes of the products that affect handling costs;

• instruct hospitals to submit charges for those APCs; and

• base payment rates for the handling fee APCs on submitted charges, reduced to costs.

COMMISSIONER VOTES: YES 16 • NO 0 • NOT VOTING 0 • ABSENT 1
Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 137

he Medicare Prescription Drug, Improvement, and

Modernization Act (MMA) of 2003 mandates that

MedPAC report on whether the Secretary should adjust

payments in the outpatient prospective payment system

(PPS) for pharmacy and nuclear medicine handling costs. The issue

arises because Medicare will begin to pay for certain drugs, biologicals,

and radiopharmaceuticals based on acquisition costs in 2006. Previously,

the payment rates for these items were higher, providing hospitals with

resources to cover handling costs. The Commission concludes that 

handling costs are nontrivial and an adjustment is warranted. However, any adjustment should be budget neutral 

because when CMS established the outpatient PPS, payments were based on hospital charges that reflected these

handling costs. This chapter closes with a discussion of the significant unbundling that has occurred within 

the outpatient PPS. The current granular approach to paying for drugs undermines incentives for efficient use 

of services in broader payment bundles. The Commission suggests that, in the future, CMS identify larger 

payment bundles.

6

In this chapter

• Is a payment adjustment 

needed?

• How should a payment 

adjustment be structured?

• How should handling 

costs be measured?

• What are the options for 

collecting data?

• A longer term agenda: 

Broader payment bundles 

in the outpatient PPS

CHAPTER

T

Payment for pharmacy

handling costs in hospital

outpatient departments
138 Payment for p harmacy handling costs in hos p ital out p atient de p artments

The Medicare Prescription Drug, Improvement, and

Modernization Act (MMA) of 2003 changed the way in

which Medicare will pay hospitals for certain drugs,

biologicals, and radiopharmaceuticals delivered in their

outpatient departments and covered under the outpatient

prospective payment system (PPS). The law affects

radiopharmaceuticals and products that Medicare

reimbursed under the outpatient PPS’s pass-through

mechanism as of December 2002 (called specified covered

outpatient drugs). The pass-through mechanism enables

additional payment for those technologies for a period of

two to three years, after which CMS incorporates them

into the payment system. 

Providers use many, but not all, of the drugs and

biologicals on the pass-through list in cancer treatment.

Other pass-through drugs and biologicals treat rheumatoid

arthritis, diseases of immune deficiency, and additional

conditions. Table 6-1 lists the drugs and biologicals

receiving the highest total payments under the outpatient

PPS in 2002; Table 6-2 lists the top radiopharmaceuticals.

In general, hospital pharmacies handle drugs and

biologicals. Radiopharmaceuticals are radioactive agents

used for diagnostic or therapeutic purposes. Many

providers use radiopharmaceuticals in nuclear imaging

procedures; others target drugs and radioisotopes in 

certain cancer treatments. Radiopharmaceuticals may be

handled by hospital pharmacies, radiopharmacies or, 

more typically, nuclear medicine departments. 

When these drugs, biologicals, and radiopharmaceuticals

(hereafter referred to as “products”) were on the passthrough list, CMS paid hospitals 95 percent of average

wholesale price (AWP), a benchmark price that

researchers and auditors have found to be well above

acquisition cost (MedPAC 2003, GAO 2001, OIG 2001).

After CMS moved these products off the pass-through list,

the agency set payment rates using the general approach of

the outpatient PPS: calculating the median value of

hospital charges reduced to costs using adjustment factors

from hospital cost report data. Manufacturers believe that

these payment rates are too low (PhRMA 2002).1

In the MMA, the Congress directed CMS to pay hospitals

for specified covered outpatient drugs in different ways

than before. Beginning in 2006, the MMA mandates 

that CMS set payment equal to average acquisition cost, 

taking into account data collected by the Government

Accountability Office (GAO) through a survey of

hospitals. GAO surveyed hospitals from fall 2004 to

spring 2005. It provided CMS with data on acquisition

costs in spring 2005.

The MMA also required MedPAC to determine whether

the outpatient PPS should have a payment adjustment to

cover services provided by hospital pharmacies or nuclear

medicine departments when they handle these products.

The law directed MedPAC to suggest a method for

making such an adjustment, if needed. (Relevant excerpts

from the MMA language requesting the study can be

found at the end of this chapter, p. 152.)

MedPAC’s study focuses on the handling costs that

pharmacy and nuclear medicine departments incur for

storing, preparing, transporting, and disposing of the

products. The study excludes the acquisition costs of the

products themselves, which GAO is studying. The study

Study drugs and biologicals with

highest payments in 2002, 

ranked highest to lowest 

APC in

2002 APC title in 2002 Brand name(s)

0733 Non-ESRD epoetin alpha injection Epogen, Procrit

0849 Rituximab Rituxan

7043 Infliximab injection Remicade

0863 Paclitaxel injection Taxol

0811 Carboplatin injection Paraplatin

0823 Docetaxel Taxotere

0828 Gemcitabine HCL Gemzar

0830 Irinotecan injection Camptosar

9115 Zoledronic acid injection Zometa

9217 Leuprolide acetate suspension Lupron, Eligard

0730 Pamidronate disodium Aredia

0728 Filgrastim injection Neupogen

7049 Filgrastim injection Neupogen

1613 Trastuzumab Herceptin

0768 Ondansetron HCL injection Zofran

7046 Doxorubicin HCL liposome injection Doxil

9005 Reteplase injection Retavase

9119 Pegfilgrastim injection Neulasta

0852 Topotecan Hycamtin

0810 Goserelin acetate implant Zoladex

1203 Verteporfin for injection Visudyne

7031 Octreotide acetate injection Sandostatin

0855 Vinorelbine tartrate Navelbine

9002 Tenecteplase TNKase

0905 Immune globulin *

Note: APC (ambulatory payment classification), ESRD (end-stage renal disease), 

HCL (hydrochloride). 

* Various manufacturers.

Source: MedPAC analysis of 2002 outpatient claims file from CMS.

TABLE

6-1
also excludes costs associated with administering the

product to the patient—such as preparing the patient for

chemotherapy, monitoring the patient during an infusion,

or treating side effects—because Medicare pays separately

for administration of chemotherapy and other drugs, as

well as for nuclear medicine procedures. MedPAC’s

analysis considers broader issues that this study raises,

namely the design of payment rates.

In considering the question of pharmacy handling costs in

hospitals, a review of the literature revealed little relevant

research or data. MedPAC consulted widely with

stakeholders, including numerous hospital pharmacy

directors and administrators, representatives of hospital

associations (including cancer hospitals), pharmaceutical

distributors, representatives of product manufacturers, and

CMS staff. We also coordinated our work with that of

GAO. To better understand how hospital pharmacies

operate, MedPAC staff conducted a site visit to a cancer

center in the Washington, DC, area. We then developed a

conceptual framework with assistance from a contractor, a

technical advisory panel, and four facilities that agreed to

serve as case studies. 

Is a payment adjustment needed?

MedPAC’s analysis indicates that handling costs for these

products are not insignificant. CMS built the existing

outpatient PPS payment pool using hospital charges that

reflected handling costs. Consequently, the Commission

concludes that CMS should make a payment adjustment,

but it should be budget neutral. In other words, total

payments for all services would remain the same, and 

the resources for an adjustment would come from a

redistribution of payments from other categories of

services. 

Background

Determining whether the outpatient PPS needs a payment

adjustment requires an understanding of previous payment

policies. Historically, hospitals generally charged only for

the drug provided; they did not routinely develop separate

charges for their pharmacy services. In a recent survey of

hospital charging practices, most respondents indicated

that this practice continues today (Worzala and Ashby

2004). In our discussions with hospitals, officials indicated

that they set charges for drugs and radiopharmaceuticals

high enough to reflect the products’ handling costs as well

as their acquisition costs. Historically, Medicare payments

were sufficient to cover both.

Under the outpatient PPS, CMS generally sets payments

based on hospitals’ charges, which the agency reduces 

to estimated costs using a cost-to-charge ratio from

Medicare cost report data. Using this methodology, CMS

incorporates handling costs into the payment rates because

handling costs are built into hospitals’ charges. Many

observers have voiced concerns about the completeness 

of the data available to CMS and the accuracy of this

methodology when setting rates for specific items (see

more detailed discussion in the section about broader

payment bundles on p. 150). Nevertheless, CMS included

handling costs as a component of hospital-wide expenses

when it set up the outpatient PPS. Thus, the current

payment system incorporates handling costs in the total

payment pool.

The MMA requires GAO to collect acquisition cost data

that CMS then will use to set payment rates for these

products in 2006. If the acquisition cost data are not

available, the MMA allows CMS to use the drug price

data collected in order to pay physicians for Part B

drugs—that is, average sales price or prices from

competitive acquisition arrangements. Under either 

of these approaches, the payment for the product would 

no longer include handling costs. 

Our conversations with stakeholders and analysis of data

from Maryland hospitals and from Medicare cost reports

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 139

Study radiopharmaceuticals with 

highest payments in 2002, 

ranked highest to lowest 

APC in 2002 APC title in 2002

1600 Technetium-99m sestamibi

0705 Technetium-99m tetrofosmin

1603 Thallium-201

1775 FDG

1601 Technetium-99m medronate

1622 Technetium Tc-99m mertiatide

1604 In-111 capromab pendetide

1627 Technetium-99m labeled RBCs

1348 I-131 solution

1188 I-131 capsule

Note: APC (ambulatory payment classification), FDG (fluorodeoxyglucose F18), 

Tc (technetium), In (indium), RBCs (red blood cells).

Source: MedPAC analysis of 2002 outpatient claims file from CMS.

TABLE

6-2
suggest that handling costs are not negligible. However,

because most hospitals do not develop charges for

pharmacy handling costs today, they do not have precise

information about the magnitude of these expenses.2 The

fact that hospitals typically prepare inpatient and

outpatient drug and biological products within the same

pharmacy complicates the measurement of handling costs.

In interviews that MedPAC staff conducted for this

research, hospital pharmacy directors stated that the types

of medications that providers administer more frequently

in outpatient departments generally require more

pharmacy preparation time than do those for inpatients.

Although data are not available to make a comparison, the

pharmacy directors believed that inpatients generally

received more medications as pills, injections, or as simple

intravenous (IV) solutions, while outpatients generally had

a larger proportion of complex infusion therapies that

pharmacists needed to reconstitute or compound.

Radiopharmacists or pharmacy technicians usually prepare

radiopharmaceuticals in a separate nuclear medicine

department, or commercial nuclear pharmacies under

contract with the hospital deliver near-ready unit doses. 

One study of 1996 Medicare hospital cost report data

found that labor and costs other than the acquisition cost

of drugs accounted for about one-third of expenses

associated with pharmacy-related cost centers—where

hospitals state the costs of drugs and of operating the

pharmacy department (Kathpal Technologies 1999).

However, it is unclear whether available data are

comparable across hospitals. The Kathpal study relied on a

sample of 55 hospitals. MedPAC analyzed recent

Medicare cost report data for more than 3,300 hospitals

and found that hospitals are not consistent in their

reporting of pharmacy costs. This inconsistency makes it

difficult to separate drug acquisition costs from pharmacy

handling costs. MedPAC found that in nearly 1,200

hospitals in which reporting appears to be comparable,

wages, salaries, and fringe benefits make up 25 percent, on

average, of pharmacy-related direct costs. The cost of

purchasing pharmacy supplies and acquiring drugs and

biologicals account for the remaining 75 percent of direct

costs. Radiopharmaceutical handling costs are typically an

expense of running a nuclear medicine department, and we

were unable to estimate the relative magnitude of these

costs from Medicare cost report data.

MedPAC also analyzed cost data for about 40 hospital

pharmacy departments in Maryland from 2001 to

2003—nearly all the hospitals in that state (see text box).3

Those data show that pharmacy department wages and

salaries, fringe benefits, and supplies made up 26 percent

to 28 percent of pharmacy departments’ direct costs

(defined as the cost of labor, benefits, and supplies plus

the acquisition cost of drugs).

Moving to a payment system based on acquisition cost for

separately paid drugs means that the system will no longer

compensate hospitals for handling costs as part of the

payment for the drug itself.4 Yet handling costs are not

negligible. In addition, some hospitals provide more of

these services than others (for example, hospitals that

specialize in cancer care, or teaching hospitals that provide

more new technology services). Therefore, the move to

reimburse for these products based on acquisition cost

could have redistributive effects among facilities. For the

reasons mentioned above, the payment system should

include an adjustment for handling products when

Medicare pays for the products at acquisition cost. 

A budget-neutral payment adjustment

A payment adjustment for handling costs should be budget

neutral because when CMS established the outpatient PPS,

it based payments on hospital charges that reflected these

handling costs. A payment adjustment would ensure that

Medicare reimburses hospitals for the costs of these

services more directly than before, but payments should

come from the redistribution of resources already within

the outpatient PPS payment base.

Prospective payment systems comprise three basic parts: 

• a classification system to define the services for which

Medicare is paying (called ambulatory payment

classification [APC] groups in the outpatient PPS);

• relative weights to determine the relative payments

among services; and

• a conversion factor Medicare uses to set the level of

payments. 

Together with volume, these three factors determine the

size of the payment pool.

MedPAC’s study primarily focuses on the classification

system and the relative weights. A payment adjustment

may require creating new APCs, which would change the

classification system. Setting appropriate payment rates

for new APCs would require establishing relative weights. 

Current law generally requires that changes to the

classification system and relative weights be made in a

budget-neutral fashion. MedPAC’s study does not address

140 Payment for p harmacy handling costs in hos p ital out p atient de p artments
the level of payments—this task is done through the

annual updates to the conversion factor, which the

Congress determines based on guidance from MedPAC.5

In addition to the outpatient PPS’s structure, other factors

support a budget-neutral payment adjustment:

• Hospital officials and others told MedPAC staff that

hospitals build handling costs for drugs, biologicals,

and radiopharmaceuticals into the charges for the

products themselves as part of the markup over 

costs. Therefore, the original payment pool that CMS

based on hospital charges (reduced to costs) reflected

handling costs. In recent years, relative weights

derived from charges (reduced to costs) also reflect

handling costs.

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 141

Hospital pharmacy costs in Maryland

I

n order to measure handling costs for drugs and

radiopharmaceuticals delivered in hospital

outpatient departments, MedPAC analyzed data

from the Maryland Health Services Cost Review

Commission (HSCRC). Maryland regulates hospitals’

charges; all payers base their payments on those

charges. Maryland established the HSCRC in 1971 to

set the rates that hospitals charge for the all-payer

system. Due to the nature of its work, the HSCRC

possesses comprehensive hospital accounting data that

helped us understand the types of costs that hospitals

incur for outpatient pass-through drugs. MedPAC

analyzed HSCRC hospital pharmacy accounting data

from approximately 40 Maryland hospitals for 2001 to

2003. The data include the following types of hospital

pharmacy costs: acquisition cost of drugs, the pharmacy

department’s other direct costs, capital costs, payment

adjustments, and an allowance for profit. We call the

sum of these costs “total direct drug expenses.” 

MedPAC analyzed three components of direct drug

expenses: (a) drug acquisition costs, (b) pharmacy

wages, and (c) pharmacy supplies. In all three years, the

nondrug elements of direct costs made up 26 percent to

28 percent of the total (Figure 6-1).

As these data illustrate, nondrug costs make up a

nontrivial proportion of costs. Figure 6-1 also shows

that the average proportions did not change much from

year to year. Overall, these data demonstrate that the

handling costs hospital pharmacies incur are not

negligible; thus, Medicare payments should account for

these costs. 

Limitations of the data

Although these data can inform the relationship

between cost categories within the pharmacy, they do

not include information on the types or volume of drugs

prepared in the pharmacy—nor do they separate the

products delivered in outpatient departments from those

used by inpatient departments. Finally, these data

exclude radiopharmaceuticals. 

Labor and supplies components 

of direct pharmacy expenses 

are stable

FIGURE

6-1

Source: MedPAC analysis of hospital cost report data from the Maryland Health

 Services Cost Review Commission. Percent of direct ph

arm

acy costs

100

80

60

40

20

0

2001 2002 2003

Drug acquisition costs

Pharmacy wages, salaries, and fringe benefits 

Pharmacy supplies
• In setting up pass-through payments in the Balanced

Budget Refinement Act of 1999, the Congress

designed the policy to be budget neutral (MedPAC

2002).6

• Through the MMA, the Congress legislated interim

payment rates in 2004 and 2005 for the products in

this study based on AWPs. Because AWPs are

benchmark prices well above acquisition costs, that

policy provided additional resources within the system

to cover pharmacy handling expenses. By law,

increased payments resulting from the interim

payment rates were made with new money—that is,

the policy was not budget neutral.7 Medicare has

subsequently built this increased spending into the

total payment pool.

How should a payment adjustment 

be structured?

Hospitals appear to incur nontrivial costs in handling

separately paid drugs and radiopharmaceuticals. Thus, as

the outpatient PPS moves toward reimbursing hospitals for

drugs at their acquisition cost, it should also provide some

payment for handling costs.

To cover reasonable pharmacy and nuclear medicine

handling costs, a payment adjustment could take one of

several forms: 

• a percentage markup on acquisition costs, 

• a handling fee tied to each administration to a patient,

or 

• inclusion of handling costs in a larger payment

bundle.

Markup on acquisition costs

Medicare could link payment for handling costs to the

acquisition cost of products. Indeed, some stakeholders

interpret the Kathpal study’s findings (1999) as follows: 

A payment methodology to reimburse hospitals for

pharmacy department costs should provide, on average, 

a 50 percent markup over the acquisition cost of products

(ACCC 2004). Under that logic, if handling costs make 

up one-third of the sum of handling costs plus acquisition

costs, Medicare would need to pay 1.5 times the

acquisition cost to cover both costs.

This approach would be administratively straightforward,

provided that Medicare can collect reliable data on

acquisition costs. However, handling costs may not be

directly proportional to a product’s acquisition costs.

Prices that hospitals pay to purchase the products depend

on a number of factors, such as the availability of generic

or therapeutic substitutes, the volume that each hospital 

(or each hospital system) buys, and the abundance or

scarcity of the products. Some drug therapies with lower

acquisition costs have relatively high handling costs

because these therapies require that a pharmacist

reconstitute them over a lengthy period or prepare them

for infusion using specialized safety equipment. Other

products carry relatively high price tags because they are

single-source drugs, but some are manufactured in a form

that requires less pharmacy handling (for example,

prepackaged unit doses, or liquids rather than powders). 

Handling fee per administration

A second way to structure an outpatient PPS payment for

handling costs is to reimburse hospital pharmacies for

each preparation of a product that is administered to a

patient. Unlike providing a markup over the product’s

acquisition cost, a per administration handling fee could

provide a more direct link between Medicare’s payment

and the resources required to carry out pharmacy and

nuclear medicine departments’ tasks. This approach is

similar to the way in which Medicaid and private payers

reimburse retail pharmacies for the dispensing costs of

outpatient prescription drugs. 

MedPAC staff’s discussions with hospital pharmacy

directors and other stakeholders revealed wide variation in

the processes and resources required to handle drug

therapies in hospital outpatient departments. For example,

a hospital pharmacy may require the ability to dispense

not only simple pills but also highly toxic chemotherapy

agents for intravenous infusion. Some patients may

receive a single drug; others receive a combination therapy

that requires the pharmacies to mix products before

administering them. Therefore, CMS may want to classify

products into broad categories, with each group requiring

similar levels of pharmacy resources. The agency would

then set a fixed payment to cover the handling costs for

each category of drugs and radiopharmaceuticals.8

This classification approach is preferable to a markup over

acquisition cost because it links payment more closely to

actual resource use. On the other hand, it is more

administratively complex. However, these complexities do

142 Payment for p harmacy handling costs in hos p ital out p atient de p artments
not appear to be insurmountable and should diminish over

time. To institute this approach, CMS would have to

create categories of handling costs, establish Healthcare

Common Procedures Coding System (HCPCS) codes for

them, and set payment rates. Hospitals would have to bill

Medicare for their handling costs using the new HCPCS

codes. Once Medicare began receiving such charges, it

could set payment rates for handling costs in each

category in the same manner that it does for other APCs

within the outpatient PPS—by evaluating the median level

of costs among submitted charges (reduced to costs).

Hospitals would need advance notice of the new codes as

well as time to collect appropriate cost information,

develop the charges, and modify their billing operations. 

Can hospitals set charges for their handling services?

Although most hospitals do not currently charge for 

their handling costs, they set charges for many different

services and should be able to develop charges for

handling costs as they have done for other costs. In fact,

one hospital official with whom MedPAC spoke stated

that his facility had already developed charges for

pharmacy services. Other hospitals indicated that if

required, they could do so.9 Through four case studies

(described on p. 147), MedPAC assessed whether

hospitals could estimate their handling costs, which could

provide valuable information for setting charges. The

case-study facilities successfully estimated costs, although

they found the process time consuming. Hospitals may

need a transition period before CMS deems that the charge

data submitted are reliable enough to set payment rates.

CMS also would need to develop a process for evaluating

the handling costs of new products and categorizing them

within appropriate APCs.

Other payers also often reimburse hospitals for handling

costs through payment for the product itself. If Medicare

reimbursed handling costs through separate APCs, that

approach could conflict with hospitals’ method of

obtaining payment from other payers. However, it seems

likely that once Medicare begins paying for these products

based on acquisition costs, other payers would want to

follow suit. Under that scenario, developing standard

charges would help hospitals ensure more direct payment

for handling costs from all payers.

Larger payment bundles

Alternatively, CMS could create larger bundles of services

within the outpatient PPS that include pharmacy and

nuclear medicine handling costs. In order to ensure that

Medicare reimburses hospitals for handling costs,

hospitals would still need to develop charges for pharmacy

services. CMS would reimburse hospitals for bundles that

include not only the acquisition cost of clinically similar

products but also their handling costs. This approach is

consistent with the original intent behind the outpatient

PPS—to provide a predetermined level of payment for

clinically similar services (APCs), thereby giving hospitals

an incentive to control costs (MedPAC 2000). 

Over time, CMS has expanded the number of APCs,

narrowing certain bundles of services, to the point of

providing separate payment for many individual products.

The Congress required CMS to set up separate payments

for the products covered in MedPAC’s study because

these products are newer technologies that generally have

higher costs than other therapies. Proponents were

concerned that if these products were bundled within

broader APCs that also included less costly therapies,

reimbursement would be too low for hospitals that chose

to provide newer products. Broad bundles, proponents

believe, could adversely affect patient care if newer

therapies represent significant advances in treatment that

are disadvantaged by the design of APCs.

Yet arguably, in cases where older and newer agents are

therapeutically equivalent, it is appropriate for CMS to

include both older and newer agents within the same APC.

This approach would give hospitals a greater incentive to

decide whether the clinical outcomes of newer therapies

justify their higher acquisition costs. Moreover, not all

new products constitute significant advances in therapy.

How should handling costs be

measured?

Measuring handling costs is primarily a cost accounting

exercise. However, after a literature review and

conversations with stakeholders, MedPAC concluded 

that no systematic, consensus-based approach exists for

identifying or measuring handling costs for these products.

To break down the process of measuring handling costs,

we took three steps:

• Developed a framework to identify and define the

handling costs.

• Classified the study products into categories according

to characteristics related to the level of resources used

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 143
in handling, including radioactivity, toxicity, mode of

administration, and special-handling considerations. 

• Conducted case studies in four facilities to test the

validity of the framework and classification system, 

as well as to assess hospitals’ ability to estimate the

relative handling costs across categories by resource

use.

Framework

In order to measure handling costs, one must first define

them. With the help of a contractor, MedPAC developed 

a framework that lays out the categories of costs (Figure 

6-2). The framework and definitions are sufficiently 

broad to span the range of products covered by this study

and to apply to both pharmacy and nuclear medicine

departments. MedPAC asked a technical advisory panel of

experts in pharmacy, nuclear medicine, hospital finance,

and cost accounting to evaluate the framework. We then

modified the groupings based on the panel’s input. (A list

of the members of the advisory group is available from

MedPAC upon request.) The dimensions of handling 

costs that MedPAC considered include:

• pharmacy or nuclear medicine management, including

regulatory compliance;

• storage, including inventory management;

• preparation, including review of drug orders and

dosage calculations;

• transport within the hospital (such as from the

pharmacy to the infusion suite); and

• disposal of products from the pharmacy or nuclear

medicine department.

Costs for specific products will vary across these

categories. Some products may have significant storage

requirements (such as extremely low temperatures to

maintain product integrity or shielded containers to protect

workers from contamination); others may have extensive

preparation costs (such as lengthy reconstitution times or

complex dosage calculations and verifications). In some

cases, management of inventory for high-cost products can

be a significant expense. In concept, all handling costs

should fit into at least one of the categories. Within each

category, the kinds of costs to measure include:

• labor and benefits,

• space,

• equipment and supplies, and 

• support contracts for other organizations to provide

certain services (such as waste disposal contracts).

144 Payment for p harmacy handling costs in hos p ital out p atient de p artments

Pharmacy and nuclear medicine management

Activities required for departmental management such as record keeping, personnel, and training. 

Also includes the department-level costs of regulatory compliance, safety, and quality assurance.

Storage

Maintaining drug or 

radiopharmaceutical 

and its components in 

appropriate conditions, 

including inventory 

management.

Preparation

Reviewing orders; 

checking dosages; 

mixing, compounding, 

or reconstituting drug or 

radiopharmaceutical for 

administration to patient.

Transport

Delivering drug or 

radiopharmaceutical 

to location at which it 

will be administered 

to patient.

Disposal

Disposing of drug or 

radiopharmaceutical 

waste and supplies 

within pharmacy or 

nuclear medicine 

department.

Labor and benefits • Space • Equipment • Supplies • Support contracts

Pharmacy and nuclear medicine functions and handling costs covered by this study 

FIGURE

6-2
Activities such as regulatory compliance and quality

improvement can affect the costs in these categories. For

example, studies have shown that individuals preparing

toxic agents can be exposed to these agents through their

skin or through breathing aerosolized particles (Morris

2005). Consequently, the National Institute for

Occupational Safety and Health (NIOSH) has issued

guidelines to protect workers who come in contact with

antineoplastics and other drugs (NIOSH 2004). The Joint

Commission on Accreditation of Healthcare Organizations

(JCAHO) assesses hospitals’ compliance with quality and

safety standards that include guidelines for preparing

products in hospital pharmacies. Accrediting bodies such

as JCAHO and some state pharmacy boards have also

adopted recent revisions to sterile compounding standards

issued in Chapter 797 of the U.S. Pharmacopeia (USP)

(U.S. Pharmacopeial Convention, Inc. 2004). In addition,

many hospitals institute their own quality safeguards, 

such as multiple reviews of orders, to prevent medication

errors. The Nuclear Regulatory Commission (NRC) and

individual states regulate and license institutions that use

radioactive materials. All hospitals must follow stringent

NRC and state guidelines on how those materials are

stored, transported, and disposed of (CORAR 2004). All

of these activities should be reflected in cost elements such

as the storage space required, the supplies and equipment

used, or the labor involved. The costs that hospitals incur

to manage and document their compliance with NRC and

state guidelines fall under pharmacy and nuclear medicine

management.

Categorizing products

Users of any payment adjustment for handling costs 

will need to group products according to the level of

resources used. The study products vary considerably,

from radioactive injections and chemotherapy infusions 

to simple oral tablets. In discussions with stakeholders 

and the technical advisory panel, MedPAC identified 

four characteristics that correlate with the level of

resources needed for handling: (1) radioactivity, (2)

toxicity, (3) mode of administration, and (4) special

handling needs. Initially, the pharmacists in MedPAC’s

advisory group used these characteristics to group the

study products into nine categories. After reviewing

information collected by the contractor from the case

studies, panel members reduced the number of categories

to seven in order to collapse those with similar handling

costs (Table 6-3 and the glossary of terms, p. 146). 

The technical advisory panel ranked categories, with

radiopharmaceuticals requiring the greatest resources and

oral preparations requiring the least. 

In general, radioactive materials require greater handling

resources than drugs. First, their additional safety

requirements affect every component of handling costs.

These measures include, for example, lead-lined storage,

special protection during preparation, and disposal in

accordance with strict regulations. Next, because the level

of radioactivity changes over time according to the

product’s half-life, radiopharmacies need to make

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 145

Categories for drugs, biologicals, 

and radiopharmaceuticals and 

their relative handling costs

Relative

Category Description handling cost*

1 Orals (oral tablets, capsules, solutions) 0.36

2 Injection/sterile preparations 

(drawing up a drug for administration) 1.00

3 Single IV solution/sterile preparations 

(adding a drug or drugs to a sterile IV 

solution) or controlled substances 1.28

4 Compounded/reconstituted IV preparations 

(requiring calculations performed correctly 

and then compounded correctly) 1.61

5 Specialty IV or agents requiring special 

handling in order to preserve their 

therapeutic value or oral cytotoxic agents 

(chemotherapeutic, teratogenic, or toxic) 

requiring personal protective equipment 2.70

6 Cytotoxic agents (chemotherapeutic, 

teratogenic, or toxic) in all formulations

except oral requiring personal

protective equipment 5.33

7+ Radiopharmaceuticals: basic and complex

diagnostic agents (including PET), 

therapeutic agents, and

radioimmunoconjugates N/A

Note: IV (intravenous), PET (positron emission tomography), N/A (not available).

Due to insufficient cost data and handling information on 

radiopharmaceuticals from case-study sites, the expert panel did not 

provide final recommendations for categorizing these products.

*Relative handling costs are calculated as follows: MedPAC’s expert 

panel selected at least one product from each category—generally those 

with the largest volume within 2002 Medicare claims under the outpatient 

prospective payment system. The Lewin Group calculated median 

handling costs for each drug selected across four case-study facilities that 

conducted microcosting exercises, where the median is the average of the 

middle two observations ranked by cost. Lewin divided each category’s 

median cost by the median cost for Category 2. For categories in which 

cost information was available for more than one product, the values 

reflect relative costs weighted by volume.

Source: The Lewin Group for MedPAC, 2005.

TABLE

6-3
additional checks and coordinate with providers and

patients to ensure a therapeutic dose and to minimize

wastage. These requirements, in turn, lead to management

costs as hospitals must ensure and document compliance. 

Toxic products, such as chemotherapy drugs, generally

require greater handling costs than nontoxic drugs because

of the need to protect both pharmacy workers and patients.

Pharmacists must carefully check dosages and sometimes

lab results to ensure that patients can tolerate the drugs.

Pharmacists and technicians must prepare certain products

under laminar flow hoods and use personal protective

equipment. Disposal of toxic waste can be a considerable

expense, and some toxic products require special storage

considerations, such as extremely low temperatures. These

costs accrue regardless of how the drug is administered. 

The mode of administration can also influence handling

costs due to the time pharmacists and technicians spend 

in preparing the materials. In general, stakeholders and

technical advisory group members said that IV

preparations require more resources than simple

injections. For example, pharmacists or technicians might

combine multiple drugs into a single infusion. They also

may reconstitute powders into liquid form, a practice that

can require significant amounts of time. By contrast,

injections generally require that the pharmacist or

technician draw a measured dose into a syringe. Oral

drugs generally require the fewest resources for

handling.10

Special handling means some products require particular

care in their preparation, storage, and transport in order 

to retain their therapeutic value. For example, some

products should not be transferred from the hospital

pharmacy to the point of administration through

pneumatic tubes because they can become denatured 

if shaken too vigorously. MedPAC’s panel of experts

believed that this need for special handling was associated

with greater handling costs, even if the product itself was

not radioactive or highly toxic. A significant number of

new agents under development are protein-based

antibodies that may require special handling.

Understanding the handling costs associated with

radiopharmaceuticals requires additional study because

hospitals procure these products in two distinct ways: 

(1) either already prepared, or (2) as inputs to be prepared

on site.11 Handling costs vary according to the form in

which hospitals order the product. This form may depend

146 Payment for p harmacy handling costs in hos p ital out p atient de p artments

Glossary of terms

Drugs: Any chemical compound used in the

prevention, diagnosis, treatment, or cure of disease, 

for the relief of pain, or to control or improve any

physiological or pathological disorder.

Biologicals: Products derived from living

material—human, plant, animal, or microorganism—

applicable to the prevention, treatment, or cure of

diseases or injuries.

Cytotoxic agents: Substances that have toxic effects

on certain cells. They are capable of causing injury or

death if handled without proper personal protective

equipment or if used inappropriately.

Teratogenic agents: Substances that can cause

developmental malformations if handled without proper

protection or if used inappropriately.

Radiopharmaceuticals: A drug or biological product

that contains a radioactive entity. They are used in

medicine for diagnostic and therapeutic purposes.

Diagnostic radiopharmaceuticals: Radioactive

drugs or biological products that contain a radionuclide

that typically is used with planar imaging, single photon

emission computed tomography, positron emission

tomography (PET), or other radiation detection probes. 

Therapeutic radiopharmaceuticals: Agents intended

to exert a cytotoxic effect on certain targeted tissues.

Radioimmunoconjugates: Agents that contain

combinations of diagnostic or therapeutic substances

linked with specific immune substances such as

immunoglobulins, monoclonal antibodies, or antigens.

They are used for specific targeting of drugs and

radioisotopes in treating certain cancers. on factors that are specific to the patient’s plan of care and

the product’s availability. One recent survey suggests that

80 percent of hospital-based nuclear medicine facilities

purchase their radiopharmaceuticals as commercially

prepared patient doses from radiopharmacies (Merlino

2004). In these cases, the invoice for the product combines

handling costs with acquisition costs and delivery fees.

Some hospitals create their own radiopharmaceuticals on

site in their nuclear medicine departments. In this case, 

the handling costs will be much higher but the acquisition

costs will be much lower, because the hospitals purchase

only component ingredients. Hospitals that prepare

radioactive materials on site may have less wastage but

significantly higher costs for shielding and equipment. 

The “make versus buy” decisions of nuclear medicine

departments constitute a dimension of complexity that

CMS will need to consider. Given its limited case-study

approach, MedPAC could not adequately determine the

relative costliness of one approach versus the other, 

or the circumstances in which compounding

radiopharmaceuticals in house would be more 

appropriate. 

The technical advisory panel initially discussed at least

two categories for radiopharmaceutical handling costs.

These two categories are based on whether products are

basic diagnostic agents or one of three other types: 

(1) complex diagnostic agents, (2) therapeutic agents, or

(3) radioimmunoconjugates. These three types of products

likely have higher handling costs because they require

personnel with more specialized training to prepare them,

more shielding and protective equipment, and additional

regulatory compliance programs (Callahan 2005). If a

facility conducts its own compounding, handling costs

could also include shielded storage areas for radioactive

generators, additional equipment for measuring

radionuclidic purity, and other supplies. Although

MedPAC presents radiopharmaceuticals as one category

in Table 6-3 (p. 145), the topic deserves further study to

better understand how handling costs for these products

differ. Based on interviews with radiopharmacists, the

range of handling costs within a single category of

radiopharmaceuticals can be greater than the range 

within any of the other product categories. Thus, CMS

may want to consider establishing multiple categories 

for radiopharmaceuticals.

Case studies 

In order to validate the proposed framework and

classification of products, MedPAC contracted with 

The Lewin Group to conduct four case studies of hospital

outpatient pharmacy and nuclear medicine department

handling costs. A case-study approach helped to ensure

that we employ common definitions and have a more

thorough understanding of participating facilities’

handling costs.12 Lewin asked each hospital or hospital

system to categorize the study products using the proposed

classification system to determine whether the facility put

products into the same categories as the pharmacists on

our advisory panel. Lewin also asked the case-study sites

to estimate handling costs for at least one product in each

category, using the proposed framework to identify

handling costs. 

MedPAC does not claim that one can generalize from

estimates of handling costs provided by four case-study

facilities to all hospitals. Consequently, MedPAC asked

Lewin to report on relative costs across categories of

products rather than reveal specific dollar-value estimates.

This confidential approach not only helped secure

hospitals’ participation but also allowed for comparison of

relative costs across hospitals without having the results

confounded by the level of costs.13

To check the reliability of the classification developed by

the pharmacists on the technical advisory panel, the

contractor asked each case-study facility to put about 230

products covered by this study into one of nine initial

categories.14 By comparing responses across facilities,

Lewin could then assess whether the categories were clear

and well-understood and whether different pharmacists put

drugs into the same categories (a reliability test). The

contractor asked case-study facilities if the categories

correlate well with the resources they devote to pharmacy

handling costs. Preliminary responses from those

interviews suggested that most of the categories were

clear, with pharmacists placing 83 percent of the products

into the same categories.15 After reviewing case-study

results, the advisory panel reassigned a small number of

products to other categories, which raised the rate of

correspondence to 89 percent. Both the advisory panel and

participating sites reported that the categories were

consistent and reflected increasing levels of handling

costs. One caveat to this analysis, however, is that only

one of the case-study hospitals compounds its own

radiopharmaceuticals. 

Four facilities undertook microcosting analyses of

handling costs for unit doses of six to nine products, one

from each category that they could cost (three facilities

could not cost radiopharmaceutical products because they

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 147
contract out nuclear medicine services). The four

facilities’ cost analyses followed MedPAC’s framework

for defining handling costs. The result was a detailed

costing of the functions shown in Figure 6-2 (p. 144):

pharmacy and nuclear medicine management, storage,

preparation, transport, and disposal. The pharmacists in

the advisory group selected specific products in each

category that generally reflect the highest volume products

typifying the categories’ characteristics. Lewin asked all

of the facilities to cost out the same product for seven

categories; in two categories, one hospital costed a

different product because it did not use the product

selected by the advisory group. 

Facilities reported that the costing exercise was feasible

and that they could isolate the inputs of handling costs.

However, they also reported that the exercise was time

consuming, requiring between 16 and 40 hours to

complete. In addition, the contractor made follow-up

phone calls with case-study facilities to ensure that the

components of cost were comparable to one another.

Nevertheless, the exercise showed that it is possible for

hospitals to measure handling costs as they do routinely

for other services. This exercise would allow hospitals 

to develop charges for pharmacy services.

The results of the microcosting exercise show that

handling costs generally increase across the categories

(Table 6-3, p. 145). The expert panel arrived at these 

seven categories after reviewing results of the

microcosting exercise using nine categories and then

collapsing them.16 To calculate the relative values, Lewin

first took the median of estimated costs for each category

across case-study sites.17 Then, Lewin divided each each

category’s median cost by the median for Category 2,

injections/sterile preparations. Thus, the median handling

costs for Category 3, simple IV solutions/sterile

preparations (where a single drug is added to an IV) 

or controlled substances, are about 1.3 times those for

Category 2. The costs for Category 4, complex IV

solutions in which the pharmacist must perform

calculations correctly to compound the preparation, are 

1.6 times those of Category 2. Similarly, Category 6,

cytotoxic agents in all formulations except oral, which

require the pharmacist or technician to use personal

protective equipment, have handling costs that are

approximately 5.3 times those of Category 2. Note that

since Lewin could not collect sufficient information 

about the handling costs of radiopharmaceuticals, these

products were presented as one category and without a

relative value. However, the data that Lewin was able to

collect suggest that these handling costs could vary widely

and relative values are likely to be considerably higher

than those shown for Categories 1 through 6. For this

reason, radiopharmaceuticals may require several

categories of handling costs.

Of course, uncertainty exists behind each set of cost

estimates from the case studies. For example, analysts at

one facility initially estimated labor costs assuming that

pharmacists and pharmacy technicians “multitask”—that

is, work to prepare several products at the same time.

Because the other case-study sites did not use a similar

approach, the contractor asked that facility to reestimate

labor costs without its multitasking assumption. If

multitasking is common when handling these products, 

the level of “true” handling costs would be lower than

those collected for this study, although relative costs 

might not be affected. 

Other costs are likely understated. For example, many

hospitals are only in the initial phases of carrying out 

new regulatory guidelines, such as USP’s Chapter 797,

Standards on Compounding Sterile Preparations.

Compliance with those standards would likely raise

estimates of handling costs for some categories of

products. However, full compliance will take time,

because some hospitals will need to make capital

expenditures that hospital administrators may not 

have already built into their plans. 

Given resource constraints, Lewin generally asked casestudy sites to provide information for the handling costs of

just a single product in each category. Clearly, however,

many products would fall within each category. Although

variation undoubtedly exists in handling costs among the

products that fall within a given category, MedPAC relied

on the expert judgment of its technical advisory panel and

the informed opinions of pharmacists and finance officials

at case-study sites to devise categories of products that

reasonably capture gradations of resource use.

The case-study analysis demonstrates that it is feasible for

hospitals to collect data that would help them establish

charges for handling services. 

RECOMMENDATION 6A

The Secretary should establish separate, budgetneutral payments to cover the costs that hospitals incur

for handling separately paid drugs, biologicals, and

radiopharmaceuticals.

148 Payment for p harmacy handling costs in hos p ital out p atient de p artments
RATIONALE 6A

When CMS begins to pay hospitals for drugs, biologicals,

and radiopharmaceuticals based on their acquisition costs,

the payment system will no longer directly reimburse

hospitals for their costs in storing, preparing, and

disposing of these products. Pharmacy handling costs are 

a nontrivial expense for hospital outpatient departments

and thus, a payment adjustment seems appropriate. Since

CMS previously built handling costs into the outpatient

PPS payment pool (by basing payment on hospital

charges), any adjustment should be budget neutral.

IMPLICATIONS 6A

Spending

• Given budget-neutral implementation, this

recommendation will have no impact on program

spending.

Beneficiary and provider

• In general, any effects on beneficiaries and providers

are likely to be small. This recommendation may help

ensure beneficiary access to care by more directly

linking payment to handling costs. Hospitals may

receive higher or lower payments based on the mix of

drugs they use, but such distributional impacts are

likely to be minimal. 

What are the options for collecting data?

To implement a payment adjustment for handling costs,

CMS would need data to set payment rates. MedPAC

considered three means of collecting data: (1) surveying

hospitals periodically, (2) conducting a series of

microcosting analyses, and (3) requiring hospitals to

submit charges. Each approach has limitations, but

requiring hospitals to submit charges has the advantage 

of providing data in the same form that CMS uses to 

set payment rates for all other services under the 

outpatient PPS.

One approach to collecting data for setting payment rates

is to survey hospitals in much the same way that the MMA

directed GAO to survey hospitals on the acquisition cost

of specified covered outpatient drugs, and then set

payment rates based on periodic survey results. However,

a survey approach might be less successful for collecting

data on pharmacy handling costs than for product

acquisition costs. In the case of the latter, GAO asked

hospitals to provide data from product invoices—a

relatively unambiguous if tedious task for the more than

1,000 national drug codes involved. For handling costs,

each hospital might use its own definitions and accounting

approach for enumerating the costs of pharmacy and

nuclear medicine departments, then allocate those costs

across other cost centers. Previous MedPAC work on

hospital charging practices suggests that these different

accounting approaches would confound attempts to collect

data on handling costs through surveys.

Alternatively, CMS could periodically conduct a series 

of microcosting analyses, in much the same way that

MedPAC’s case-study facilities did. However, CMS

would need a larger sample of hospitals estimating 

costs for more products in order to develop a more

representative and stable set of cost estimates. CMS 

could use those analyses to establish payment rates in

certain benchmark years, with indexes of cost growth 

used to update costs in other years. For example, one

recent study of pharmacy costs for preparing

chemotherapy infusions used a microcosting approach

(Pharmacotherapy Outcomes Research Center 2005).18

Time-and-motion studies are a common part of such

exercises, in which cost analysts measure directly the

amount of pharmacist and pharmacy technician time and

other resources that pharmacies use to prepare specific

products. Although this approach offers the most promise

for measuring resource use accurately, CMS would likely

find it prohibitively expensive to conduct such studies for

a representative sample of hospitals and for a wide variety

of drug, biological, and radiopharmaceutical products.

Under a third approach, CMS would require hospitals to

submit charges for pharmacy handling costs under a

limited number of separately paid APCs. Those APCs

would be designed to reflect categories of pharmacy

handling costs in much the same way as the seven

categories of products devised by MedPAC’s technical

advisory panel. Hospitals would submit charges based on

their handling costs for each administration delivered to a

patient. If CMS needs to set payment rates before they

begin to collect hospital charge data, the agency could

conduct a limited number of microcosting analyses for 

a set of products to set initial payments. Ultimately,

however, CMS would set payments in the same manner 

as for other APCs: by calculating the median of hospitals’

charges reduced to costs for those services, thereby

limiting the burden on CMS.

Requiring hospitals to set charges for handling costs has

disadvantages and advantages. CMS has no control over

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 149
the level of sophistication that hospitals would use to

develop charges for handling costs. While some hospitals

might conduct “time and motion” studies or detailed cost

analyses, other hospitals might use cruder approaches.

Nevertheless, CMS would use the charges that hospitals

developed from both more and less sophisticated methods

to set payment rates. An advantage of requiring hospitals to

set charges is that this process automatically would provide

CMS with updated information about handling costs. In

comparison, CMS would need to repeat surveys or

microcosting analyses periodically in order to keep

information current.

RECOMMENDATION 6B

The Secretary should:

• define a set of handling fee APCs that group drugs, 

biologicals, and radiopharmaceuticals based on 

attributes of the products that affect handling costs;

• instruct hospitals to submit charges for those APCs; 

and

• base payment rates for the handling fee APCs on 

submitted charges, reduced to costs.

RATIONALE 6B

In order to set more accurate payment rates for pharmacy

department services, CMS should base handling fees on

handling costs for preparing a drug administration or

nuclear medicine procedure, rather than making these

handling fees proportional to the acquisition cost of the

product. CMS could use MedPAC’s framework to develop

separate payments for hospital pharmacy handling costs.

Our contractor conducted categorization and microcosting

exercises at four case-study sites to test whether hospitals

could understand the framework and collect information

about handling costs in order to set charges for handling

services provided by pharmacy and nuclear medicine

departments. MedPAC’s analysis suggests that developing

charges for handling costs is feasible. 

IMPLICATIONS 6B

Spending

• This recommendation will have no impact on program

spending.

Beneficiary and provider

• In general, any effects on beneficiaries and providers

are likely to be small. This recommendation may help

ensure beneficiary access to care by making more

direct payment for handling costs. Some hospitals

may incur costs to develop charges for handling costs;

however, those costs are likely to be relatively small

compared with similar efforts that hospitals undertake

to develop charges for all other services that they

provide. For hospitals that deliver a larger volume 

of this study’s products, developing charges for

handling costs could be worthwhile because under 

this recommendation, Medicare would pay hospitals

directly for pharmacy department services.

A longer term agenda: Broader

payment bundles in the outpatient PPS

MedPAC’s study question falls within the context of the

Congress’s changes to payment rates beginning in 2006,

when Medicare will pay hospitals based on the hospitals’

average acquisition costs for the study products.

Therefore, our analysis focused on the need for—and

design of—a payment adjustment for handling costs.

However, for the longer term, a broader question is

whether the current approach to paying for drugs in the

outpatient PPS provides incentives for delivering those

hospital services efficiently.

Under the outpatient PPS, the unit of payment is the

ambulatory payment classification, or APC. The breadth

or narrowness of a bundle within the outpatient PPS 

varies tremendously by APC. For some services, such as

outpatient surgery, considerable packaging takes place.

The APC includes all costs incurred by the hospital to

admit and prepare the patient, staff and equip the 

operating room, supply products needed during the

procedure (including inexpensive drugs), and observe 

the patient after the procedure. (Medicare pays for

physician services separately.) In contrast, the outpatient

PPS includes separate APCs for every drug that costs at

least $50 per administration, as well as separate payments

for drug administration, and—if CMS adopts MedPAC’s

recommendation—a separate handling fee. 

If CMS adopts a handling fee, the outpatient PPS will

have a greater degree of unbundling for drugs than other

Part B payment systems. In physician offices, Medicare

makes one payment for the drug, while handling costs 

are built into the payment for drug administration. For

dialysis facilities, Medicare bundles payment for many 

of the drugs, their handling, and administration costs into

the composite rate for dialysis services.

150 Payment for p harmacy handling costs in hos p ital out p atient de p artments
One can see the disproportionate unbundling of drugs in

the number of APCs. All clinic visits, procedures, and

diagnostic tests paid for under the outpatient PPS are

described by about 450 APCs. In comparison, some 300

APCs exist for separately paid drugs, which account for a

small share of payment.19

Initially, CMS proposed packaging many drugs with

related procedures. It determined payments using the same

process as for other items: charges from the claims

reduced to costs using cost-to-charge ratios (CCRs) from

cost reports. Manufacturers’ concerns about the accuracy

of hospital coding and methods that CMS used to set

payment rates led to gradual unbundling of payments for

drugs and radiopharmaceuticals as well as to the use of

alternative data sources for setting payment rates. 

Manufacturers and others worry that bundling would make

hospitals less willing to supply expensive drugs if CMS

calculated the payment rates as the median costs among

claims that included lower cost products as well. They

argue that newer agents provide significant advances in

therapy, and thus the design of payment bundles could

adversely affect patient care. Manufacturers and others

also argue that the standard approach to setting payments

is inadequate for expensive drugs, due to the poor quality

of coding for claims and to practices that underestimate

costs for more expensive items and overestimate costs for

less expensive ones. 

Historically, hospitals did not need to code individual

drugs using HCPCS codes, nor did they need to accurately

record the number of units because payment was based 

on total charges. Today, however, hospitals must bill

separately paid drugs with a HCPCS code and must 

ensure that the units are accurate in order for CMS to set

reasonably accurate payment rates. As experience with the

outpatient PPS builds, hospitals’ coding should become

more accurate. But the payment system is complex, and

some hospitals use antiquated billing systems. For these

reasons, hospitals continue to struggle with their coding.

Charge compression results from the interaction of

hospitals’ methods of setting charges and CMS’s method

of converting those charges to costs. Generally, CMS 

uses a single CCR to convert the charges for all services 

in a single revenue center, such as pharmacy, into costs.

Within a revenue center, however, some hospitals mark 

up inexpensive products more than they do expensive

products, which leads to charge compression. For

example, when setting charges for a generic antibiotic, 

a hospital may mark up its acquisition cost by a factor 

of six, while it marks up an expensive chemotherapy drug

by a factor of two. If CMS uses a single CCR that covers

all pharmaceuticals to estimate costs from the resulting

charges, the approach will tend to overestimate the costs

of inexpensive items while generally underestimating the

costs of expensive items. MedPAC’s survey of hospital

charge-setting practices confirmed that hospitals often 

use smaller markups on more expensive items. Other

researchers have found similar results (GAO 2004).

Although this phenomenon may lead to inaccurate

estimates of costs for individual products, the global

estimate of costs for pharmacy products should not

change: Any overestimate of lower cost items should

generally balance out any underestimate of higher cost

items. This balancing out may be one reason why concern

over charge compression is greater among manufacturers

of drugs, biologicals, and medical devices than among

hospitals.

When some items are bundled and others are not, the

payment system provides an incentive to use those

products paid separately, if they are more profitable than

the bundled items. MedPAC has documented considerable

problems in payment for dialysis treatment—such as rapid

increases in use of separately paid items—when CMS

bundles payment for some services and bills separately for

other services, notably drugs. CMS is conducting a

demonstration to broaden the dialysis bundle and counter

those problems. In the outpatient PPS, providers have an

incentive to substitute a high-cost drug that is separately

payable for a lower cost drug that would be bundled into

the APC payment for the service. If hospitals act on this

incentive, it could raise beneficiaries’ overall cost sharing,

Part B premiums, and Medicare’s program spending.

In addition, setting payment rates for small bundles is

likely to be less accurate than setting rates for larger

bundles. Isolating a single input requires great precision 

in setting payment rates. Given the tools available to

CMS, that precision may not be possible. Relying on

outside data sources, such as the GAO study of acquisition

costs, is administratively cumbersome. It also requires

considerable administrative resources that CMS might

better spend elsewhere. 

With broader payment bundles, variations in charging

practices across inputs are more likely to balance out,

leading to payment rates that, on average, are close to

costs. Furthermore, greater bundling of hospital outpatient

department services could work in tandem with payment

approaches that take into account quality and efficiency.

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 151
For example, rather than paying for each administration 

of chemotherapy, CMS may be able to identify episodes of

chemotherapy treatment. Ideally, both payment and

performance measurement would span entire episodes.

Currently, broader bundles do not exist, but additional

research could result in a more streamlined payment

system that offers better incentives. As MedPAC continues

to pursue its agenda on refinements to the outpatient PPS,

we will investigate this topic. 

152 Payment for p harmacy handling costs in hos p ital out p atient de p artments

Mandate for this study (excerpts from Section 621 of the MMA)

(a) Payment for Drugs. 

(1) Special rules for certain drugs and biologicals.

Section 1833(t) (42 U.S.C. 13951(t)), as amended by

section 411(b), is amended by inserting after

paragraph (13) the following new paragraphs:

“(14) Drug APC payment rates. 

...

“(B) Specified covered outpatient drug defined. 

“(i) In general. In this paragraph, the term

‘specified covered outpatient drug’ means,

subject to clause (ii), a covered outpatient drug

(as defined in section 1927(k)(2)) for which a

separate ambulatory payment classification group

(APC) has been established and that is—

“(I) a radiopharmaceutical; or

“(II) a drug or biological for which payment

was made under paragraph (6) (relating to passthrough payments) on or before December 31,

2002.

“(ii) Exception. Such term does not include—

“(I) a drug or biological for which payment is

first made on or after January 1, 2003, under

paragraph (6);

“(II) a drug or biological for which a temporary

HCPCS code has not been assigned; or

(III) during 2004 and 2005, an orphan drug (as

designated by the Secretary).

...

“(E) Adjustment in payment rates for overhead

costs.

“(i) MedPAC report on drug APC design. The

Medicare Payment Advisory Commission shall

submit to the Secretary, not later than July 1,

2005, a report on adjustment of payment for

ambulatory payment classifications for specified

covered outpatient drugs to take into account

overhead and related expenses, such as pharmacy

services and handling costs. Such report shall

include—

“(I) a description and analysis of the data

available with regard to such expenses;

“(II) a recommendation as to whether such a

payment adjustment should be made; and

“(III) if such adjustment should be made, a

recommendation regarding the methodology

for making such an adjustment.

“(ii) ADJUSTMENT AUTHORIZED. The

Secretary may adjust the weights for ambulatory

payment classifications for specified covered

outpatient drugs to take into account the

recommendations contained in the report

submitted under clause (i). 

Sec. 621. Hospital outpatient department (HOPD) payment reform.
Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 153

1 Specifically, manufacturers believe that hospitals set their

charges for higher cost drugs with smaller markups than for

lower cost drugs and services. Manufacturers are concerned

that if hospitals adjust drug charges to costs using a single

department-wide cost-to-charge ratio, estimated costs will be

too low for high-cost drugs and too high for lower cost items

(PhRMA 2003). See the section on broader payment bundles

later in this chapter for a more detailed discussion.

2 Some of the few available sources are annual national

surveys of pharmacy practices in hospital settings conducted

by the American Society of Health-System Pharmacists

(ASHP). Although these surveys provide useful insights,

they focus on the role of pharmacists in managing the

medication-use process rather than tracking the cost of all

resources needed to perform pharmacy services. The ASHP

also conducts an annual pharmacy staffing survey to gauge

the supply of and demand for pharmacists and pharmacy

technicians.

3 Maryland uses a regulatory process to set the rates that

hospitals charge. Because of its regulatory approach, the

state collects detailed cost information from hospitals,

including the acquisition cost of drugs, salaries and fringe

benefits, and other supplies used in hospital pharmacy

departments.

4 Given budget-neutral recalibration of the relative weights,

any decrease in the relative weights for drugs, biologicals,

and radiopharmaceuticals that results from moving to

acquisition cost would result in slightly increased relative

weights for other services. Total payments for all services

would remain the same. 

5 The outpatient PPS experienced a full market basket update

in 2001, 2003, 2004, and 2005. 

6 Despite the law, pass-through payments from August 2001

through April 2002 were not adjusted to ensure budget

neutrality.

7 The interim payment rates depend on the type of drug and

are based on AWPs as of May 1, 2003. Sole-source drugs

were paid between 88 percent and 95 percent of the reference

AWP in 2004 and are paid between 83 percent and 95

percent of the reference AWP in 2005. Innovator multiplesource drugs are paid up to 68 percent of the reference AWP.

Noninnovator multiple source drugs are paid up to 46

percent of the reference AWP.

8 CMS would need to consider how to pay hospitals for

handling combination therapies. Options include paying a

handling fee for each individual product, paying one

handling fee for the more resource-intensive product of the

combination, or paying one handling fee for the first product

listed when they are billed for concurrent handling and a

smaller percentage for each subsequent product.

9 Although most hospitals do not set separate charges for their

handling costs, a small number do. Some hospitals also bill

separately under evaluation and management codes for the

time that pharmacists spend educating individual patients

about their drug regimens and answering their questions.

10 Controlled substances constitute an exception.

11 Some hospitals make decisions daily about whether to

prepare radiopharmaceuticals in house or to purchase

commercially prepared unit doses, depending on the

hospital’s expected caseload of patients.

12 MedPAC initially considered conducting a representative

survey (as GAO is doing for its study on acquisition costs)

but concluded that it would be difficult to ensure the

comparability of any data collected. We based that decision

on the lack of common definitions for these costs and on

observations from hospital pharmacy and finance directors

that hospitals account for their pharmacy costs in very

different ways. 

13 Four hospitals or hospital systems committed to participating

in both parts of the case-study analysis (categorizing drugs

and providing estimates of handling costs). All four hospitals

or hospital systems are located on the East Coast and range

in size from 100 to more than 700 beds. Three are located in

large urban areas (population greater than one million), and

one is located in a smaller urban area. One of the facilities 

is an outpatient cancer center associated with a major

teaching hospital. For each case study, directors of finance,

pharmacists, and cost analysts generously shared their time

and expertise. Two additional hospital systems—one in the

South and another in the East—agreed to conduct the

categorization but not the costing exercise. 

14 Lewin did not require hospitals to categorize products that

they do not dispense.

15 The majority of cases in which categorizations differed

involved situations in which hospitals used different forms of

the same product—for example, a prepackaged liquid versus

a powder form that requires reconstituting. 

Endnotes
16 This study’s technical advisory panel initially used separate

categories for oral cytotoxic agents and specialty IV agents

that require special handling, but then they later grouped

both within Category 5 because both agents’ handling costs

were of a similar magnitude. One external reviewer of this

study suggested splitting those two types of agents because

they believe that changes in therapy, handling procedures,

and the need to track utilization warrant separate groupings. 

17 Because there was an even number of sites (four), the

median was calculated as the simple average of the two

middle values. Although there was substantial variation in

estimated costs for any one product across case-study sites,

the cost data demonstrate that the categories reflected

increasing levels of handling costs.

18 This study evaluated handling costs at two academic medical

outpatient infusion centers and two community cancer

centers. The study focused on facilities that provide only

chemotherapy, rather than a mixture of medication therapies

as most U.S. hospitals provide.

19 Given the changing definitions, it is difficult to compare 

the number of APCs to the share of spending. However,

pass-through drugs, separately paid drugs, and blood

products accounted for about 7 percent of spending in 2002. 

154 Payment for p harmacy handling costs in hos p ital out p atient de p artments
Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 155

Association of Community Cancer Centers. 2004. Presentation on

GAO and MedPAC studies prepared for member hospitals.

Washington, DC: ACCC. 

Callahan, R. J. 2005. Non-acquisition costs to hospitals for

handling radiopharmaceuticals. Unpublished paper prepared for

The Lewin Group, Boston, MA.

Council on Radionuclides and Radiopharmaceuticals. 2004.

Presentation to MedPAC staff on radiopharmaceutical overhead

costs. Moraga, CA: CORAR. October 21.

Government Accountability Office. 2004. Medicare: Information

needed to assess adequacy of rate-setting methodology for

payments for hospital outpatient services. GAO–04–772.

Washington, DC: GAO. September. 

Government Accountability Office. 2001. Medicare: Payments

for covered outpatient drugs exceed providers’ cost.

GAO–01–1118. Washington, DC: GAO. September. 

Kathpal Technologies. 1999. High cost drugs under the

Outpatient Prospective Payment System. Prepared for the 

Health Care Financing Administration. Fairfax, VA: Kathpal

Technologies. September.

Medicare Payment Advisory Commission. 2003. Report to the

Congress: Variation and innovation in Medicare. Washington,

DC: MedPAC.

Medicare Payment Advisory Commission. 2002. Report to the

Congress: Medicare payment policy. Washington, DC: MedPAC.

Medicare Payment Advisory Commission. 2000. Report to the

Congress: Selected Medicare issues. Washington, DC: MedPAC.

Merlino, D. A. 2004. Nuclear medicine facility survey: Society of

Nuclear Medicine 2003 survey reporting on 2002 cost and

utilization. Journal of Nuclear Medicine Technology 32, no. 4

(December): 215–219.

Morris, J. 2005. What if the cure is also a cause? Washington

Post, February 15.

National Institute for Occupational Safety and Health, Centers for

Disease Control and Prevention, Department of Health and

Human Services. 2004. NIOSH Alert: Preventing occupational

exposure to antineoplastic and other hazardous drugs in health

care settings. Publication no. 2004–165. Washington, DC:

NIOSH. http://www.cdc.gov/niosh/docs/2004-165/.

Office of Inspector General, Department of Health and Human

Services. 2001. Medicare reimbursement of prescription drugs.

No. OEI–03–00–00310. Washington, DC: OIG. January.

Pharmaceutical Research and Manufacturers of America. 2003.

Letter to T. S. Scully, CMS Administrator. October 6. 

Pharmaceutical Research and Manufacturers of America. 2002.

Letter to T. S. Scully, CMS Administrator. October 3. 

Pharmacotherapy Outcomes Research Center, University of Utah.

2005. Documentation of pharmacy cost in the preparation of

chemotherapy infusions in academic and community-based

oncology practices. Final report submitted to The Lewin Group

on behalf of the National Patient Advocate Foundation. Salt Lake

City, UT: Pharmacotherapy Outcomes Research Center. January.

The Lewin Group. 2005. Examining the relative handling costs 

of drugs delivered in hospital outpatient settings. Deliverable

provided to MedPAC. April.

U.S. Pharmacopeial Convention, Inc. 2004. Pharmaceutical

Compounding–Sterile Preparations. U.S. Pharmacopeia 28

(Chapter 797): 2461–2477. Rockville, MD: USP.

Worzala, C., and J. Ashby. 2004. Presentation on survey of

hospital charge-setting practices before the Medicare Payment

Advisory Commission, Washington, DC. September 10.

http://www.medpac.gov/public_meetings.

References

Critical access hospitals

CHAPTER 7

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 159

he Congress mandated that MedPAC study the effect of

the critical access hospital (CAH) provisions in the

Medicare Prescription Drug, Improvement, and

Modernization Act of 2003 (MMA). The CAH program

increases Medicare payments to small hospitals whose Medicare costs 

exceed prospective payment system (PPS) rates. The program has 

increased Medicare payments and the profitability of many small rural

hospitals. Cost-based payments for those CAHs will total about $5 

billion in 2006, roughly $1.3 billion more than under the PPS. The MMA

changes will cause a few more hospitals to convert to CAH status this

year but will also effectively stop conversions after 2005. 

Some CAHs are quite close to other providers. In 2003, approximately 17 percent of cost-based Medicare 

payments went to CAHs that were 15 or fewer miles from another hospital. This raises an issue of competition

between CAHs and providers paid under Medicare PPS. For example, Medicare payments to CAHs for post-acute

patients in swing beds are higher than rates paid to competing SNFs. Payment modifications and other 

adjustments may be needed for fair competition.

7

In this chapter

• Congressional mandate 

and background

• How does conversion to 

CAH status affect 

hospitals?

• Is quality of care at lowvolume rural hospitals 

comparable to that of 

higher volume rural 

hospitals?

• MMA changes to the

CAH program 

• Summary of findings

CHAPTER

T

Critical access hospitals
Congressional mandate and

background

The Congress mandated that MedPAC “analyze the 

effect on total payments, growth in costs, capital 

spending, and such other payment effects” of a broad

range of rural provisions in the Medicare Prescription

Drug, Improvement, and Modernization Act of 2003

(MMA). This rural report is due in December 2006. As 

an interim step, the Congress also mandated that “The

Commission shall submit to Congress an interim report 

on the matters...with respect to changes to the Critical

Access Hospital provisions under section 405” of the

MMA (see text box, p. 174). In this report, we describe 

the current state of the critical access hospital (CAH)

program and then evaluate the current and future

implications of the following four key aspects of 

section 405: 

• removing states’ ability to waive the requirement that

a CAH be located 35 miles by primary road and at

least 15 miles by secondary road from another

provider starting in 2006; 

• increasing the maximum daily acute census from 

15 to 25;

• allowing CAHs to operate PPS psychiatric and

rehabilitation units, which do not count toward the 

25-bed limit; and

• increasing CAH payments to 101 percent of costs.

History

In 1988, the Montana Hospital Research and Education

Foundation (an affiliate of the Montana Hospital

Association) designed a demonstration of a type of

hospital called a medical assistance facility (MAF) that

received cost-based reimbursement from Medicare. 

MAFs were isolated, limited-service hospitals that could

admit patients for up to a four-day length of stay. In 1989,

the Congress authorized the Rural Primary Care Hospital

(RPCH) program, a second demonstration program

whereby small, rural hospitals would receive cost-based

payments from Medicare. The Balanced Budget Act of

1997 (BBA) merged the MAF and RPCH programs into 

a new category of hospitals called critical access hospitals

(CAHs). CAHs would receive cost-based inpatient and

outpatient payments from Medicare. To qualify for the

CAH program, a hospital had to be 15 miles by secondary

road and 35 miles by primary road from the nearest

hospital or be declared a “necessary provider” by the state.

Because states can waive the distance requirement, the

CAH program became an option that could help almost all

small rural hospitals, as opposed to being limited to

helping isolated hospitals. 

Following the BBA, the Congress approved a series of

legislative and regulatory changes that made the program

more beneficial for rural hospitals (Table 7-1). In 2000,

the Congress categorized on-call payments to physicians

as a reimbursable expense and provided CAHs with 

cost-based reimbursement for post-acute services in swing

beds. Swing beds can be used for acute or post-acute care.

The MMA reduced restrictions on CAHs by allowing

them to treat up to 25 (rather than up to 15) acute patients

at one time, and to operate psychiatric or rehabilitation

units. The MMA also increased inpatient and outpatient

payments to CAHs from 100 percent of costs to 101

percent of costs. Advocates have argued that CAHs need

Medicare payments to be greater than costs so they can

build reserves to replace buildings and equipment that

continue to become more expensive. CMS restrained the

program’s growth somewhat in 2004 when it clarified that

observation beds that could also be used as inpatient beds

would count toward the 25-bed limit. As a result, some

hospitals that have a peak census above 25 patients may

have decided not to convert to CAH status. Given current

CAH payment policies, most rural hospitals that have a

peak census of 25 or fewer patients will benefit from

conversion to CAH status if they expect their Medicare

prospective payments to be less than 101 percent of

allowed Medicare costs.

CAH regulations also require that patients’ length of stay

in CAHs be limited to an average of four or fewer days. 

If a CAH fails to meet the four-day rule (a rare case),

CMS requires that the CAH develop and implement a 

plan of correction. The flexibility provided by swing 

beds makes it easier for CAHs to meet the four-day rule.

Physicians can discharge their patients to post-acute status

after three days of acute care if the patient meets the

clinical requirements for being discharged to post-acute

care. The patient can stay in the same swing bed and the

CAH receives the same cost-based payment. The average

Medicare acute length of stay at hospitals that converted to

CAH status fell from 3.8 days in 1998 to 3.2 days in 2003.

The sum of Medicare acute and post-acute days in swing

beds per Medicare discharge increased from 6.0 days in

1998 to 6.4 days in 2003 for hospitals with swing beds.

160 Critical access hos p itals
The increase in post-acute days per discharge may reflect

longer post-acute stays at the CAH and an increase in

patients transferred to the CAH for post-acute care.1

The number of CAHs has grown rapidly

As the series of legislative changes shown in Table 7-1

made CAH status more attractive, the CAH program grew

from 41 hospitals on January 1, 1999, to 1,055 hospitals

on January 1, 2005 (Figure 7-1). Most CAHs failed to

meet the 35-mile criteria for being considered an isolated

provider and entered the program based on state criteria

that declared them necessary providers. A state can declare

hospitals necessary providers only if it has an approved

rural health plan that lists the criteria used to determine

which hospitals are necessary providers. States have set

the criteria so that most (and in some cases, all) of their

small rural hospitals are declared necessary providers, and

therefore are eligible to be helped by the CAH program.

Criteria do not have to be closely related to access to care.

For example, some states give necessary provider status 

to all rural hospitals in counties with an above-average

percentage of people over age 65. One state declares

hospitals necessary providers if they have a high risk of

closure based on several considerations such as having a

low occupancy rate and being located in an area with local

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 161

Legislation and changes in 

regulation make CAH conversions 

easier and increase payments

Key aspects of CAH

Legislation legislation and regulations

BBA (1997) The CAH program is enacted. It allows rural 

hospitals to choose cost-based payments for 

outpatient and acute inpatient services if the 

hospitals agree to the following limitations:

• 15 acute patients.

• 25 total patients (including swing beds, 

excluding observation beds).

• All patients' length of stay is limited to 4 days. 

• States can declare rural hospitals 

“necessary providers,” removing the 

requirement that hospitals be isolated from 

other providers.

BBRA (1999) • Length-of-stay restriction is changed to an 

average of 4 days.

• States can declare hospitals “rural,” 

allowing CAHs to exist in MSAs.

BIPA (2000) • Medicare pays cost-based reimbursement 

of “on-call” payments to physicians. PPS 

hospitals do not receive this type of payment. 

• CAHs receive cost-based reimbursement 

for Medicare post-acute patients in 

swing beds. 

Cost accounting • CMS increases CAH Medicare post-acute 

regulations (2001) payments in rules regarding CAHs’ swing-bed

cost accounting methodology. 

MMA (2003) • Inpatient limit is expanded from 15 to 25 

acute patients.

• Rehabilitation and psychiatric units are 

allowed and do not count toward the 25-bed

limit. They are still paid PPS rates.

• Payments increased to 101 percent of costs.

• Starting in 2006, new CAHs must be 

35 miles by primary road or 15 miles by 

secondary road from another provider.

States can no longer waive this requirement.

CMS interpretive • CMS will count observation beds that could be

guidelines (2004) used as acute beds toward the 25-bed limit. 

Note: CAH (critical access hospital), BBA (Balanced Budget Act of 1997), 

BBRA (Balanced Budget Refinement Act of 1999), MSA (metropolitan 

statistical area), BIPA (Medicare, Medicaid, and SCHIP Benefits 

Improvement and Protection Act of 2000), PPS (prospective payment 

system), MMA (Medicare Prescription Drug, Improvement, and 

Modernization Act of 2003). 

TABLE

7-1

Note: CAH (critical access hospital). Number is as of January 1 of each year.

Source: The Rural Hospital Flexibility Tracking Project, 2003, and additional data 

 from CMS. Number of CAHs

1,200

800

1,000

600

400

200

0

1999 2004 2005 2000 2001 2002 2003

The CAH program

is growing rapidly

FIGURE

7-1
competition (Gale 2002). CMS gave states great flexibility

in setting necessary provider criteria because CMS

believed that the Congress intended to give the states

almost total control over this issue. 

In addition to the “necessary provider rule,” states can

declare hospitals rural, even those within metropolitan

statistical areas (MSAs). Due to the flexibility in the

“necessary provider” and rural requirements, only 18

percent of CAHs are more than 35 road miles from

another provider (Figure 7-2). We identified 151 

hospitals that were located 15 or fewer road miles 

from another provider and 616 that were located 15 

to 35 road miles from another provider.

How does conversion to CAH status

affect hospitals?

The CAH program is designed to increase Medicare

payments to low-volume hospitals whose Medicare costs

exceed PPS payment rates. Hospitals project whether their

costs (under CAH cost accounting) will exceed PPS

payment rates by hiring consultants. The Federal Office 

of Rural Health Policy provides hospitals with grant 

funds to pay these consultants through the Rural Hospital

Flexibility Grant program.2 CAHs receive four key 

types of cost-based Medicare payments: (1) inpatient, 

(2) general outpatient, (3) post-acute (swing-bed), and 

(4) laboratory payments.3 To estimate how the four types

of payment changed following conversion, we examine

changes in Medicare payments from 1998 (preconversion)

to 2003 (postconversion) for hospitals that converted

between 1999 and 2002. To control for industry-wide

changes in the volume of services, we compare changes in

Medicare payments for converting hospitals with changes

in Medicare payments for a comparison group of similar

hospitals that remained PPS hospitals during that

timeframe. 

Because all CAHs had 1,900 or fewer discharges in 

2003, we limit the comparison group to hospitals that

either became CAHs in 2004 or had fewer than 1,900

discharges in 2003. Because most CAHs are located in

rural locations, we also limit the comparison group to

hospitals outside core metropolitan areas, as defined by

Rural–Urban Commuting Areas (RUCAs), which use

census tracts (rather than counties) to evaluate the degree

to which various areas are rural (Morrill et al. 1999). We

further restricted CAHs and the comparison hospital

sample to hospitals that filed a 12-month (as opposed to a

partial-year) cost report in 1998 and 2003. The result is 

a set of 498 CAHs that converted to CAH status between

1999 and 2002 and 551 comparison hospitals that retained

their PPS status through 2003. The 551 comparison

hospitals are larger than the average existing CAHs, but

they still fall within the size range for CAHs.4 In fact,

during the first nine months of 2004, 141 of the 551

comparison hospitals converted to CAH status. We expect

that roughly half of the comparison hospitals will convert

to CAH status by the end of 2005.

In the subsections below, we first discuss the benefits of

cost-based inpatient, outpatient, and post-acute (swingbed) payments. We then turn to the more difficult issue of

laboratory payments. 

Inpatient Payments Medicare cost reports indicate 

that converting CAHs had reported inpatient costs that

exceeded PPS payments by an average of $10,000 before

conversion—indicating that for most hospitals, cost-based

162 Critical access hos p itals

Note: CAH (critical access hospital). Distances from 939 CAHs that were operating 

 in fall 2004 are to the closest hospital, which may be another CAH. 

 Indian Health Service CAHs and hospitals located closest to Indian Health 

 Service hospitals are excluded from this analysis. 

Source: MedPAC analysis of Medicare Cost Report file from CMS. Number of CAHs

450

350

400

300

250

200

150

100

50

0

5.1–15.0

143

15.1–25.0

401

25.1–35.0

215

35.1+

172

1.0–5.0

8

Distance to the nearest hospital

(in road miles)

Most CAHs are 15 to 35 miles

from other hospitals

FIGURE

7-2
inpatient reimbursement was a small incentive to 

convert. Following conversion, inpatient payments 

per CAH discharge increased from $3,868 in 1998 to

$4,704 in 2003, a 4 percent annual rate of increase. This 

change exceeded the 2.3 percent annual increase at the

comparison hospitals. The net annual average increase in

inpatient payments was $81,000 per hospital (Table 7-2, 

p. 164). Total inpatient payments to CAHs rose slower

than the rate of cost growth per discharge due to a decline

in the average number of Medicare acute discharges from

575 in 1998 to 499 in 2003 (Table 7-3, p. 166).

Outpatient Payments Converting hospitals 

reported total Medicare outpatient costs that exceeded

Medicare payments by roughly $100,000 in 1998 (before

conversion). CAH conversion allowed these hospitals to

eliminate the reported losses. In addition, conversion to

CAH status allows on-call payments to physicians and

other on-call providers to become a reimbursable

outpatient cost. Elimination of losses on outpatient

services and higher outpatient volume contributed to

CAHs increasing their outpatient payments more than

comparison hospitals (an annualized rate of 15 percent

compared with 5.7 percent per year [Table 7-2, p. 164]).

Over five years, outpatient payments increased by 

an aggregate of 69 percentage points faster than at

comparison hospitals. The one-time shift to cost-based

reimbursement accounts for much of this jump in

outpatient payments. 

Post-acute payments When a hospital converts to CAH

status, it qualifies for cost-based reimbursement for postacute patients in swing-beds. The shift from receiving

SNF rates for post-acute patients to receiving estimated

costs (which assume post-acute routine costs equal acute

routine costs) resulted in a dramatic increase in post-acute

care payments from $259 per day before conversion to

$1,016 per day after conversion (Table 7-2, p. 164). 

This compares to an increase from $262 to $270 at

comparison hospitals that operated swing beds in 1998

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 163

Swing-bed cost accounting rules result in higher post-acute payments 

I

n fiscal years starting before December 21, 2000,

Medicare paid critical access hospitals (CAHs) a

fixed payment for the costs associated with routine

care provided to post-acute patients in swing beds. This

fixed payment equaled the average cost of routine care

for post-acute patients in freestanding skilled nursing

facilities (SNFs). Due to the Medicare, Medicaid, and

SCHIP Benefits Improvement and Protection Act of

2000, CMS now uses a new method to calculate

payments for routine services (HCFA 2001). 

Under this new method, CMS pays for routine care

based on hospitals’ reported costs, averaged over acute

and skilled nursing patients. To calculate the cost of a

post-acute patient’s routine care, CMS divides the

hospitals’ total inpatient routine costs (acute and postacute) by the sum of acute and post-acute days to obtain

an estimated routine cost per day. Because hospitals’

routine costs per day exceed freestanding SNFs’ routine

costs per day, this change in payment methodology

causes a significant increase in payments for post-acute

care. In our sample of CAHs, payments for post-acute

care (including ancillary services) rose from $259 per

day before conversion to $1,016 per day after

conversion (Table 7-2, p. 164). 

Relative to the old method, the new payment

methodology increases payments for post-acute care

and decreases payments for acute care. The changes

reflect a shift in cost allocation from acute to post-acute

care. To compute the routine costs allocated to acute

patients, CMS starts with total inpatient routine costs

and then “carves out” the payments for Medicare postacute patients. CMS then allocates the remaining costs

to acute patients. When post-acute payments increase,

the amount that CMS carves out increases, and the costs

remaining to be allocated to acute patients decrease.

Although CAHs receive roughly $1,000 in Medicare

payments for every post-acute day, some of that gain is

offset by a reduction in costs allocated to acute patients.

For the marginal post-acute day, the net increase in

Medicare payments may be only $400 to $500 rather

than the full $1,000. Net revenue per post-acute day of

$400 to $500 is about $100 to $200 more than SNF

payment rates of roughly $300 per day. and 2003. The increased payment rates—not utilization—

were the primary reason that payments to converting

hospitals increased by an average of $463,000 per hospital 

(Table 7-2).

Most of the increased swing-bed revenue is offset by a

decline in payments for Medicare acute patient days.

Financial consultants to CAHs have informed us that some

hospital administrators do not fully appreciate how this

offset works. A more transparent pricing system may

improve hospital administrators’ ability to understand

exactly how much their Medicare revenue will increase

when they serve more Medicare post-acute patients in

swing beds. We discuss the details of swing-bed cost

accounting in the text box (p. 163).

The sum of inpatient, outpatient, and post-acute (swingbed) payments rose by 9.5 percent per year at hospitals

that converted to CAH status, compared with a 3.3 percent

rise at the comparison group hospitals (Table 7-2). If the

CAHs’ Medicare revenues had grown at the comparison

group’s annual rate (3.3 percent) rather than at their actual

rate (9.5 percent), Medicare payments per hospital for

inpatient, outpatient, and post-acute services would have

been approximately $750,000 lower in 2003. It should 

be noted that the rate of cost growth at the comparison

hospitals was roughly 1 percent above the rate of increase

in PPS payments. Therefore, the difference between 

the 9.5 percent payment increase for CAHs and the 

3.3 percent payment increase at PPS hospitals partially 

164 Critical access hos p itals

CAHs benefit from large increases in outpatient and swing-bed payments 

Medicare payments Medicare payments Annualized

1998 2003 Change growth rate

Total payments per hospital

CAHs that converted

after 1998 and before 2003

Inpatient $1,240,000 $1,321,000 $81,000 1.0 %

Outpatient 528,000 1,061,000 533,000 15.0 

Post-acute (swing-bed) + 117,000 + 580,000 + 463,000 37.7

Total payments 1,885,000 2,962,000 1,077,000 9.5

Comparison hospitals

that did not convert

Inpatient $2,363,000 $2,695,000 $332,000 2.7 %

Outpatient 786,000 1,038,000 252,000 5.7

Post-acute (swing-bed) + 134,000 + 122,000 + –12,000 –1.9

Total payments 3,283,000 3,855,000 572,000 3.3

Payments per unit of service

CAHs that converted

after 1998 and before 2003

Per acute discharge $3,868 $4,704 $836 4.0% 

Per post-acute day 259 1,016 757 31.4

Comparison hospitals

that did not convert

Per acute discharge $4,166 $4,670 $504 2.3% 

Per post-acute day 262 270 8 0.6

Note: CAH (critical access hospital). In this table, outpatient revenue in 1998 and 2003 does not include outpatient lab costs because fee schedule data were not readily 

available. The Medicare payments also do not include skilled nursing facility, home health, rehabilitation, or psychiatric unit payments, which are all paid based on 

prospective payment systems.

Source: MedPAC analysis of Medicare Cost Report file from CMS.

TABLE

7-2
reflects the fact that updates in PPS payments were lower

than increases in hospital costs from 1998 through 2003. 

Laboratory payments Traditional hospitals receive

payments for outpatient laboratory services based on a fee

schedule. CAHs receive cost-based payments. We cannot

precisely compute how much larger CAHs’ cost-based

laboratory payments are because we lack preconversion

Medicare cost data on laboratory services. However, 

our discussions with CAH accountants, analysis of

postconversion laboratory payments, and examination of

total lab costs before conversion suggest that, on average,

cost-based laboratory payments increase CAH payments

by roughly $100,000 per CAH. 

Net increase in Medicare payments Converting

hospitals reported over $3 million per hospital in costbased Medicare payments in 2003, which is roughly

$850,000 more per hospital than CAHs would have

received if payments had risen at the same rate as that of

the comparison hospitals. The $850,000 consists of the

estimated $100,000 in additional laboratory payments 

plus the $750,000 figure representing above-average

growth in inpatient, outpatient, and post-acute 

(swing-bed) payments. 

The difference in PPS payment rates and cost-based

payment rates How much of the $850,000 represents 

an increase in the payment rate, and how much represents

an above-average increase in patient volume? To answer

this question, we used patient-level claims data to model

the payments that hospitals would have received under

PPS in 2003 and compared those payments with the

payments that CAHs actually received under cost-based

reimbursement in 2003. We modeled outpatient payments

by calculating ambulatory payment classification (APC)

and hold-harmless payments based on Medicare claims

and cost report data submitted by the hospitals. The

difference between CAH payment rates and PPS 

payment rates provides a rough estimate of increased

Medicare spending. In addition to modeling outpatient

PPS payments, we modeled inpatient payments and

swing-bed payments. Inpatient payments were modeled

using the hospitals’ 2003 case mix index derived from

claims data using a 2003 diagnosis related group (DRG)

grouper and any special payment status the hospital had,

such as sole community hospital status prior to converting

to CAH status. We modeled PPS swing-bed payments

using the per diem rate received by the comparison 

group hospitals. 

We found that roughly all of the $850,000 represented

increased payment rates to CAHs rather than volume

increases.5 While CAHs increased their volume of

outpatient services and post-acute days following

conversion, these increases were roughly offset by

decreases in inpatient volume.6 Averaging across 

inpatient and outpatient service lines, volume growth

appears to be about equal in the two hospital groups 

from 1998 to 2003.

If the difference between CAH payments and PPS

payment rates per hospital was roughly $850,000 in 

2003, what will the difference be in 2006? To answer 

this question, we needed to make four adjustments to 

the $850,000 figure. First, we adjusted for the increases 

to PPS payment rates that were enacted as part of the

MMA, including increases in disproportionate share

payments, a lower labor share for hospitals with a belowaverage wage index, and a low-volume adjustment for

isolated rural hospitals that will be in effect in 2006.

Second, we accounted for the fact that CAHs will receive

101 percent of Medicare costs in 2006 rather than the 100

percent of costs received in 2003. Third, we modeled PPS

payments with the hold-harmless provision extended and 

a second time assuming the hold harmless is allowed to

expire prior to 2006. Fourth, we examined a range of

potential cost increases at CAHs.

We found that if CAHs can restrain their cost growth to 

a level equal to increases in PPS payment rates and if the

outpatient hold-harmless provision is extended, the net

difference between CAH payment rates and PPS payment

rates would grow from roughly $850,000 in 2003 to

slightly below $1 million per CAH in 2006. However, if

Medicare payments to CAHs continue to rise at historical

rates or if the hold-harmless provision is allowed to expire,

the difference between CAH payments and PPS payments

would rise to over $1 million per year in 2006. Given the

range of potential differences between CAH payment rates

and PPS payment rates, we estimate that 2006 payments

per CAH will be roughly $1 million higher under costbased reimbursement than they would have been under

PPS payment rates. 

The hospital doors stay open

One goal of the CAH program is to preserve access to care

in isolated areas by improving the financial condition of

isolated hospitals and preventing closures. The program

has accomplished that mission. By converting to CAH

status, converting hospitals have dramatically increased

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 165
their Medicare payments and improved their all-payer

profit margins from –1.2 percent in 1998 to 2.2 percent in

2003.7 This increase can be compared to the comparison

hospitals’ decline in all-payer margins from 2.2 percent in

1998 to –0.2 percent in 2003. As CAHs improved their

profitability, CAH closures almost ceased. CMS reported

that 15 CAHs closed from 1999 through 2003, and we

have identified one additional closure in 2004. The

hospital that closed in 2004 was approximately six miles

away from two competing hospitals. A for-profit

corporation is considering reopening the closed CAH.8

Many of the CAHs that are helped by the program are

critical for beneficiaries’ access to care. Some are in

isolated areas of the West; others are located on islands

(e.g., Martha’s Vineyard; Kodiak, Alaska). In these

isolated areas, the CAH may serve as the only source of

care—not only for local citizens but also for individuals

visiting the area or driving through on local highways.

About 20 percent of CAHs (172 of the approximately 939)

for which we have data are located more than 35 road

miles from the closest hospital.

Why did some small hospitals choose

not to convert?

In most cases, hospitals do not convert to CAH status for

one of two reasons: 

• They do not want to be limited to 25 acute-care beds. 

• They expect their Medicare PPS payment rates to be

higher than their reported costs under CAH cost

accounting. 

Hospitals with above-average Medicare PPS payment

rates are less likely to convert. The comparison hospitals

received an average of $298 more in payments per

discharge in 1998 than converters ($4,166 versus 

$3,868, Table 7-2, p. 164). Payments differ in part 

because comparison hospitals were more likely to be 

Sole Community Hospitals and more likely to receive

significant disproportionate share (DSH) payments. Sole

Community Hospitals receive inpatient payment rates

based on their historical costs when these cost-based

payments exceed current payment rates. (DSH payments

go to PPS hospitals with high shares of Medicaid and lowincome Medicare patients.) Hospitals that did not convert

received an average of $113,000 in DSH payments in

2003; they would have lost these payments if they had

converted. 

Hospitals with below-average costs are also less likely to

convert. After adjusting for case mix and wage levels,

comparison hospitals tended to have lower costs per

discharge ($4,013 versus $4,429 for CAHs in 1998). 

Changes in service offerings follow

national trends and financial incentives

Following conversions, CAHs exhibited a change in their

service mix and in their patient mix. Services shifted from

acute inpatient services to post-acute care and outpatient

166 Critical access hos p itals

Changes in service volumes 

per hospital following 

conversion to CAH status

1998 2003 Change

Total acute discharges

Converters (n=498) 575 499 –76*

Comparison group (n=551) 1,097 1,121 24*

Medicare acute discharges

CAH converters 320 288 –32*

Comparison group 568 586 18*

Medicare acute and 

swing-bed days

Converters’ Medicare acute days 1,229 939 –290*

Comparison Medicare acute days 2,368 2,209 –159*

Converters’ swing days 461 651 190*

Comparison swing days 537 461 –76*

Medicaid acute days

Converters’ Medicaid acute days 159 127 –32*

Comparison Medicaid acute days 401 427 26*

Total acute and swing-bed

days (all payers)

Converters 2,764 2,439 –325

Comparison group 4,563 4,314 –249

Medicare percentage of 

all days (acute and swing-bed)

Converters 61% 65% 4%*

Comparison group 62% 62% 0%*

Note: CAH (critical access hospital). Values presented are unweighted means. 

An evaluation of medians found similar changes over time and similar 

differences between CAHs and comparison hospitals.

* Indicates changes are significant using a p<.01 criterion and a standard

t-test.

Source: MedPAC analysis of Medicare Cost Report file from CMS.

TABLE

7-3
services. The hospitals’ inpatient payer mix shifted 

toward post-acute Medicare patients and slightly away

from acute Medicare and Medicaid patients (Table 7-3).

The increased payment rates for post-acute services in

swing beds may have contributed to the decision by an

additional 10 percent of CAHs to initiate swing-bed

services (Table 7-4). 

In contrast with swing beds, the profitability of operating

home health and hospital-based SNFs is expected to

decline slightly following conversion to CAH status.

Home health and SNF profitability decline slightly

because Medicare pays for these types of care on a

prospective basis. Retaining these services causes some

hospital overhead to be allocated to these services,

resulting in less hospital overhead eligible for cost-based

reimbursement. Cost-based reimbursement can slightly

distort the decision to close a home health agency or a

SNF by reducing the profitability of the services due to the

allocation of overhead to these services. CAHs were only

slightly more likely to close their SNFs (4 percent versus 

3 percent) and their home health agencies (11 percent

versus 9 percent) than comparison hospitals (Table 7-4).

The differences are not statistically significant, suggesting

that the small shift in incentives is not having a large effect

on decisions to close services. 

The Federal Office of Rural Health Policy has funded a

multiyear study by a team of academic researchers to track

conversions to CAH status as well as CAHs’ activities and

successes. The Flex Tracking Team found that between

2002 and 2004, 40 percent of CAHs significantly

expanded radiology services and 20 percent expanded

laboratory services (Casey and Klingner 2004). Nineteen

percent of CAHs expanded their rehabilitation services

and 12 percent expanded their emergency services. In

contrast, 6 percent of CAHs dropped their obstetric

services. 

Distribution of payments, by distance 

to other hospitals

Although the CAH program has helped preserve access to

emergency and inpatient care in isolated areas, it may not

have accomplished this goal in an efficient manner. In

some cases, Medicare pays cost-based reimbursement to

CAHs that are not critical for patients’ access to care. 

In our sample of 623 CAHs (which includes hospitals 

with partial-year cost reports), 15 percent of cost-based

payments ($289 million) went to providers that were

located more than 35 miles from another provider, and 

17 percent of payments ($320 million) went to hospitals

that were located within 15 miles of another provider

(Figure 7-3, p. 168). The remainder of the $1.9 billion 

in payments went to hospitals that were located 15 to 

35 miles from another provider. 

Consultants who work with CAHs have noted a flurry 

of activity among hospitals that are deciding whether to

convert to CAH status before the states lose their ability 

to declare necessary providers on January 1, 2006. Based

on these conversations and an examination of cost-report

data, we estimate that roughly 1,300 CAHs will exist by

the start of 2006. Given recent cost growth trends and the

projected number of CAHs, we expect Medicare’s costbased payments to CAHs to total roughly $5 billion in

2006. We estimate that this $5 billion in payments will

represent between 3 and 4 percent of all Medicare

inpatient and outpatient payments to hospitals in 2006. 

We expect the $5 billion in cost-based payments to be

roughly $1.3 billion above PPS payment rates for 

those services. 

Will CAH costs continue to grow rapidly? 

The PPS was implemented in the early 1980s to increase

hospitals’ incentive to control costs. Now that CAHs 

have reverted back to cost-based reimbursement, there is 

a concern that CAHs will have a reduced incentive to

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 167

Changes in service offerings 

1998 2003 Change

Swing-bed services 

are offered

Converters 85% 95% 10%*

Comparison group 74 77 3*

SNF services are in 

a distinct-part unit

Converters 32 28 –4

Comparison group 26 23 –3

Home health agency 

services are offered

Converters 49 38 –11

Comparison group 56 47 –9

Note: SNF (skilled nursing facility). 

* Indicates changes are significant using a p<.01 criterion and a standard

t-test.

Source: MedPAC analysis of Medicare Cost Report file from CMS.

TABLE

7-4
control costs. Although cost-based reimbursement does

reduce hospitals’ incentive to control costs, it does not

eliminate that incentive. Three important points frame our

thinking about CAHs’ incentives to cost control costs: 

• All hospitals have some incentive to control costs.

• The incentive is weaker under cost-based

reimbursement.

• Factors other than cost-based reimbursement affect 

the hospitals’ incentive to control costs. 

Non-Medicare patients represent 35 percent of CAHs’

inpatient days, and CAHs need to keep their costs below 

the rates they receive from private payers to remain

profitable. Technically, CAHs need to keep their costs per

unit of service on all non-Medicare patients (including

indigent patients) lower than their income per unit 

of service, including nonoperating income such as

government support, investment income, and charitable

contributions. Although the need to make money on

private-payer patients gives CAHs some incentive to

control costs, CAHs can increase spending more easily than

similar PPS hospitals can, all else being equal. When a PPS

hospital purchases additional labor or equipment, it must

pay for those inputs with cash flow from existing sources 

or through increased patient volume. In contrast, when a

CAH purchases additional labor or equipment, its Medicare

payment per unit of service increases (assuming that

volume does not change). For example, assume Medicare

patients account for 50 percent of a CAH’s charges. If 

that CAH hires a full-time pharmacist for a total cost of

$100,000 per year, the hospital must absorb $50,000 of 

the cost, but increased Medicare reimbursements will 

pay for the remaining $50,000. The effective price of 

the pharmacist drops from $100,000 to $50,000. If the

employee’s value to the community exceeds 50 percent 

of his or her cost, the hospital would hire that individual. 

So why do some CAHs choose not to hire full-time

pharmacists? Some CAH administrators may feel that they

cannot afford the 50 percent of the cost that Medicare does

not cover. Factors such as uncompensated care costs can

place pressure on hospitals to control costs, making the

hospitals more reluctant to make expenditures with a

negative return on investment. In summary, cost-based

reimbursement reduces hospitals’ incentive to control

costs, but it does not eliminate that incentive. 

Costs per unit of service grow at CAHs 

To test for differences in cost growth between CAHs and

our comparison group of similar small hospitals, we

examined costs per inpatient day. We focus on inpatient

days because this unit of output covers both Medicare

acute-care days and post-acute (swing-bed) days. We have

to combine acute-care and post-acute costs because the

cost accounting rules for allocating costs between the two

categories change when hospitals convert to CAH status. 

From 1998 to 2003, costs at converting hospitals rose 

by an average of $461 per day, from $869 to $1,330 per

day (a 53 percent increase) compared to a $318 per day

increase (37 percent) for the comparison group (Figure 

7-4). This measure should be viewed with caution for

three reasons. First, this measure is influenced by changes

in total patient days and the ratio of post-acute days to

acute days from 1998 to 2003. As we noted above, CAHs

had a larger reduction in total days and a shift toward 

post-acute swing-bed patients. CAHs’ reduction in total

inpatient days will push costs per day upward, while the

shift toward post-acute days may slightly push costs per

day downward. Second, this cost increase may be a one168 Critical access hos p itals

Note: CAH (critical access hospital).

Source: MedPAC analysis of Medicare Cost Report file from CMS.

20%

25.1–35.0 miles

15%

35+ miles

17%

1–15 miles

48%

15.1–25.0 miles

CAH payments, by distance 

from the nearest hospital

FIGURE

7-3
time phenomenon associated with the conversion to 

CAH status. For example, if a hospital closes its SNF 

and home health agency, overhead costs may be allocated

back to inpatient and outpatient services—therefore, the

shift upward in costs may be a one-time event. Third, we

cannot be sure about causation. Hospitals that experienced

(or expect to experience) an increase in costs are more

likely to convert because cost-based reimbursement is

more advantageous for high-cost hospitals. Causation 

is likely flowing both ways: Cost growth can drive

conversion and conversion can drive cost growth. 

When we looked at cost growth of CAHs that had

converted by 2001, we found that older CAHs actually

reported lower cost growth per inpatient day from 2002 

to 2003. These older CAHs showed an increase in costs

per inpatient day of 7 percent ($84) from 2002 to 2003,

while the comparison hospitals reported cost increases of 

9 percent ($101) per day. The lower cost growth per day 

at CAHs could partially reflect the steady increase in 

post-acute Medicare days without an increase in Medicare

acute discharges. The lower cost growth could also reflect

a moderation in cost growth at CAHs following an initial

jump in costs associated with conversion to CAH status. 

After conversion, Medicare payments to

CAHs continue to grow

To get an idea of how fast payments will continue to 

grow in years after conversion has been completed, we

examined changes in payments to CAHs that converted 

by 2001. We found that Medicare payments for inpatient,

outpatient, and post-acute services at CAHs increased by

16 percent from 2001 to 2002 and by 12 percent from

2002 to 2003—compared with 4 percent and 1 percent,

respectively, for hospitals in the comparison group. The

payment increases result from increases in costs and

increases in the volume of services at CAHs. 

Is quality of care at low-volume rural

hospitals comparable to that of higher

volume rural hospitals?

The CAH program helps small hospitals remain

financially viable, even when they are located in close

proximity to other small hospitals. A key policy issue is

whether patients are better served by two small hospitals

located in close proximity to one another or by one

merged hospital. On the one hand, low-volume hospitals

have limited resources. For example, a recent survey

found that most CAHs do not employ a full-time

pharmacist; 40 percent have a pharmacist on site for 10 

or fewer hours per week (Casey et al. 2004). A lack of

resources and a lack of experience seeing patients with

similar conditions could affect outcomes at low-volume

hospitals. On the other hand, patients at low-volume

hospitals may receive more personal attention. The

combination of less sophisticated resources and more

personalized attention may affect outcomes differently,

depending on the type of services that a hospital provides. 

We have limited information on the quality of care in lowvolume rural hospitals. The Institute of Medicine (IOM)

notes a general absence of studies on patient safety in rural

settings (IOM 2005). The Agency for Healthcare Research

and Quality (AHRQ) reports patient safety indicator (PSI)

rates for all-payer discharges in national, metropolitan, and

micropolitan areas; however, it does not report PSI

measures at small rural hospitals (AHRQ 2004). Romano

and colleagues studied all-payer data for 1.1 million

hospitalizations in 14 states in 2000. They found that rural

hospitals reported fewer patient safety problems on 12 of

19 PSIs than urban nonteaching hospitals (Romano et al.

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 169

Note: CAH (critical access hospital). Days includes both acute and post-acute days.

Source: MedPAC analysis of Medicare Cost Report file from CMS. Costs per d

a

y

$1,400

1,000

1,200

800

600

400

200

0

1998 2003

CAH converters Comparison hospitals

CAH costs per inpatient day 

rose faster than those of 

comparison hospitals

FIGURE

7-4
2003). Coburn and colleagues compared reported PSI

rates for rural hospitals by size. Rural hospitals with fewer

than 50 beds reported lower rates of postoperative hip

fracture and postoperative hemorrhage or hematoma

compared with rural hospitals with 50 to 99 beds. The

hospitals with under 50 beds also reported lower rates of

iatrogenic pneumothorax, infection due to medical care,

and postoperative hemorrhage or hematoma, compared

with rural hospitals with 100 or more beds (Coburn et al.

2004). This limited literature suggests that the smaller

hospitals report fewer patient safety problems.

MedPAC presented information on hospitals’ patient

safety indicators and risk-adjusted mortality in our last two

March reports (MedPAC 2004, MedPAC 2005). Due to

the small number of discharges at CAHs, we limited our

examination to the five most common patient safety issues

at rural hospitals and the five DRGs with the largest

number of deaths in rural hospitals. The small number of

discharges at each individual CAH prevented us from

accurately commenting on the quality of individual CAHs

or even commenting on the variance in quality across

CAHs. We were limited to examining the average quality

of care at different categories of hospitals. We compared

small CAHs (500 or fewer discharges per year), larger

CAHs (more than 500 discharges per year), our list of 551

potential CAHs (our comparison hospitals), and all other

rural hospitals. We split CAHs into two categories—

hospitals with more than 500 discharges and hospitals 

with fewer than 500 discharges—because prior research

has indicated that the smaller CAHs are less likely to be

accredited by the Joint Commission on Accreditation 

of Healthcare Organizations and less likely to employ 

a pharmacist for 40 or more hours per week 

(Casey et al. 2004). 

We examined risk-adjusted rates of patient safety

indicators for the most common adverse events in rural

hospitals in 2003 (Figure 7-5). We risk adjust rates for

age, sex, modified DRG, and comorbidity using AHRQ’s

methods (AHRQ, 2005). Although small CAHs reported

higher mortality in low-mortality DRGs than other 

rural hospitals, these small CAHs (with 500 or fewer

discharges) reported better rates than larger hospitals 

170 Critical access hos p itals

Patient-safety scores, other than death in low-mortality DRGs,

are better in smaller rural hospitals

FIGURE

7-5

Note: DRG (diagnosis related group), DVT (deep vein thrombosis), CAH (critical access hospital). Rate is risk adjusted per 10,000 eligible cases by hospital size 

 using 2003 data. Differences between rates for CAHs and rural hospitals with more than 1,900 discharges are statistically significant using a p<.5 criterion.

Source: MedPAC analysis of 100 percent MedPAR data using Agency for Healthcare Research and Quality indicators and methods.

R

ate per 10,000 eligible c

ases

250

200

150

100

50

0

Patient-safety indicators

CAHs with under

501 discharges

CAHs with 501 to

1,900 discharges

Rural hospitals with 

over 1,900 discharges

Decubitus ulcer Post-operative pulmonary 

embolism or DVT

Accidental puncture

or laceration

Death in low-mortality

DRGs

Potential CAHs with up

to 1,900 discharges
for failure to rescue, accidental puncture or laceration,

postoperative pulmonary embolism or deep vein

thrombosis, and decubitus ulcer. 

The limited literature on risk-adjusted mortality at rural

hospitals is dated, reports mixed findings, and fails to

separately examine hospitals as small as CAHs (Schlenker

et al. 1996; Keeler et al. 1992). Our analysis of riskadjusted mortality may be the first national study that

compares risk-adjusted mortality in hospitals with 25 or

fewer beds to that of other rural hospitals. We examined

all Medicare inpatient claims (the 100 percent MedPAR

file) and risk-adjusted rates for age, sex, and severity 

of patients’ conditions based on all patient refined

diagnosis related groups (APR–DRGs). Smaller CAHs

reported higher risk-adjusted 30-day mortality rates than

larger CAHs, potential CAHs, and all rural hospitals 

for congestive heart failure, stroke, acute myocardial

infarction (AMI), and gastrointestinal hemorrhage. 

Other than for pneumonia, the 30-day risk-adjusted

mortality rates generally declined as hospital volume

increased (Figure 7-6). We examined the risk of death for

the 30 days following admission to control for the fact that

CAHs may be more likely to transfer patients that develop

complications and need more intensive services. Studies

examining in-hospital mortality (as opposed to 30-day

mortality) or that focus on non-Medicare patients may

yield different findings. 

Why do patient safety measures look better at smaller

hospitals and risk-adjusted mortality measures look

worse? One possibility is that small hospitals perform 

well with some aspects of quality and not as well with

other aspects of quality. It is also possible that small

hospitals do not fully code the complications that patients

experience. Once Medicare pays a hospital based on costs,

that hospital may lack an incentive to code complications

that do not affect charges and payments. When hospitals

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 171

Mortality rates are higher in smaller rural hospitals

FIGURE

7-6

Note: AMI (acute myocardial infarction), GI (gastrointestinal), CAH (critical access hospital). The total number of eligible cases at CAHs ranges from 1,946 for AMI to 17,180 

 for pneumonia. The number of eligible cases at potential CAHs ranges from 4,739 for AMI to 35,645 for pneumonia. Rate is risk adjusted per 10,000 eligible cases by 

 hospital size using 2003 data. Differences between rates for CAHs and rural hospitals with more than 1,900 discharges are statistically significant using a p<.5 criterion.

Source: MedPAC analysis of 100 percent MedPAR data using Agency for Healthcare Research and Quality indicators and methods.

R

ate per 10,000 eligible c

ases

2,500

3,000

500

1,000

1,500

2,000

0

Inpatient condition

CAHs with under 

501 discharges

CAHs with 501 to

1,900 discharges

Rural hospitals with 

over 1,900 discharges

Congestive

heart failure

Stroke AMI GI hemorrhage Pneumonia

Potential CAHs with up

to 1,900 discharges
code poorly, they may not report complications that in 

turn make their patient mix look less sick and increase

their risk-adjusted mortality. To gain some insight into

whether poor coding and hence poor risk adjustment is

driving higher risk-adjusted mortality rates at smaller

hospitals, we also examined 30-day mortality without 

risk adjustment. The raw mortality data tell a similar 

story. Other than for pneumonia, unadjusted mortality

tends to fall as patient volume increases. 

Without reviewing the patients’ charts, we will not know

whether this higher mortality reflects poorer quality of

care at CAHs, or if the CAHs have patients with a higher

risk of mortality and that risk is not picked up in our

administrative data. It is possible that patients with a high

risk of mortality—due to factors not detected by our riskadjustment model—might choose the local CAH over 

a distant hospital if they thought they were too ill to be

assisted by a larger hospital. In other words, CAHs may

attract Medicare beneficiaries who expect to die if the

patients see the CAH as a more comforting environment

than a larger hospital. CAHs may thus have a higher

quality of care than is indicated purely by the mortality

statistics shown in Figure 7-6 (p. 171). 

In our June 2001 report on Medicare issues in rural areas,

we noted that peer review organizations—now known 

as quality improvement organizations (QIOs)—faced

incentives to target quality improvement efforts to large

and usually urban providers. We recommended that the

Secretary require peer review organizations to work with

more rural providers when carrying out their quality

improvement activities (MedPAC 2001). In the eighth

scope of work for the QIOs—which begins in 2005—the

Secretary requires that QIOs recruit CAHs to participate 

in reporting 13 quality improvement measures specified

for CAHs. The QIOs will be evaluated based on CAH

reporting of the CAH quality measures and CAH conduct

of local quality improvement projects (CMS 2005). This

changes the incentives faced by QIOs and may lead to

increased efforts to measure and improve the quality of

care in CAHs. 

One tool for monitoring quality of care at CAHs that is

currently missing is the Minimum Data Set (MDS) patient

assessment instrument for post-acute patients. While the

MDS is an imperfect instrument, the Secretary could

consider requiring CAHs to assess patients using the 

MDS or developing an alternative assessment instrument

that could be used for post-acute patients in SNFs and

swing beds.

MMA changes to the CAH program 

Now we turn to looking at a series of changes in the MMA

that affected CAHs. We are often limited to projecting 

the effects of these MMA changes, because some of the

changes have not yet become effective and we do not yet

have 2004 financial data from hospitals. 

States lose their ability to declare 

new “necessary providers”

The most important recent change to the CAH program 

is the elimination of states’ ability to declare additional

hospitals “necessary providers” starting in 2006. As a

result, the CAH program will essentially cease to add

additional hospitals at the start of 2006. Almost all

hospitals that would meet the criteria of being 15 miles 

by secondary road and 35 miles by primary road have

already converted to CAH status. The Congress

grandfathered existing CAHs into the program.

How will this 2006 change affect Medicare beneficiaries?

Because most hospitals have already converted, the 

impact will be limited. However, a few hospitals

may be forced to close or merge with neighboring

facilities when their patient volume declines, if they 

do not meet the distance criteria for the CAH program.

Closures can result in increased travel times for patients

and increased volumes at the remaining hospitals in the

market. The net effect on patients is unclear. Although 

the general belief is that shorter travel times will improve

outcomes, the magnitude of that travel-time effect is not

clear from the limited literature on the topic (Lerner et al.

2003). There is also the question of whether hospital

consolidation will improve quality. Although patient

mortality is lower in larger hospitals, it is not clear that 

the AHRQ risk-adjustment model adequately adjusts for

the health status of patients who choose to go to very 

small hospitals. Given that the law will affect very few

existing hospitals and that each closure is expected to have

a limited effect on patient travel times, this new provision

of the MMA should have a small impact on Medicare

beneficiaries. 

There is a question of whether Congress went far enough

to restore the focus of the CAH program on isolated

hospitals. If having two neighboring providers is not

clearly better than having one provider with higher

volumes, then it may not be justified to continue providing

cost-based payments to the two providers when they are

172 Critical access hos p itals
within 15 miles from one another. If all CAHs were

required to be 15 miles from another provider to maintain

their necessary provider status, neighboring low-volume

hospitals would face financial pressure to consolidate. 

It may be difficult to overcome local political tensions

between two communities and merge hospitals, but the

mergers could result in having a higher volume facility

with more resources. 

There is also a concern that Medicare will have roughly

1,300 hospitals that receive higher payment rates than PPS

hospitals and SNFs that compete with them. The PPS

hospitals may feel they should receive the same payment

rates as a CAH if they compete in the same market for

employees, physician loyalties, and patients. The problem

of a nonlevel playing field exists primarily because CAHs

are allowed to be in close proximity to other hospitals. 

Limit on acute patients increases 

from 15 to 25

Prior to the MMA, CAHs could use only 15 of their 25

beds for acute care. When CAHs operated under this

constraint in 2003, the largest number of discharges at 

a CAH was 1,900. Will this legislative change result 

in significantly more conversions to CAH status or

significantly more discharges at existing CAHs? 

Even with the option of using all 25 beds for acute care, 

it will be difficult for a hospital to have significantly more

than 1,900 discharges. A hospital with 2,000 discharges

would have an 88 percent occupancy rate if its patients

stayed four days on average and a 66 percent occupancy

rate if its patients stayed three days (acute plus post-acute).

It may be difficult for CAHs to reduce patients’ lengths 

of stay (acute plus post-acute) below four days. After

examining Medicare margins for hospitals with close to

2,000 discharges, we believe that allowing CAHs to have

up to 25 acute-care patients will generate less than 100

additional conversions to CAH status. 

Will admissions per CAH and the cost (to Medicare) of

CAH conversions increase? Hospitals that downsized 

to become CAHs may slightly increase their inpatient

admissions. However, the payment rates for acute

inpatient care at CAHs tend to be only slightly higher 

than payment rates at PPS hospitals. It is the payment 

rates for outpatient and post-acute services at CAHs that

are significantly higher than PPS payment rates. Raising

the limit on acute patients from 15 to 25 does not affect

the number of post-acute patients or the volume of

outpatient services a CAH can provide. Therefore, we 

do not expect this provision to have a major effect on the

average cost (to Medicare) of each CAH conversion. The

average conversion is still expected to result in Medicare

payments that are roughly $1 million more than PPS rates

per hospital in 2006. 

CAHs can have distinct-part psychiatric

and rehabilitation units with up to 

10 beds

Prior to the passage of the MMA, the Government

Accountability Office (GAO) studied the potential 

impact of allowing CAHs to have distinct-part units. 

The GAO suggested that the provision may result in 

an additional 47 conversions. As of January 1, 2005 

(12 months after Congress passed the MMA), 15 CAHs

have distinct-part psychiatric units and 4 CAHs have

distinct-part rehabilitation units. Among our list of 551

comparison hospitals, 74 had distinct-part psychiatric or

rehabilitation units. Given our review of the data, the

GAO’s prediction of roughly 50 additional conversions

due to allowing distinct-part units appears to be correct. 

The shortage of mental health professionals in rural 

areas is well documented (IOM 2005). The distinct-part

psychiatric units in CAHs may allow some mental 

health patients to stay closer to home and may help in 

the retention of mental health professionals in rural 

areas. Little research exists regarding how well the 

mental health services provided by these distinct-part 

units match rural communities’ needs. The Maine Rural 

Health Research Center is planning to conduct a study 

of mental health services at small rural hospitals in 2006

and should be able to shed some light on the degree to

which the services provided at these distinct-part units

meet the needs of rural communities. 

The cost of this MMA provision has been modest.

Medicare pays prospective payment rates for services

provided in distinct-part units, and fewer than 50 CAHs

are expected to have distinct-part units. 

Payments rise to 101 percent of costs 

The MMA increased payments to CAHs from 100 percent

of allowable costs to 101 percent of allowable costs. The

average CAH allocated roughly $3 million of costs to

cost-based Medicare services in 2003. The net impact of

allowing a 1 percent profit margin is roughly $30,000 per

hospital in 2003. By the time conversions cease in 2006,

we expect that average costs per CAH will have grown by

slightly more than 12 percent annually due to historical

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 173
rates of growth in payments to CAHs and larger CAHs

entering the program. In 2006, we expect that a 1 percent

increase in Medicare payments will be roughly $40,000 to

$50,000 per hospital, equivalent to between $52 million

and $65 million total for the projected 1,300 CAHs. 

Summary of findings

The CAH program has successfully helped low-volume

hospitals remain financially viable. In 2003, Medicare

payments grew by roughly $850,000 per CAH more than

they would have if payments had grown at the rate of

competing hospitals. Higher Medicare revenues led to

improved profit margins, and CAH closures have almost

ceased. 

Although it is important to have a program that provides

isolated rural hospitals with enough funding to cover the

cost of efficiently delivering high-quality care, there are

several drawbacks to the current system of cost-based

Medicare payments:

• Cost-based payments can distort the financial

incentives to close services and reduce hospitals’

incentives to control costs.

• Cost-based payments can differ from the prospective

payment rates Medicare pays to nearby competitors

for similar or identical services. For example, the

current system pays much higher rates for post-acute

care in CAHs than it does for post-acute care in

competing SNFs. 

• Some low-volume hospitals are receiving costbased reimbursement when they are not critical 

for beneficiaries’ access to care. 

These three troubling aspects of the CAH program need

further research. MedPAC will continue to track cost

growth at CAHs to see whether cost-based reimbursement

leads to above-average cost growth.

There may also be a need for research that evaluates

whether CAHs are gaining market share in services where

their payment rates are substantially above the rates paid

to competitors. For example, if CAHs are gaining market

share in post-acute services due to being paid significantly

higher rates than SNFs, paying CAHs a fixed payment rate

for post-acute care that is closer to the rate paid to their

competitors might be appropriate. In the case of hospitals,

there is a need to evaluate whether paying CAHs higher

payment rates than competing PPS hospitals creates an

unlevel playing field when hospitals compete for

employees, physician loyalties, and patients. 

In addition, given the CAH program’s ability to preserve

hospitals with low patient volumes, there is a need for

further research that examines whether Medicare

beneficiaries are better served by (a) having two lowvolume hospitals in close proximity to each other or 

(b) having those neighboring hospitals merge into one

larger hospital. Policy makers may wish to balance the

desire to keep care local with the goals of improving the

quality of care and restraining cost growth. 

174 Critical access hos p itals

Section 433 of the MMA 

(a) In General.—The Medicare Payment Advisory

Commission shall conduct a study of the impact of

sections 401 through 406, 411, 416, and 505. The

Commission shall analyze the effect on total

payments, growth in costs, capital spending, and

such other payment effects under those sections.

(b) Reports.—

(1) Interim Report. —Not later than 18 months

after the date of the enactment of the Act, the

Commission shall submit to Congress an interim

report on the matters studied under subsection (a)

with respect only to changes in the critical access

hospital provisions under section 405.

(2) Final Report.—Not later than 3 years after the

date of enactment of this Act, the Commission

shall submit to Congress a final report on all

matters studied under subsection (a). Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 175

1 In the case of certain DRGs, Medicare pays a reduced PPS

payment rate if the patient is discharged to a SNF for postacute care and had an unusually short hospital stay.

However, Medicare does not reduce payments if the patient

is discharged to a CAH’s swing bed (Schoenman 2004). 

2 The Rural Hospital Flexibility Grant program gives states

grants that can be used for the following purposes: to assist

rural hospitals in assessing conversion to Critical Access

Hospital status, network development, and integration of

emergency medical services. The program is authorized

under section 1820 of the Social Security Act. 

3 CAHs also benefit from being paid 115 percent of the

physician fee schedule if physicians assign their billing rights

to the CAH. This benefit was not included in our estimate of

the benefits of conversion to CAH status.

4 CAH conversion is not a random event. Hospitals choose to

convert. Therefore, any comparison group will differ from

converting hospitals. Almost all of the smallest rural

hospitals (fewer than 500 discharges) have chosen to convert

to CAH status. Therefore, our comparison hospitals tend to

be the size of larger CAHs (500 to 1,900 discharges). While

all CAHs had 1,900 or fewer discharges after conversion, it

should be noted that some hospitals had more than 1,900

discharges prior to conversion, but were willing to downsize

to 25 beds to obtain higher payment rates as a CAH. Some

hospitals have more discharges prior to conversion than they

do after conversion. 

5 The actual difference between cost-based payments and

payment under PPS rates could range anywhere between

$800,000 and $900,000 in 2003. We can only present a

rough estimate ($850,000) of the difference due to our

inability to precisely estimate what outpatient therapy

payments and outpatient hold harmless payments would have

been if the CAHs had been paid fee schedule rates for

therapy services and had reported their outpatient costs using

PPS cost-accounting rules. 

6 Consultants have informed us that the projected benefits of

conversion are usually lower than $850,000 per hospital.

However, most consultants project benefits of conversion

based on preconversion service volumes. We examine the

difference between PPS payments and cost-based payments

using hospitals’ postconversion service volumes. Following

conversion, CAHs have tended to expand their volume of

services in areas where they received substantially higher

payments than neighboring PPS hospitals, specifically

outpatient services and post-acute care in swing beds. 

7 We report all-payer margins because they are not affected by

the changes in Medicare cost accounting rules that occur

when a hospital converts to CAH status. In contrast, overall

Medicare margins are affected by the differences between

CAH cost accounting rules and PPS cost accounting rules. 

8 In our sample of 498 CAHs, 18 are for-profit hospitals.

Endnotes
Agency for Healthcare Research and Quality (AHRQ). 2005.

Guide to patient safety indicators. Washington, DC: AHRQ. 

Agency for Healthcare Research and Quality (AHRQ). 2004.

2004 annual healthcare quality report. Washington, DC: AHRQ. 

American Hospital Association (AHA). 2000 and 2004. 

Hospital statistics: 2000 and 2004 editions. Washington, DC:

AHA. January.

Casey, M., and K. Klingner. [Flex Monitoring Team]. 2004. 

2004 CAH survey: National data. August.

Casey, M., I. Moscovice, and J. Klingner. [Flex Monitoring

Team]. 2004. Critical access hospital patient safety priorities 

and initiatives: Results of the 2004 national CAH survey.

September. 

Centers for Medicare & Medicaid Services, Department of Health

and Human Services. 2005. Request for Proposal (RFP) Number

CMS–05–QIO–1CNAHC. http://www.eps.gov/spg/HHS/HCFA/

AGG/CMS05QIO1CNAHC/Attachments.html. 

Coburn, A.F., M. Wakefield, M. Casey, et al. 2004. Assuring

rural hospital patient safety: What should be the priorities?

Journal of Rural Health 20, no. 4 (Fall): 314–325.

Institute of Medicine. 2005. Quality through collaboration: 

The future of rural health care. Washington, DC: IOM.

Gale, J. State approaches to the certification of necessary

providers in the Rural Hospital Flexibility Program. 2002. 

Portland, ME: Maine Rural Health Research Center, University

of Southern Maine.

Health Care Financing Administration, Centers for Medicare &

Medicaid Services, Department of Health and Human Services.

2001. Exemption of critical access hospital swing beds from

skilled nursing facility prospective payment system. Program

Memorandum Transmittal, no. A–01–09. January 16.

Keeler, E. B., L. V. Rubenstein, and K. L. Kahn. 1992. Hospital

characteristics and quality of care. Journal of the American

Medical Association 268, no. 13 (October 7): 1709–1714.

Lerner, E. B., A. J. Billittier, J. Dorn, et al. 2003. Is total out-ofhospital time a significant predictor of trauma patient mortality?

Academic Emergency Medicine 10, no. 9 (September): 949–954.

Medicare Payment Advisory Commission. 2005. Report to the

Congress: Medicare payment policy. Washington, DC: MedPAC. 

Medicare Payment Advisory Commission. 2004. Report to the

Congress: Medicare payment policy. Washington, DC: MedPAC.

Medicare Payment Advisory Commission. 2001. Report to the

Congress: Medicare in rural America. Washington, DC:

MedPAC. 

Morrill, R., J. Cromarie, and G. Hart. 1999. Metropolitan, urban,

and rural commuting areas: Toward a better depiction of the

United States settlement system. Urban Geography 20: 727–748.

Institute of Medicine. 2005. Quality through collaboration: The

future of rural health. Washington, DC: IOM. 

Romano, P., J. J. Geppert, S. Davies, et al. 2003. A national

profile of patient safety in U.S. hospitals. Health Affairs 22, 

no. 2 (March/April): 154–166.

The Rural Hospital Flexibility Tracking Project. 2003. The Rural

Hospital Flexibility Program: The tracking project third-year

findings. WWAMI Rural Health Research Center. Seattle, WA:

January.

Schlenker, R. E., D. F. Hittle, C. A. Hrincevich, et al. 1996.

Volume/outcome relationships in small rural hospitals. Journal of

Rural Health 12, no. 5 (Fall): 395–409.

Schoenman, J. 2004. Rural implications of Medicare’s post-acute

care transfer payment policy. Bethesda, MD: National Opinion

Research Center. June.

176 Critical access hos p itals

References
Using clinical and cost 

effectiveness in Medicare

CHAPTER 8

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 179

olicymakers are looking for ways to use Medicare’s 

resources more efficiently. One way Medicare has done

so is by using information about the clinical effectiveness

of a service when making coverage decisions and setting

payment rates. MedPAC supports CMS’s recent effort in linking 

coverage with a requirement for collecting clinical effectiveness data. By

contrast, Medicare does not explicitly consider the cost effectiveness of

a service in either the coverage or payment process. Nonetheless, cost 

effectiveness potentially can promote care that is more cost efficient and

higher quality. Before Medicare can routinely use cost effectiveness, policymakers will need to address valid 

concerns about its methods. The Secretary could play an important role in standardizing the methods used in these

analyses. Medicare can begin considering cost effectiveness by collecting this type of information from 

manufacturers when making coverage decisions (when available), sponsoring cost-effectiveness studies, and 

using such studies to prioritize pay-for-performance and disease management initiatives. 

8

In this chapter

• Medicare’s coverage and 

payment processes consider

clinical effectiveness

• Understanding costeffectiveness analysis

• Medicare’s coverage and 

payment processes do not 

explicitly use costeffectiveness analysis

• The future of costeffectiveness analysis

in Medicare

CHAPTER

P

Using clinical and cost

effectiveness in Medicare
Considering evidence about the clinical effectiveness and

cost effectiveness of alternative health services might be

another way to increase the return on society’s investment

in health care. Cost effectiveness evaluates the clinical

effectiveness and resource costs of two or more alternative

services, including drugs, medical devices, surgical and

diagnostic procedures, and medical treatment strategies.

The central function of cost-effectiveness analysis is 

to assess the relative value of alternative services for

improving health. Currently, Medicare does not explicitly

consider a service’s cost effectiveness when making

coverage decisions or setting payment rates. Medicare

does, however, consider a service’s clinical effectiveness

when making coverage decisions and when making

payments for certain services.

The first section of this chapter outlines how Medicare

uses clinical information when making coverage decisions

and setting payment rates. We find that CMS uses an

open, evidence-based process when making coverage

decisions and considers clinical effectiveness information

in the rate-setting process for certain services. MedPAC

supports CMS’s recent effort in linking coverage with a

requirement for prospective data collection.

Next, MedPAC begins to consider the use of costeffectiveness information by Medicare. Cost-effectiveness

analyses can potentially improve Medicare’s ability to

maximize beneficiaries’ health and well-being and might

enable the program to achieve better value for its

expenditures. Medicare cannot use the dollars that it

spends on services that are not cost effective for other

important purposes—purposes such as providing other

health benefits within and outside Medicare. Medicare,

together with other payers and purchasers, is in a strong

position to consider such information because it 

represents the interest of large populations. 

Medicare could begin to consider cost-effectiveness

analysis in the following specific ways: 

• standardizing the methods used to conduct such

studies,

• collecting cost-effectiveness information from

manufacturers and providers in the coverage process

(when available), 

• sponsoring cost-effectiveness studies, 

• providing cost-effectiveness analyses to beneficiaries

and health professionals, and

• using available cost-effectiveness analysis to prioritize

pay-for-performance and disease management

initiatives.

However, before Medicare can routinely begin to use costeffectiveness analysis, policymakers will need to address

valid concerns about the methods that researchers use in

current analyses. Policymakers and other stakeholders 

cite the lack of a common set of techniques in costeffectiveness analysis as one reason for their limited use 

of such a method. The Secretary could play an important

role in advancing the field of cost effectiveness by helping

to standardize the methods in these analyses. In addition,

the Secretary could develop the methods in an open

process similar to the current process of making national

coverage decisions. 

Medicare’s coverage and payment

processes consider clinical effectiveness

Although Medicare’s coverage process does not explicitly

consider cost effectiveness, it does consider value by

assessing the clinical effectiveness of new services.

Medicare also considers clinical effectiveness when

determining payment for new services paid through 

under certain prospective payment systems (PPSs) and 

for some services not paid through PPSs. However, the

Congress recently limited the agency’s use of such

information when paying for certain services furnished 

in the hospital outpatient setting. 

Making coverage decisions and using

clinical effectiveness information

Medicare covers health care services when adequate

evidence shows that these services improve health

outcomes, regardless of the unit or aggregate cost. In

practice, services that are high cost will receive greater

scrutiny than other services (Tunis 2005). 

Historically, CMS based its coverage determinations on

descriptive information as well as scientific and clinical

evidence. A general notice that the agency published in

1999 formalized the evidence-based process for making

coverage decisions and made the process more transparent

and understandable to the public. Using such an evidence180 Using clinical and cost effectiveness in Medicare
based approach, CMS assesses whether a given service is

reasonable and necessary by determining: (1) if it is safe

and effective per the Food and Drug Administration

(FDA) regulatory process; and (2) if adequate evidence

leads CMS to conclude that the service improves net

health outcome. 

CMS may limit coverage to specified circumstances 

based on scientific evidence. For example, in a decision

concerning carotid artery stenting, CMS extended

coverage to patients who were at high risk of stroke 

and complications during surgery. To better ensure that

patients receive care most appropriate for their needs, 

the coverage decision also delineated minimum standards

that facilities must meet to treat high-risk patients—such

as providing necessary imaging equipment, advanced

physiologic monitoring equipment, and emergency

management equipment and systems. 

Recently, CMS is also linking national coverage with

participation in comparative clinical trials and data

registries in order to determine the effectiveness of new

services for Medicare beneficiaries. The agency refers 

to these comparative clinical trials as “coverage with

evidence development” or practical clinical trials.1

CMS collects the data to ensure patient safety, evaluate 

the benefit of the service, and improve physician decision

making. Ultimately, these data should improve the quality

of the available scientific evidence because the current

FDA regulatory process provides some but not all

information needed for CMS to make evidence-based

decisions. These trials can potentially enhance Medicare’s

ability to assess the effectiveness of new services while

providing beneficiaries with access to these services.

Information that CMS derives from these trials may 

enable the agency to refine coverage decisions based 

on high-quality evidence. 

The characteristic features of practical clinical trials are 

that they: (1) select clinically relevant alternative services 

to compare; (2) include a diverse population; (3) recruit

participants from heterogeneous practice settings; and 

(4) collect data on a broad range of health outcomes 

(Tunis et al. 2003). Recent examples of these trials include: 

• FDG-PET (2-deoxy-2- [F-18] fluoro-D-glucose

positron emission tomography) scans for the

diagnosis of patients who have mild cognitive

impairment or shows signs of early dementia.

CMS will collaborate with the National Institute on

Aging, the Agency for Healthcare Research and

Quality (AHRQ), the Alzheimer’s Association,

manufacturers, and other experts to develop a large

practical clinical trial. 

• Percutaneous transluminal angioplasty of the

carotid artery with stenting. CMS will cover this

technology when medical providers furnish it in

accordance with FDA-approved protocols that govern

postapproval studies. 

• Off-label uses of four anticancer drugs: xaliplatin

(Eloxatin®), irinotecan (Camptosar®), bevacizumab

(Avastin®), and cetusimab (Erbitux®). CMS will

cover these drugs for beneficiaries in certain clinical

trials sponsored by the National Cancer Institute. 

What do these services have in common? They are either

new or a new use of an existing service, they are costly,

they have the potential for high use, and current scientific

evidence is inadequate for certain populations of interest.

For example, the four anticancer drugs are costly. One 

of the new drugs to treat colorectal cancer costs about

$30,000 when used with other agents for an eight-week

course of treatment (Schrag 2004). 

Finally, paying for the costs of routine care for patients in

FDA clinical trials—which began in September 2000—

is another way in which Medicare has strengthened its

clinical evidence base. CMS pays the routine costs of care

for patients who enroll in trials that meet certain criteria.2

From the information collected in clinical trials, Medicare

can begin to learn about the effectiveness of new services.

In addition, the MMA authorizes the AHRQ to conduct

and support research studying the outcomes, comparative

clinical effectiveness, and appropriateness of health care

items and services. 

Setting payment rates and use of clinical

effectiveness information

Some of Medicare’s PPSs consider the clinical

effectiveness of new technologies in the rate-setting

process. For example, for a new technology to be eligible

to receive a pass-through payment in the inpatient PPS, 

it must represent an advance in medical technology that

substantially improves (relative to services previously

available) diagnosis or treatment. For new-technology

pass-through payments under the hospital outpatient PPS,

medical devices must meet the same criteria.

For services not covered under PPSs, CMS has set a new

service’s payment rate the same as that of an existing

service after concluding that both services are clinically

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 181
comparable. In 2003, CMS set the payment rate for a 

new service (a biological) at the same rate as that of 

an existing service after concluding that both services

were functionally equivalent. The new service was

darbopoetin alfa (Aranesp®), and the existing service was

erythropoietin (Procrit® and Epogen®). Specifically, the

agency concluded that both products were functionally

equivalent because they used the same biological

mechanism to produce the same clinical result—

stimulation of the bone marrow to produce red blood cells. 

Section 622 of the Medicare Prescription Drug,

Improvement, and Modernization Act of 2003 (MMA)

limits the use of the functional equivalence standard. 

The Congress prohibited the use of this standard for drugs

and biologicals in the hospital outpatient setting. However,

the MMA did not preclude the agency from setting the

payment rate the same for other clinically comparable

services in other settings. Under the “least costly

alternative” policy, Medicare’s contractors (carriers 

and fiscal intermediaries) may deny coverage for the

additional cost of a more expensive service if a clinically

comparable service costs less.3

Carrier policies related to two drugs illustrate how 

this policy works. During the last several years, many

carriers have implemented a least costly alternative for

two drugs used to treat prostate cancer—leuprolide 

acetate (Lupron®) and goserelin acetate (Zoladex®)—

administered in physicians’ offices. Current payment 

for Lupron is $226.66 versus $192.68 for Zoladex.

According to the Office of Inspector General (OIG),

carriers implemented a least costly alternative in 47 of 

57 jurisdictions in 2003 (OIG 2004). Thus, in these

jurisdictions, contractors paid physicians the payment

amount for Zoladex when they furnished Lupron. In some

instances, contractors paid the higher payment amount if

the physician documented why the more costly treatment

option was medically necessary. The OIG recommended

that all carriers apply a least costly alternative for Lupron. 

Understanding cost-effectiveness

analysis

For more than 25 years, researchers have used costeffectiveness analysis as a technique for economic

evaluation in health care. This tool is used by some

commercial health plans and purchasers, most frequently

for understanding the value of new drugs. Many medical

directors believe that cost-effectiveness analysis can and

should play a greater role. Nonetheless, some stakeholders

fear that the explicit use of cost effectiveness by public

and private payers could harm patients’ access to care,

negatively affect the innovation of new services, and lead

to the rationing of care. 

What is cost-effectiveness analysis? 

Cost-effectiveness analysis involves estimating the costs

and health outcomes of a service and its alternatives.

Researchers usually summarize their results in a series of

cost-effectiveness ratios that show the cost of achieving

one unit of health outcome for different kinds of patients

and alternative services.

Cost-effectiveness analysis is closely related to

cost–benefit analysis. Although both types of analyses

consider costs and benefits, the key difference is how

researchers measure benefits. In cost–benefit analysis,

researchers express benefits in monetary terms, whereas

cost-effectiveness analysis presents benefits in terms of

health outcomes. 

Researchers often measure health outcomes in terms 

of years of life gained, cases of a particular disease

prevented, or improvements in functional status.

Researchers also commonly use improvements in 

health-related quality-of-life years as a measure. The

quality-adjusted life year (QALY) is a measure of health

outcome that assigns to each time period a weight (ranging

from 0 to 1) that corresponds to the quality of life during

that period. It is the arithmetic product of life expectancy

and a measure of the quality of the remaining life years.

QALYs provide a common currency to assess the extent

of the benefits that patients gain from a variety of services

in terms of health-related quality of life and survival.

Although use of QALYs in cost-effectiveness analysis is

widespread, some researchers are concerned that these

measures do not adequately reflect societal values 

(Nord et al. 1999).

By providing estimates of outcomes and costs, costeffectiveness analysis shows the tradeoffs involved in

choosing among services. That is, the analysis provides

information about the opportunity cost of each service. 

We can think of the value of services—in terms of their

net costs and net outcomes—as a grid, with four quadrants

showing the impact of services as either increasing or

decreasing health and either increasing or decreasing costs

(Figure 8-1).

182 Using clinical and cost effectiveness in Medicare
Researchers refer to a service that is more effective and

less costly than its alternatives as “dominant.” In Figure 

8-1, dominant services fall into the lower right quadrant

(IV). A service that is more costly and more effective 

than its alternatives falls into the upper right quadrant (II).

Table 8-1 presents the cost-effectiveness ratios of selected

services that beneficiaries use; we present this table for

illustrative purposes only. Among the selected services we

include in the table, influenza vaccination is “dominant.”

The remainder of the services fall into quadrant II—they

improve health but increase costs. The cost-effectiveness

ratios range from less than $10,000 per QALY for beta

blocker after acute myocardial infarction to over $500,000

per QALY for left ventricular assist devices and positron

emission tomography (PET) for Alzheimer’s disease

(Gillick 2004, Neumann 2005a).

How have cost-effectiveness analyses

evolved in health care?

In the 1960s and early 1970s, policymakers applied 

cost-effectiveness analysis to a variety of health issues,

including kidney disease and maternal and child health

programs. Beginning in the 1970s, cost-effectiveness

analyses of health issues began to appear in major medical

journals. Since then, researchers have developed models to

compare costs and outcomes for services ranging from:

• drugs—(e.g., those used in combination antiretroviral

therapy for HIV disease); 

• preventive services—(e.g., vaccination against

pneumoccocal pneumonia); 

• screening—(e.g., for HIV and different types of

cancers and chronic diseases, such as chronic kidney

disease);

• services—(e.g., early hospital discharge after

uncomplicated acute myocardial infarction and

smoking-cessation services); and

• procedures—(e.g., bypass surgery for coronary 

artery disease and lung-volume-reduction surgery 

(Boulware et al. 2003, Eddy 1989, Paltiel et al. 2005,

Willems et al. 1980). 

The number of cost-effectiveness analyses has grown

steadily (Elixhauser 1998). General medical, medical

specialty, public health, and policy journals publish 

more than 100 studies per year (Gold et al. 1996).

Neumann (2005b) reported that about 40 percent of all

published cost-effectiveness studies assess the value of

pharmaceuticals (Neumann 2005b). This investigator

found that fewer studies are published assessing the cost

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 183

Note: This figure shows the impact of services in terms of their net costs and net 

 outcomes as a grid, with four quadrants showing the impact of services as 

 either increasing or decreasing health and either increasing or decreasing costs.

Decreases health Increases health

Decreases 

costs

Increases 

costs

I II

III IV

The impact of services

on outcomes and costs

FIGURE

8-1

Cost effectiveness of selected 

services in the Medicare population

Cost-effectiveness

Technology ratio (2002$/QALY)

Influenza vaccine Cost saving

Beta blocker after acute 

myocardial infarction Under $10,000

Cholesterol management, 

secondary prevention $1,000–$50,000

Dialysis for ESRD $50,000–$100,000

Lung volume reduction surgery $100,000–$300,000

Left ventricular assist devices $500,000+

PET for Alzheimer's disease $500,000+

Note: QALY (quality-adjusted life year), ESRD (end-stage renal disease), 

PET (positron emission tomography). The cost-effectiveness ratio is 

expressed in 2002 dollars spent for each additional year of life at full 

quality gained. 

Source: Gillick 2004, Neumann 2005a.

TABLE

8-1
effectiveness of other types of services, such as surgical

interventions, screening services, and medical and

diagnostic procedures. The availability of efficacy data 

on drugs from FDA clinical trials partly accounts for the

higher proportion of published studies assessing drugs. In

addition, manufacturers’ need to show the value of a new

drug to formulary committees and other purchasers may

also play a role, as discussed below. Manufacturers also

use cost-effectiveness analysis to predict the price that

purchasers will be willing to pay for a new drug

(Neumann 2005b). 

Over the years, pharmaceutical manufacturers have

sponsored an increasing proportion of cost-effectiveness

analyses. Neumann (2005b) estimates that their share

increased from 14 percent between 1976 and 1997 to 20

percent between 1998 and 2001, while government- and

foundation-sponsored studies decreased from 54 percent 

to 43 percent. About one-third of all studies did not report

the funding source during each time period. 

Designing cost-effectiveness analysis 

When measuring the clinical effectiveness, outcomes, and

costs of alternative services, researchers must construct a

conceptual model. Such models range from the simple

(such as decision trees) to the complex (such as Markov

models).4 A cost-effectiveness analysis typically addresses

the following methodological issues: 

• The perspective of the analysis. The findings of a

cost-effectiveness analysis vary depending on the

viewpoint of interest to the researcher—society,

purchaser, insurer, or another party. A costeffectiveness analysis from a societal perspective

includes everyone who is affected by the service; it

also includes all associated health outcomes and costs

(Gold et al. 1996). By contrast, a cost-effectiveness

analysis from an insurer’s perspective would include

only those outcomes and costs that affect that

particular insurer. 

• The sources of clinical effectiveness and outcomes

data. Researchers can use data from numerous

sources, including FDA clinical trials and practical

clinical trials, patients’ medical records, health care

claims submitted to insurers, and health surveys. 

• The method of defining costs. Costs include direct

medical (e.g., cost of medical services), direct

nonmedical (e.g., transportation costs), and indirect

(e.g., value of lost productivity). For example, lost

productivity measures the costs associated with lost 

or impaired ability to work or to engage in leisure

activities, and lost economic productivity due to death. 

• The selection of comparison services. Comparative

groups can include pharmaceutical, medical, and

surgical services, or no treatment. 

• The time horizon. Researchers must choose the period

of time to measure a service’s costs and outcomes.

• The discounting of costs and outcomes. When the

time horizon of cost-effectiveness analyses extends

into the future, researchers must convert future costs

and future health outcomes to their present value. In

doing so, researchers appropriately adjust the costeffectiveness ratios for the different timing of cost and

outcomes. The discount rates that researchers use to

convert health outcomes and costs to a present value

can differ. 

• The uncertainty of the clinical events and costs.

Sensitivity analysis varies the assumptions of the

clinical and cost data.

• The measurement of outcomes. As we mentioned

earlier, researchers measure outcomes in terms of

QALYs, cases of a particular disease prevented, or

improvements made in functional status. 

Recognizing the complexity of cost-effectiveness analysis,

several groups have published guidelines designed to

ensure and improve the quality of such analyses. In 1993,

the Public Health Service convened the U.S. Panel on 

Cost Effectiveness in Health and Medicine to address

methodological concerns about cost effectiveness. The

panel reviewed the state of the health and medicine field

and developed recommendations to improve the quality

and comparability of these types of studies.5 In addition to

this panel, some peer-reviewed journals have also

developed publication standards for cost-effectiveness

studies.6

One study shows that more recently published costeffective analyses are adhering to the guidelines of the

panel (Neumann 2005c). Comparing studies published 

in 1998 to 2001 with those published in 1976 to 1997,

studies improved in almost all categories, including:

clearly presenting the study perspective (73 percent 

versus 52 percent, respectively); discounting both costs

184 Using clinical and cost effectiveness in Medicare
and outcomes (82 percent versus 73 percent, respectively);

and reporting incremental cost-effectiveness ratios 

(69 percent versus 46 percent, respectively). 

Who uses cost-effectiveness analysis? 

The experience of public and private entities regarding

cost-effectiveness analysis varies. Cost-effectiveness

analysis is not explicitly used by Medicare, and is used by

some organizations to develop clinical guidelines and—on

a limited basis—by health plans and purchasers. Other

countries use cost-effectiveness analysis more widely than

the United States. 

Use of cost-effectiveness analysis by public

and nonprofit entities

At least two organizations consider cost-effectiveness

analysis when developing guidelines—the recent

recommendations of the third U.S. Preventive Services

Task Force (USPSTF) and the U.S. Guide to Community

Preventive Services.

7 USPSTF, an independent panel 

of private-sector experts in primary care and prevention,

considered cost-effectiveness studies in its recommendation

concerning screening for abdominal aortic aneurysms,

coronary heart disease, and bacteriuria. The U.S. Guide to

Community Preventive Services examines population-based

health promotion and disease prevention services. This

group considered selected economic evaluations, including

cost-effectiveness analysis, for the following topics:

diabetes, oral health, physical activity, and tobacco. 

The task force used these analyses to make the case that 

the intervention was valuable and should be incorporated

routinely into primary medical care. 

The National Committee for Quality Assurance (NCQA)

has recognized the importance of cost-effectiveness

information. In selecting a measure for a particular 

clinical condition, the committee considers costeffectiveness information. For example, in its State of

Health Care Quality Report, it includes estimates of 

the incremental cost effectiveness of conducting

conventional pap screening every three years, compared

with conducting no pap screening (NCQA 2004). This

effort shows how policymakers can use cost-effectiveness

analysis in prioritizing which measures to use in pay-forperformance programs and how frequently providers

should furnish these services to patients. 

One state—Oregon—experimented with using costeffectiveness analysis to help reform its Medicaid

program. The state attempted to rank different services

based on their cost effectiveness and cover only those

services that fell above a line established by the state’s

budgetary resources. Ultimately, policymakers considered

information on cost effectiveness less formally in the 

plan Oregon eventually adopted because of disputes

surrounding its use. Specifically, stakeholders criticized

the initial priority list that ranked services based on their

cost effectiveness as being counterintuitive, assigning

higher priorities to some services that seemed less

important than other lower ranked services (Eddy 1991). 

Use of cost effectiveness by commercial

health plans and purchasers

Health plans, pharmacy benefit managers (PBMs), and

hospitals have used cost-effectiveness analysis, along with

other types of pharmacoeconomic analysis, for the past

two decades (Neumann 2005b). Pharmacoeconomic data

include cost-effectiveness analysis and other types of

health economic analyses, such as cost–benefit, cost-ofillness, and cost-of-care studies. 

The 1997 Food and Drug Administration Modernization

Act codified rules governing the health economic

information that manufacturers can disseminate to plans

and purchasers. The act permits manufacturers to

disseminate health economic information, provided that

this information directly relates to an approved indication

of a service and results from reliable scientific evidence.

Commercial plans and purchasers frequently consider

evidence about a new service’s cost rather than its cost

effectiveness when making coverage decisions. Cost

information supplements the clinical effectiveness

information that plans use in making these decisions

(Project HOPE 2002). A survey of medical directors 

of 228 managed care plans in 2001 indicates that 

90 percent of the plans consider the cost of a new service

(Garber 2004). The survey results also indicate that: 

• Nearly all plans (93 percent) will cover a more

effective service, even if it is more costly.

• Plans use cost information the most frequently 

(58 percent) to design policies that require the use 

of less costly (but equally effective) services first.

By contrast, plans consider formal cost-effectiveness

analyses to assess new services less frequently. In one

survey, only 40 percent of the plans reported using costeffectiveness analysis (Garber 2004). Another survey

found that 51 percent of private payers used either costeffective or cost–benefit analysis (Bloom 2004). 

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 185
The Blue Cross Blue Shield Evaluation Center, which

provides technology assessments to subscribing

commercial health plans and provider groups, uses an

evidence-based process for assessing services but

generally excludes explicit considerations of cost and 

cost effectiveness (Garber 2001). Instead, the center 

relies primarily on clinical evidence.8

Purchasers more frequently consider cost-effectiveness

information to inform coverage decisions about drugs 

than about other services. To consider such information

appropriately, formulary managers have increasingly

adopted the Academy of Managed Care Pharmacy’s

(AMCP’s) new evidence-based formulary guidelines,

which call for drug manufacturers to submit clinical and

economic evidence about their products to support the

listing of new pharmaceuticals (AMCP 2005). These

guidelines, the Principles of a Sound Drug Formulary

System, were developed by a coalition of national

organizations and lay out the essential components of a

drug formulary system. AMCP supports the consideration

of pharmacoeconomic factors when making formulary

decisions, after establishing a drug’s safety, efficacy, 

and therapeutic need. 

Why do commercial health plans not use costeffectiveness analysis more widely? Concerns about

potential litigation may discourage them from explicitly

using such analysis in coverage decisions. In one survey 

of health plan officials, most respondents said that they

would cover equally effective but costlier treatments for

fear of litigation or backlash (Singer et al. 1999). To date,

very little litigation has directly raised or challenged the

use of cost-effectiveness analysis (Jacobson and Kanna

2001). Researchers also note that if the medical profession

begins to accept cost-effectiveness analysis underlying 

its standards of care, the courts could incorporate the

information by deferring to professional custom. 

Lack of understanding about the value and applicability 

of cost-effective analysis may also limit its use. Issues

surrounding the methods used to conduct studies may be

another factor. We discuss some of these issues later in

this chapter. Prosser and colleagues (2000) report that

plans may not use cost-effectiveness analysis because their

members may view such analysis as a tool to ration care. 

Use of cost effectiveness internationally

The international experience sharply contrasts with that of

the United States. For a number of years, health systems in

Australia, the United Kingdom, and other countries have

incorporated cost-effectiveness considerations explicitly

into their processes for making coverage and pricing

decisions about drugs and other services.9 For example: 

• Since 1992, Australia requires drug companies to

submit evidence on the comparative cost effectiveness

of new pharmaceuticals before listing them on the

national formulary, and this information guides the

government’s decisions on paying for new drugs.

Companies cannot list new drugs on the national

formulary unless an independent statutory body 

(the Pharmaceutical Benefits Advisory Committee)

recommends it. Between 1993 and 2000, the

pharmaceutical industry in Australia submitted 

more than 300 studies (Hill et al. 2000).

• In the United Kingdom, the National Institute for

Health and Clinical Excellence (NICE) provides

nonbinding guidance to the National Health Service

(NHS) on treatments and care for people who use 

the NHS in England and Wales. NICE develops

technology assessments on the use of new and

existing services and clinical guidelines on the

appropriate treatment of specific diseases and

conditions. NICE’s technology assessments 

consider both clinical effectiveness and costeffectiveness information.

However, the consideration of clinical effectiveness and

cost-effectiveness information internationally has not

proceeded without some disputes. For example, some

patient groups and manufacturers have raised concerns

about a January 2005 preliminary recommendation by

NICE that did not support the use of three drugs for

treating mild to moderate Alzheimer’s disease (NICE

2005). NICE will release its final guidance in July 2005.

Some concerns surrounding Medicare’s

use of cost-effectiveness analysis

Numerous stakeholders—drug and device manufacturers,

providers, beneficiaries, and health economists—have

raised issues and concerns about Medicare’s use of costeffectiveness information in the coverage process.

Stakeholders have also raised some of these same

concerns about the use of such information by other public

and private payers and purchasers.

• Use of cost effectiveness might impair beneficiaries’

access to certain services and will lead to rationing.

For example, a policy that covers only those services

that have cost-effectiveness ratios below a specific

threshold would result in beneficiaries not having

186 Using clinical and cost effectiveness in Medicare
access to all services. Critics are concerned that

Medicare will use cost-effectiveness information for

cost containment purposes only, not for promoting

appropriate care. 

• Some policymakers, providers, and beneficiaries may

not understand cost-effectiveness methods. Costeffectiveness analysis requires a kind of abstract

thinking that might be counterintuitive to some

individuals because it ranks treatments by their 

cost-effectiveness ratios instead of by their benefits

(Eddy 1992). 

• Some policymakers, providers, and beneficiaries may

mistrust the methods used to conduct costeffectiveness analysis. Researchers have noted that

the methodological approach varies from study to

study. Evaluations of the same services and diseases

can show different results. In assessing the cost

effectiveness of treating patients with diabetes, Eddy

(2005) compared five models that used the same

quality weights and cost per treatment. He found that

cost-effectiveness ratios varied from about –$10,000

per QALY to nearly $40,000 per QALY.

Although the U.S. Panel on Cost Effectiveness in

Health and Medicine recommended that published

studies include a reference case that uses a standard

set of methods, many published analyses do not do so.

The lack of clear reporting on methods has led to

concerns from some stakeholders that costeffectiveness analysis is not transparent and that

analyses are “black boxes.” Finally, some stakeholders

are concerned that analyses contain the biases of the

sponsors who fund the studies and the researchers

who conduct them.

• Cost-effectiveness analysis might slow innovation.

Medicare’s coverage policies strongly influence the

medical care that beneficiaries receive for services not

covered under PPSs. (For services paid through PPSs,

providers serve as the purchaser and make decisions

about which services to furnish to beneficiaries.)

Because Medicare covers more than 40 million

beneficiaries, a negative coverage decision could 

have an enormous effect on manufacturers’ revenues.

Manufacturers have noted that a noncoverage decision

by Medicare has a much greater impact on them than

the coverage decisions of individual commercial

health plans. In addition, other payers—including

commercial health plans and Medicaid—often 

follow Medicare’s policies.

• CMS may not have the statutory authority to

consider costs. Section 1862 of the Social Security

Act gives the Secretary the authority to cover items 

or services that are “reasonable and necessary” for 

the diagnosis or treatment of illness or injury or that

improve the functioning of a malformed body

member. Some stakeholders question whether the

Secretary has the authority to consider the value of a

service—in terms of its costs or cost effectiveness—

when making a determination of reasonable 

and necessary.

• Cost effectiveness may not capture public

preferences for allocating limited resources. Some

stakeholders contend that cost effectiveness might be

an aid to decision making, but it is not a complete

procedure for making resource allocation decisions

because it cannot incorporate all the values relevant to

such decisions.

Medicare’s coverage and payment

processes do not explicitly use costeffectiveness analysis

Although the national coverage process considers clinical

effectiveness, it generally does not consider clinical and

cost information together—that is, cost effectiveness. Only

in one instance—for a colorectal screening test—has CMS

explicitly considered the cost effectiveness of a service

when making a national coverage decision and setting the

payment rate (see text box, p. 188).

On several occasions, CMS tried to interpret the statute’s

requirement that Medicare only pay for services that are

reasonable and necessary by including either cost

effectiveness or added value considerations. In 1989, 

the agency published a proposed regulation stating 

that for purposes of coverage, the medical community

would have to accept a technology as safe, effective,

noninvestigational, and appropriate. CMS also included

cost effectiveness as an explicit criterion. Stakeholders

criticized the proposal, particularly for its costeffectiveness provision, and the agency withdrew 

the proposal in 1999. 

Later, in 2000, CMS published a notice of intent outlining

the criteria the agency would use when making national

coverage decisions. The criteria considered the cost only

for services that provided equivalent benefits to an

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 187
existing covered alternative but that were more costly

(Figure 8-2). Again, because of strong opposition, 

CMS never issued a proposed regulation. Foote (2002)

noted that resistance by affected interest groups was one

element that delayed action. 

The future of cost-effectiveness analysis

in Medicare

In recent years, Medicare is using its resources more

efficiently by assessing the clinical effectiveness of

services when making coverage decisions and when

setting payment rates for certain services. MedPAC

supports CMS’s efforts in using an evidence-based,

transparent process when making coverage decisions 

and, more recently, in implementing practical clinical

trials and data registries as a means to obtain better

scientific evidence. 

Might cost-effectiveness analysis also improve Medicare’s

ability to obtain better value for its expenditures? Cost

effectiveness has the potential to favor medical services

that are more likely to improve patient outcomes and 

to discourage the use of services with fewer benefits. 

Cost-effectiveness analysis may not save the Medicare

program money. Wider use of cost-effective, underutilized

services might result in increasing Medicare spending,

which might not be offset with savings elsewhere. 

On the other hand, cost effectiveness could save the

Medicare program money in the long run if its use by the

program encourages manufacturers to develop services

that are more cost effective than current ones.

Manufacturers might bring more cost-effective products 

to the market, if doing so could allow them to increase

their share of Medicare’s market. 

Medicare could begin to consider cost-effectiveness

analysis in four ways. First, the program could begin to

collect cost-effectiveness information during the coverage

process. If feasible, CMS could collect the data via data

registries and practical clinical trials after the agency

agrees to cover a service. In addition, manufacturers that

have already prepared cost-effectiveness analyses could

share these analyses with the agency. Such analyses 

could help the agency better understand the value of 

a new service. Almost all large drug and medical 

device companies have formalized the conduct of 

cost-effectiveness analysis within their firms 

(DiMasi et al. 2001). 

Second, the Secretary could sponsor cost-effectiveness

studies—but these studies will be successful only if 

the research is independent. The Secretary could conduct

the studies or could sponsor other organizations—

such as quasi-public entities or independent private

organizations—to do so. AHRQ has already conducted

cost-effectiveness studies and technology assessments 

188 Using clinical and cost effectiveness in Medicare

CMS’s use of cost effectiveness for a new service

The Balanced Budget Act of 1997 extended coverage 

of colorectal screening tests to Medicare beneficiaries.

To carry out the law, CMS first asked the Agency 

for Healthcare Research and Quality (AHRQ) to

conduct a technology assessment of immunochemical

fecal occult blood tests (iFOBTs) to:

• compare iFOBT to guaiac-based fecal occult blood

test (gFOBT) in terms of cancers detected, cancer

deaths averted, and costs;

• assess cost effectiveness; and

• estimate payment levels of iFOBT at which cost

effectiveness would equal that of gFOBT at current

Medicare payment.

Based on information from this technology assessment

and other sources, CMS concluded that there was

adequate evidence for Medicare to cover iFOBT. 

The results of this analysis demonstrate that CMS 

can use cost-effectiveness information in developing

payment rates. for CMS to use in the national coverage process. In

addition, AHRQ—along with its predecessor agency, 

the National Center for Health Services Research—has

sponsored methodological work in this field (Power and

Eisenberg 1998). The National Institutes of Health have

also sponsored internal and external research on cost

effectiveness. Neumann (2004) raises the possibility of

contracting with quasi-public entities, such as the Institute

of Medicine, to conduct such studies. Alternatively,

Reinhardt (2001, 2004) suggests that independent research

institutes conduct cost–benefit analyses on drug therapies.

The Secretary would also need to determine the services

on which to focus—for example, services with high costs

and the potential for high use versus services for which

little cost-effectiveness information is available (such as

surgical and diagnostic procedures and medical devices). 

Third, Medicare could provide cost-effectiveness analysis

to beneficiaries and health professionals. Both are

potential audiences for information about the relative

value of treatment alternatives that cost-effectiveness

analysis can provide. The traditional Medicare program

does not encourage providers and beneficiaries to weigh

the costs and benefits of a service when making health

care decisions. Medicare does provide some clinical

effectiveness information about certain providers—

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 189

Proposed criteria for making coverage decisions

FIGURE

8-2

Note: CMS never officially implemented this set of criteria, which was issued in a notice of intent.

Source: CMS 2000.

Service is 

covered

Service is 

not covered

Is there sufficient 

evidence that 

demonstrates the 

service is medically 

beneficial for a 

defined population?

Is there a medically 

beneficial alternative 

service that is the 

same clinical modality 

that Medicare currently 

covers?

Is the service 

substantially less or 

substantially more 

beneficial than 

the Medicare-covered 

alternative?

Will the service result in 

equivalent or lower total costs 

for the Medicare population 

than the Medicare-covered 

alternative?

Yes Yes Neither

No Service is No

substantially

less beneficial 

Service is 

substantially

more beneficial 

No Yes
dialysis facilities, hospitals, home health agencies, and

nursing homes—but not cost-effectiveness information.

A consortium of health-related organizations conducted 

a project in which consumers participated in discussion

groups and physicians responded to a survey and

participated in discussion groups on the use of cost

effectiveness. The results suggest that the former are

interested in obtaining better information and that the

latter consider cost effectiveness when making clinical

decisions (Ginsburg 2004; Sacramento Healthcare

Decisions 2001). This project included the following 

key findings: 

• Physicians vary in how often they discuss cost

effectiveness with their patients: 50 percent do so

occasionally, 30 percent do so frequently or always,

and 20 percent report that they never do.

• Most physicians (90 percent) either agreed strongly 

or agreed somewhat that it is appropriate for them 

to consider cost effectiveness when making 

clinical decisions.

• Many consumers accept cost effectiveness as a

reasonable criterion when doctors consider treatment

alternatives for individual patients.

• Consumers also indicated that they need to take more

responsibility in their role as health care recipients, to

improve their individual well-being as well as to

reduce costs.

This research shows that patients and providers can—and

sometimes do—consider cost-effectiveness information.

Nonetheless, Medicare, together with other payers and

purchasers, is in a strong position to disseminate such

information because it represents the interest of 

large populations. 

By using cost-effectiveness analysis, Medicare might

promote other organizations’ use of this analysis. For

example, more commercial health plans might begin 

to consider cost-effectiveness analysis; as mentioned

earlier, less than half of the surveyed plans consider 

cost-effectiveness analysis. Medical organizations 

and federal agencies might also consider using costeffectiveness analysis to develop clinical guidelines. 

Fourth, Medicare could begin to use available costeffectiveness analysis to prioritize pay-for-performance

and disease management initiatives. Consider the

screening of chronic kidney disease among the Medicare

population: Cost-effectiveness analyses could help 

inform policymakers about which subpopulations (such 

as beneficiaries who have diabetes) would generate the

most favorable ratios of health gain to spending. USPSTF

has demonstrated the usefulness of cost-effectiveness

analysis to determine optimal interventions for screening

and to identify the different target populations or risk

groups who might be suitable for preventive services

(Saha et al. 2001).

Before Medicare can routinely use cost-effectiveness

analysis for any of these purposes, it will need to address

valid concerns about the methods used in current analyses.

The measurement of costs and outcomes differ from study

to study. As we mentioned earlier, evaluations of the same

services and diseases can show different results. The lack

of a standardized method of cost-effectiveness analysis

has limited its use by policymakers (Gold et al. 1996).

The Secretary could play an important role in advancing

the field of cost effectiveness. As mentioned earlier, 

the U.S. Panel on Cost Effectiveness in Health and

Medicine made important contributions in addressing

methodological concerns. The Secretary could help

standardize the methods used to conduct these analyses 

in an open process similar to the current national coverage

process. This action will improve the quality of costeffectiveness studies, in turn increasing their usefulness 

to patients, private and public payers, policymakers, 

and health professionals. 

As the field of cost effectiveness evolves and as Medicare

and researchers address methodological issues, Medicare

could begin to apply cost-effectiveness analysis in its ratesetting process. This method might augment the tools that

Medicare now uses in the rate-setting process, such as the

“least costly alternative” policy. 

190 Using clinical and cost effectiveness in Medicare
Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 191

1 Practical clinical trials address questions about a service’s

risks, benefits, and costs as they would occur in routine

clinical practice (Tunis et al. 2003). In practical clinical

trials, researchers select clinically relevant interventions to

compare, include a diverse population of study participants,

recruit participants from a variety of practice settings, 

and collect data on a broad range of health outcomes.

Researchers conduct these trials in “real-world settings” 

with minimal intrusion on care.

2 CMS will pay for beneficiaries’ routine costs in clinical trials

for those trials that: (1) evaluate a service included in a

Medicare benefit category; (2) assess the clinical efficacy of

a service; and (3) enroll patients with a diagnosed disease

rather than healthy volunteers.

3 CMS contracts with companies, known as fiscal

intermediaries and carriers, to process and reimburse Part A

and Part B claims. 

4 Decision-tree models represent the sequence of chance

events and decisions over time for an intervention and each

comparative service. A Markov model is a special type of

state-transition model in which the transition probabilities

depend only on the current state, not on the previous states. 

5 Among the panel’s recommendations is one regarding the

use of a reference case, in which researchers should use a

standard set of methods. For example, the reference case

analysis should compare the proposed service of interest to

existing practice. 

6 For example, the New England Journal of Medicine

developed a policy for the review of cost-effectiveness

analyses intended to preclude financial conflicts of interest

that might affect the choice of methods or data that

researchers use in an analysis (Kassirer and Angell 1994).

The journal announced that it would not publish costeffectiveness analyses if an author has a financial

relationship with a sponsoring company. 

7 The USPSTF, convened by the Public Health Service,

evaluates clinical research to assess the merits of preventive

measures, including screening tests, counseling,

immunizations, and preventive medications. 

8 The Blue Cross Blue Shield Technology Evaluation Center

uses five criteria for evaluating services: (1) the technology

must receive final approval from the appropriate government

regulatory bodies; (2) the scientific evidence must permit

conclusions by the Commission concerning the technology’s

effect on health outcomes; (3) the technology must improve

the net health outcome; (4) the technology must be 

as beneficial as any established alternatives; and 

(5) the improvement must be attainable outside the

investigational settings.

9 Other countries that consider cost-effectiveness information

include Canada, Denmark, Finland, France, Hungary,

Ireland, Italy, New Zealand, the Netherlands, Norway,

Portugal, Spain, and Switzerland.

Endnotes
Academy of Managed Care Pharmacy. 2005. Principles of a

sound drug formulary system. http://www.amcp.org/data/

nav_content/drugformulary%2Epdf.

Bloom, B. 2004. Use of formal benefit/cost evaluations in 

health system decision making. The American Journal of

Managed Care 10, no. 5 (May): 329–335.

Boulware, L. E., B. G. Jaar, M. E. Tarver-Carr, et al. 2003.

Screening for proteinuria in U.S. adults: A cost-effectiveness

analysis. Journal of the American Medical Association 290, 

no. 23 (December 17): 3101–3114.

Centers for Medicare & Medicaid Services, Department of Health

and Human Services. 2000. Medicare program; criteria for

making coverage decisions. Federal Register 65, no. 95 (May

16): 31125–31129. 

DiMasi, J. A., E. Caglarcan, and M. Wood-Armany. 2001.

Emerging role of pharmacoeconomics in the research and

development decision-making process. Pharmacoeconomics 19,

no. 7 (July): 753–766.

Eddy, D. 2005. The role of cost-effectiveness analysis in

decision-making for CMS. Presentation at MedPAC public

meeting, March 11, Washington, DC.

Eddy, D. 1992. Clinical decision making: From theory to

practice. Journal of the American Medical Association 268, 

no. 18 (November 11): 2575–2582.

Eddy, D. 1991. Oregon’s methods. Journal of the American

Medical Association 266, no. 15 (October 16): 2135–2141.

Eddy, D. 1989. Screening for breast cancer. Annals of Internal

Medicine 111, no. 5 (September 1): 389–399.

Elixhauser, A., M. Halpern, J. Schmier, et al. 1998. Health care

CBA and CEA from 1991 to 1996: An updated bibliography.

Health Affairs 36, no. 5 (May): MS1–MS9.

Foote, S. 2002. Why Medicare cannot promulgate a national

coverage rule: A case of regula mortis. Journal of Health Politics,

Policy and Law 27, no. 5 (October): 707–730.

Garber, A. M. 2004. Cost-effectiveness and evidence evaluation

as criteria for coverage policy. Health Affairs (May 19):

W284–W296. 

Garber, A. M. 2001. Evidence-based coverage policy. Health

Affairs 20, no. 5 (September–October): 62–82.

Gillick, M. R. 2004. Medicare coverage for technological

innovations—Time for new criteria? New England Journal of

Medicine 50, no. 21 (May 20): 2199–2203.

Ginsburg, M. E. Cost-effectiveness: Will the public buy it or

balk? 2004. Health Affairs (May 19): W297–W299.

Gold, M. R., J. E. Siegel, L. B. Russell, et al. 1996. Costeffectiveness in health and medicine. New York: Oxford

University Press.

Hill, S. R., A. S. Mitchell, and D. A. Henry. 2000. Problems with

the interpretation of pharmacoeconomic analyses. Journal of the

American Medical Association 283, no. 16 (April 26):

2116–2121.

Jacobson, P. D., and M. L. Kanna. 2001. Cost-effectiveness

analysis in the courts: Recent trends and future prospects.

Journal of Health Politics and Law 26, no. 2 (April): 291–326.

Kassirer, J. P., and M. Angell. 1994. The journal’s policy on costeffectiveness analysis. New England Journal of Medicine 331, 

no. 1 (September 8): 669–670. 

National Committee for Quality Assurance. 2004. The state of

health care quality. Washington DC: NCQA.

National Institute for Health and Clinical Excellence. 2005.

Appraisal consultation document: Alzheimer’s disease—

donepezil, rivastigmine, galantamine and memantine.

http://www.nice.org.uk/page.aspx?o=245908.

Neumann, P. J. 2005a. Medicare and cost-effectiveness.

Presentation at MedPAC public meeting, March 11, 

Washington, DC.

Neumann, P. J. 2005b. Using cost-effectiveness analysis to

improve health care. New York: Oxford University Press. 

Neumann, P. J. 2005c. Growth and quality of the cost-utility

literature, 1976–2001. Value in Health 8, no. 1

(January–February): 3–9. 

Neumann, P. J. 2004. Why don’t Americans use costeffectiveness analysis? The American Journal of Managed 

Care 10, no. 5 (May): 308–312. 

Nord, E., J. L. Pinto, J. Richardson, et al. 1999. Incorporating

societal concerns for fairness in numerical valuations of health

programmes. Health Economics 8, no. 1 (February): 25–39.

192 Using clinical and cost effectiveness in Medicare

References
Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 193

Office of Inspector General, Department of Health and Human

Services. 2004. Medicare reimbursement for Lupron.

Washington, DC: OIG.

Paltiel, A. D., M. C. Weinstein, A. D. Kimmel, et al. 2005.

Expanded screening for HIV in the United States—An analysis of

cost-effectiveness. New England Journal of Medicine 352, no. 6

(February 10): 586–595. 

Power, E. J., and J. M. Eisenberg. 1998. Are we ready to use costeffectiveness analysis in health care decision-making? Medical

Care 36, no. 5 (May): MS0–MS17.

Project HOPE. 2002. Coverage determination processes used by

private insurers and Medicare. Bethesda, MD: Project HOPE

Center for Health Affairs.

Prosser, L. A., J. P. Koplan, P. J. Neumann, et al. 2000. Barriers

to using cost-effectiveness analysis in managed care decision

making. American Journal of Managed Care 6, no. 2 (February):

173–179.

Reinhardt, U. E. 2004. An information infrastructure for the

pharmaceutical market. Health Affairs 23, no. 1

(January/February): 107–112.

Reinhardt, U. E. 2001. Perspectives on the pharmaceutical

industry. Health Affairs 20, no. 5 (September/October): 136–149.

Sacramento Healthcare Decisions. 2001. Cost-effectiveness as a

criterion for medical and coverage decisions.

http://www.sachealthdecisions.org/vf.html.

Saha, S., T. J. Hoerger, M. P. Pignone et al. 2001. The art and

science of incorporating cost effectiveness into evidence-based

recommendations for clinical preventive services. American

Journal of Preventive Medicine 20, no. 3 (April): 36–43.

Schrag, D. 2004 The price tag on progress—chemotherapy for

colorectal cancer. New England Journal of Medicine 351, no. 4

(July 22): 317–319.

Singer, S., L. Bergthold, C. Vorhaus, et al. 1999. Decreasing

variation in medical necessity decision making: Final report to

the California HealthCare Foundation. Oakland, CA: Stanford

University, Center for Policy. 

Tunis, S. R. 2005. Medicare and medical technology policy.

2005. Baltimore: Centers for Medicare & Medicaid Services,

Department of Health and Human Services. February 11.

Tunis, S. R., D. B. Stryer, and C. M. Clancy. 2003. Practical

clinical trials: Increasing the value of clinical research for

decision making in clinical and health policy. Journal of the

American Medical Association 290, no. 12 (September 24):

1624–1632.

Willems, J. S., C. R. Sanders, M. A. Riddiough, et al. 1980. Cost

effectiveness of vaccination against pneumococcal pneumonia.

New England Journal of Medicine 303, no. 10 (September 4):

553–559.

Review of CMS’s preliminary

estimate of the physician

update for 2006

CHAPTER 9

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 197

MS has an annual requirement to use a statutory formula and

calculate a preliminary estimate of the next payment update

for physician services and to send the estimate to MedPAC.

MedPAC must then include a review of the estimate in its

June report to the Congress. For 2006, CMS’s estimate is an update of –4.3 percent. In general, we find that in calculating

the update, CMS used estimates that are consistent with recent trends. In sending MedPAC this estimate, CMS raises a 

second issue: rapid growth in spending for physician services in 2004 (Kuhn 2005). CMS’s preliminary analysis shows that

increases in the volume of a broad range of services—office visits, minor procedures, imaging, laboratory and other tests,

and drugs administered in physician offices—explain the vast majority of the increase in spending. Increases of this 

magnitude raise technical and policy questions and may argue for changes in the way Medicare pays for physician services,

consistent with MedPAC’s recommendations on paying for performance, measuring resource use, reforming the payment

update for physician services, and developing quality standards for imaging providers. Future recommendations could come

from planned Commission work on laboratory services, physical therapy, and possible mispricing of payments under the 

physician fee schedule.

9

In this chapter

• Spending growth in 2004

• Preliminary estimate of the 

physician update for 2006

• Making the case for change

CHAPTER

C

Review of CMS’s preliminary

estimate of the physician

update for 2006
Physicians are central to the delivery of health care. They

evaluate and manage patients, decide when hospitalization

is necessary, perform surgery in hospitals and ambulatory

settings, prescribe drugs, and direct nurses and other

professionals in various settings, including nursing homes,

home health agencies, and dialysis facilities.

CMS’s preliminary estimate is that Medicare spending for

physician services rose sharply by 15.2 percent in 2004

(Kuhn 2005). Its preliminary estimate of the physician

update for 2006 is –4.3 percent. The spending increase 

and the update are linked: A statutory formula adjusts the

update if spending differs from a target based on growth 

in the national economy.

We expected a negative update for 2006. A large

difference has accumulated between actual spending and

the target. In addition, the Congress prevented negative

updates that would have occurred in 2004 and 2005 in the

absence of intervention. The spending increase in this

preliminary estimate is large and requires further study

because it has implications for the financing of Medicare

and beneficiaries’ out-of-pocket spending. In addition,

such a large one-year increase would raise technical and

policy questions about why the increase occurred and how

much of it is due to better diagnosis and care versus

spending that is not necessary and not contributing to 

the quality of care.

In this chapter, we discuss the implications of the spending

growth in 2004. We also review the preliminary estimate

of the 2006 physician update. CMS is required to submit

such an estimate to MedPAC in accordance with a

provision in the Balanced Budget Refinement Act of 1999

(BBRA). The BBRA also requires a MedPAC review of

the estimate as part of the Commission’s June report. In

reviewing CMS’s estimate, MedPAC’s purpose is not to

assess the adequacy of the update. Our analysis of the

update for 2006 can be found in our March 2005 report to

the Congress (MedPAC 2005). Instead, we limit our

review to the technical issues involved in CMS’s use of

the statutory formula to calculate the update.

Spending growth in 2004

CMS states that the surge in spending occurred across a

broad range of services (Table 9-1). The highest growth

occurred in two categories—minor procedures and

imaging, with spending for each category growing by 22

percent in one year. CMS attributes much of the increase

in minor procedures to spending for chemotherapy

administration and physical therapy. The increase in

spending for chemotherapy administration is at least partly

due to an increase in payments for the services required 

by the Medicare Prescription Drug, Improvement, and

Modernization Act of 2003 (MMA). Spending growth 

was also high for Part B drugs and for laboratory and 

other tests, with spending for each category growing by 

17 percent.1

CMS attributes most of the overall rise in spending to

growth in the volume of services. Growth in the number 

of beneficiaries accounts for only a small fraction of the

increase, and CMS estimates that legislative changes—

namely, provisions in the MMA—account for only about

one-fifth of the increase. To understand more about the

volume growth, CMS plans to work further on this issue

and to discuss the results with the physician community

and other stakeholders. Indeed, referring to MedPAC

recommendations on measuring quality and resource use,

CMS is exploring ways to confidentially share information

with individual physicians about how their practices

compare with those of their peers (MedPAC 2005).

In the meantime, MedPAC has analyzed 2004 volume

growth for services that it has studied previously—

198 Review of CMS’s p reliminary estimate of the p hysician u p date for 2006

Spending growth varies by 

type of service, 2003–2004

Percent

Type of of Spending

service spending increase

Visits 38% 11 %

Minor procedures 20 22

Imaging 14 22

Laboratory and other tests 12 17

Part B drugs 10 17

Major procedures 6 8

Other 1 13

Total 100 15

Note: In the first column of numbers, percentages may not necessarily 

add to the total, due to rounding. The total spending increase is a 

weighted average, so the spending increases by type of service do not 

add to the total.

Source: Kuhn 2005 and unpublished data from CMS.

TABLE

9-1
services that Medicare pays for under the physician fee

schedule. To conduct this analysis, we decomposed CMS

spending growth rates into their components: enrollment

growth, the physician update for 2004, and a change in

law concerning the geographic practice cost indexes

(GPCIs) in the fee schedule.2 This decomposition left a

residual spending increase that we can interpret as growth

in the volume of services (Boards of Trustees 2005).3 We

then compared that measure of 2004 volume growth with

estimates of volume growth from 1999 to 2003 (MedPAC

2005). The results agree with CMS’s conclusions about

volume growth: For the services studied, growth in the

volume of physician services in 2004 was considerably

higher than it was from 1999 to 2003 (Figure 9-1). The

biggest difference (12 percentage points) was in minor

procedures, which increased 18 percent in 2004 compared

with average annual growth of 6 percent from 1999 to

2003. Growth in the volume of imaging was also much

higher in 2004: Eighteen percent in 2004 compared with

10 percent annually from 1999 to 2003.

Did all of the increases in 2004 represent services that

beneficiaries need? It is possible that some of the increases

are due to factors often cited as reasons for growth in

spending and use of services: technological innovation,

defensive medicine, direct-to-consumer advertising, shifts

in the site of care, and adherence to clinical guidelines that

call for more intensive treatment of chronic illness. These

factors, however, are not likely the whole story because 

all of them have been at work for at least several years.

Referring to one component of the growth in spending—

a 25 percent increase in spending for advanced

imaging—the CMS administrator said during a press

briefing that nothing suggests that such an increase is

appropriate (Precht 2005).

One consequence of the spending increase is that CMS

now expects the monthly Medicare Part B premium to 

rise higher than previously expected—perhaps by another

$1.50. This increase would be on top of the $9.50 increase

already contemplated for 2006 by the trustees of the

Medicare trust funds and would result in a net 14 percent

increase in the premium. The increase would follow the

large 17 percent increase for 2005 (Boards of Trustees

2005).

Another effect of the spending increase is a larger Part B

claim on the general revenues of the U. S. Treasury. Not

only does this claim impose a burden on taxpayers, but it

also increases the likelihood that spending will reach a

trigger in the MMA. This trigger requires legislative action

if general revenues exceed 45 percent of total outlays for

the Medicare program.

The jump in spending and the associated increase in use of

services also raise concerns about the quality of care. By

the Institute of Medicine’s definition, quality problems

include not just misuse and underuse of services but also

overuse (Institute of Medicine 2001). If some of the

increase represents overuse of services, it may have

negatively affected the quality of care.

The magnitude of the spending increase in 2004 and its

effects argue for change; the question is, how can the

payment system for physician services be part of that

change? As MedPAC has stated previously, the physician

fee schedule—indeed, all of Medicare’s payment

systems—is neutral or negative toward quality. The

Commission has also said that the update formula for

physician services is inequitable because it treats all

physicians and regions of the country alike regardless of

their individual efficiency in furnishing care. And we

further suspect that payments and costs for imaging

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 199

Note: For minor procedures, volume growth from 2003 to 2004 includes changes 

 in the structure of payments for chemotherapy administration.

Source: MedPAC analysis. Percent ch

ange

20

15

10

5

0

Minor

procedures

Imaging Major

procedures

Visits

Average annual volume 

growth, 1999–2003

Volume growth 

2003–2004

Type of service

Volume grew more rapidly in 

2004 than in previous years

FIGURE

9-1
services are misaligned because CMS bases the payments

for practice expense on historical charges instead of

relative resource use.4 There are likely other examples of

mispriced services.

These and other problems have prompted MedPAC to

make a series of recommendations on paying for

performance, measuring resource use, reforming the

payment update for physician services, and developing

quality standards for imaging providers (MedPAC 2005).

More recommendations may come from work we have

planned on laboratory services and physical therapy. As

we discuss in more detail later in this chapter, other 

issues concern the physician fee schedule and possible

mispricing of services, which could have an effect on the

volume of services. We plan to address such issues in 

the context of reviewing Medicare’s experience with the

physician fee schedule now that it has been in place for

over a decade. However, before we discuss these plans, we

fulfill our statutory requirement to review CMS’s estimate

of the physician update for 2006. In general, we find that

in calculating the update, CMS used estimates that are

consistent with recent trends.

Preliminary estimate of the physician

update for 2006

Medicare pays for physician services according to a fee

schedule that assigns relative value units (RVUs) to

services, reflecting resource requirements. These RVUs

are adjusted for geographic differences in practice costs

and multiplied by a dollar amount—the conversion

factor—to determine payments. Thus, the conversion

factor is a key element of the payment system. Changes 

in the conversion factor trigger proportional changes in 

the payment rates for all of the more than 7,000 services

represented in the physician fee schedule.

CMS updates the conversion factor annually, based on a

formula in law that is designed to control spending while

accounting for factors that affect the cost of physician

services. CMS issues a final rule on the update in

November of each year and implements the update on

January 1 of the following year. To help the Congress and

others anticipate the update, the BBRA requires CMS to

prepare, by March 1 of each year, a preliminary estimate

of the next year’s update. The BBRA also requires

MedPAC to review that estimate in the Commission’s

June report. This chapter fulfills that requirement for 

the 2006 update.

Calculating the update

Calculating the update is a two-step process. First, CMS

estimates the sustainable growth rate (SGR). The SGR is

the target rate of growth in spending for physician services

and is a function of projected changes in:

• input prices for physician services;5

• real gross domestic product (GDP) per capita, an

allowance for growth in the volume of services;6

• enrollment in traditional fee-for-service Medicare; and

• spending attributable to changes in law and regulation.

For 2006, CMS’s preliminary estimate of the SGR is 2.5

percent (Table 9-2).

Second, CMS calculates the update, which is a 

function of:

• the change in input prices for physician services,7 and

• an update adjustment factor that increases or decreases

the update as needed to align actual spending,

cumulated over time, with target spending determined

by the SGR.

The estimate of the change in input prices for 2006 is 2.9

percent (Table 9-3). The more important part of the update

calculation, however, is the update adjustment factor,

200 Review of CMS’s p reliminary estimate of the p hysician u p date for 2006

Preliminary sustainable 

growth rate, 2006

Factor Percent

Change in: 

input prices 2.8%

traditional Medicare enrollment –2.5

real GDP per capita 2.3

Change due to law and regulations 0.0

Sustainable growth rate 2.5

Note: GDP (gross domestic product). Percents are converted to ratios and 

multiplied, not added, to produce the sustainable growth rate.

Source: Kuhn 2005.

TABLE

9-2
which CMS estimates at –7.0 percent, the maximum

negative adjustment permitted under current law. When

we combine this adjustment with the estimated change in

input prices, the result is an update of –4.3 percent.

The update adjustment factor is the link mentioned earlier

between spending and the update. The factor is negative

because actual spending for physician services started 

to exceed the target in 2000 and has since remained 

above the target (Figure 9-2). Indeed, the update

adjustment factor would be –21.1 percent if not for 

the –7.0 percent limit.

Reviewing CMS’s estimate

Because the update adjustment factor is well beyond the

statutory limit, MedPAC anticipates no changes in CMS’s

estimates that would change the update. In the 2006 SGR,

the estimate of the change in input prices, as measured by

the Medicare Economic Index (MEI), is similar to changes

in the MEI for earlier years.8 The change in real GDP per

capita of 2.3 percent equals the 10-year moving average 

of real GDP estimates from the Bureau of Economic

Analysis (BEA), adjusted for population growth 

(BEA 2005).

CMS expects no measurable changes in spending due to

law and regulation for 2006.9 Provisions in the MMA will

expire then (e.g., floors on the GPCIs for Alaska), but

CMS anticipates that the drop in spending will be very

small—less than 0.1 percent. CMS also considered

implementation of the Medicare Part D drug benefit and

the possible effects of the benefit on the use of physician

services. The agency chose not to include a specific

spending change in the SGR related to the Part D benefit,

relying on a recommendation of the Technical Review

Panel on the Medicare Trustees Report (2004). The panel

concluded that Part D could lead to higher or lower use of

other health services, and the panel agreed with an

assumption of no effect on utilization or costs in Part A or

Part B. However, the panel recommended further research

on the topic to take advantage of the natural experiment

offered by implementation of Part D. Depending on the

results of this research, CMS could revise the SGR’s law

and regulation factor in the future.

The remaining factor in the SGR estimate for 2006—

the change in fee-for-service enrollment—is also

uncertain. CMS assumes a decrease in fee-for-service

enrollment of 2.5 percent (Table 9-2). This figure differs

from the Congressional Budget Office’s (CBO’s)

enrollment projection, which is an increase in fee-forservice enrollment of 0.5 percent for fiscal year 2006. A

decrease would occur if some enrollment shifts from

Medicare fee-for-service to Medicare Advantage (MA).

The magnitude of such a shift (if it occurs) remains

unclear, but CMS will know more in June 2005 when MA

plans submit bids and identify market areas. CMS can then

revise the enrollment projection, if necessary, before the

update becomes final in November 2005. Even then, CMS

will have limited information on changes in enrollment in

2006, but the agency will have another two years to revise

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 201

Estimate of the update for 

physician services, 2006

Factor Percent

Change in input prices 2.9%

Change in adjustment factor –7.0

Update –4.3

Note: Percents are converted to ratios and multiplied, not added, to produce 

the update.

Source: Kuhn 2005.

TABLE

9-3

Target

Actual

Source: Office of the Actuary 2005. Spending (doll

ars in billions)

100

80

90

70

60

50

40

1997 1998 1999 2000 2001 2002 2003 2004

Through 2004, actual spending for

physician services exceeded target

FIGURE

9-2
the enrollment estimate if better data become available,

just as the agency does with changes in spending due to

law and regulation.

Regardless of what happens with enrollment, CMS’s

calculation of the update for 2006 is very unlikely 

to change. To see the effect of an enrollment change,

MedPAC substituted CBO’s projection for CMS’s

projection, then calculated an update adjustment factor 

of –21.0 percent, almost the same as CMS’s calculation 

of –21.1 percent based on its own estimate of 

enrollment growth.

The only remaining issue concerns CMS’s estimates of

actual spending for 2004 and 2005. Data on actual

spending are nearly complete through the first three

quarters of 2004 but are less complete for the last quarter

of that year. Therefore, the estimate of actual spending in

2004 may increase or decrease somewhat before CMS

issues a final rule on the update in November 2005. Of

course, the uncertainty regarding 2005 estimates is greater

than for 2004 because CMS currently has very little

information on actual spending for 2005.

To address these uncertainties, the agency has used

stochastic projection techniques to analyze variation in the

update adjustment factor (Office of the Actuary 2005).

Under a range of possible scenarios for growth in real

GDP per capita and growth in the volume of physician

services, the analysis shows a 100 percent probability that

the update adjustment factor will equal the maximum

negative adjustment of –7.0 percent.

A maximum negative adjustment has such a high

probability because a different outcome would require an

uncharacteristic decrease in spending for physician

services in 2005. An update of 1.5 percent for 2005 has

already occurred. Therefore, the only way in which

spending could fall is through a substantial decrease in the

volume of physician services per beneficiary. However,

this decrease is very unlikely based on historical trends.

From 1999 to 2003, for example, volume increased at an

average annual rate of about 5 percent per year. As we

discussed earlier, volume grew at an even higher rate in

2004. For this reason, MedPAC anticipates that CMS’s

update calculations (to be published in November 2005)

will show the maximum reduction that the statute permits.

Making the case for change

Previously, the Commission has recommended policies

that could work in tandem with the physician fee schedule,

such as paying for performance, measuring resource use,

and developing quality standards for imaging providers.

Additional issues have emerged that are internal to the fee

schedule. As such, they represent instances of possible

mispricing. If mispricing includes Medicare overpaying

for services, that mispricing could contribute to overuse 

of services—one of the concerns with the spending

increase in 2004.

202 Review of CMS’s p reliminary estimate of the p hysician u p date for 2006

Impact of the practice expense 

GPCI on the payment rate for

an equipment-intensive service

Example: MRI of lumbar spine without contrast material performed in a

physician’s office or IDTF, 2005

Locality with lowest practice expense GPCI:

Missouri, excluding Kansas City and St. Louis

Adjusted

RVU GPCI RVU

Physician work 1.48 x 1.000 = 1.48

Practice expense 12.93 x 0.813 = 10.51

PLI 0.71 x 0.892 = + 0.63

12.63

Conversion factor x $37.90

Payment rate $478.47

Locality with highest practice expense GPCI:

San Francisco

Adjusted

RVU GPCI RVU

Physician work 1.48 x 1.064 = 1.57

Practice expense 12.93 x 1.501 = 19.41

PLI 0.71 x 0.651 = + 0.46

21.44

Conversion factor x $37.90

Payment rate $812.71

Note: GPCI (geographic practice cost index), MRI (magnetic resonance 

imaging), IDTF (independent diagnostic testing facility), RVU (relative value

unit), PLI (professional liability insurance). Results may not equal numbers 

shown due to rounding. Localities considered are those in the continental 

United States.

Source: CMS 2004.

TABLE

9-4
Adjusting payments geographically for

input prices

Under the physician fee schedule, GPCIs adjust payment

rates to account for differences in the price of inputs used

in furnishing physician services. Three separate GPCIs

correspond to each of three components of the fee

schedule’s relative value scale: physician work, practice

expense, and professional liability insurance.

MedPAC’s concern is with the practice expense GPCI.

Current policy stipulates that the prices of some

inputs—namely, equipment and supplies—do not vary

geographically because physicians purchase those inputs

in a national market, not locally. When constructing the

GPCI, CMS accounts somewhat for this fact by holding

constant the price of equipment and supplies. The problem

is that the GPCI applies to the entire practice expense

payment for all services, even though the cost of

equipment and supplies, as a proportion of practice

expense, varies by service. Therefore, for equipment- and

supply-intensive services, payments are too high, relative

to costs, in high-GPCI areas and too low, relative to costs,

in low-GPCI areas.

The effect of the GPCI adjustment can be significant. The

most frequently billed magnetic resonance imaging (MRI)

study—MRI of the spine—is an example. In the locality

with the lowest practice expense GPCI (areas of Missouri

outside Kansas City and St. Louis), the payment rate for

MRI of the spine is $478 (Table 9-4, p. 202). By contrast,

the payment rate is $813—70 percent higher—in San

Francisco, the locality with the highest practice expense

GPCI.10 The main reason for the difference is that the

practice expense GPCI is 0.813 in the areas of Missouri. 

In San Francisco, it is 1.501. This difference prevails even

though most of the direct costs of furnishing the service

originate from the equipment, which physicians purchase

in a national market.11

The problem with the practice expense GPCI varies,

depending on the service. Across all services, equipment

and supplies represented about 32 percent of direct costs,

on average, in 2003 (Figure 9-3). For imaging services,

however, equipment and supplies represented an average

of 76 percent of direct costs. For other services—such as

major procedures and evaluation and management

(E&M)—equipment and supplies make up a lower-thanaverage share of direct costs. Within this latter group of

services, the practice expense GPCI causes payments to be

too low, relative to costs, in high-GPCI areas and too high,

relative to costs, in low-GPCI areas.

To assess the magnitude of this problem, MedPAC plans

to analyze the correlation between the volume of the

affected services—such as imaging—and the practice

expense GPCI. To assess possible solutions, we plan to

replicate CMS’s practice expense methodology and to

calculate the portion of each service’s practice expense

RVUs that we can attribute to equipment and supplies. In

addition to illustrating the methods required, we can then

model the payment effects of a policy change.

Revisiting the boundaries of payment

localities

The GPCIs vary by geographic areas called payment

localities. Of the 89 total payment localities, 34 consist 

of entire states (Figure 9-4). Initially, Medicare accepted

the localities established by the contractors who process

claims for Medicare. To set boundaries for the localities,

the contractors used their knowledge of patterns in

physician charges for services.

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 203

Direct expenses in practice 

expense RVUs, 2003

FIGURE

9-3

Note: RVU (relative value unit), E&M (evaluation and management).

Source: MedPAC analysis of practice expense input file from CMS, 2003; 

 Medicare claims data for 100% of beneficiaries. Percent

age of direct expenses

80

100

90

20

40

60

70

10

30

50

0

Type of service

Nonphysician clinical staff Equipment and supplies

E&M Imaging Major Other

procedures

Tests All
As another possible instance of mispricing of services, it

may be time to revisit the boundaries of payment

localities, at least in those states that do not have statewide

localities. CMS has not revised the boundaries since 1997,

when it consolidated 210 localities to the current 89 to

simplify administration and reduce payment differences

among adjacent geographic areas. In addition, physicians

can initiate a change in the locality boundaries of their

state. Some physicians are working toward such a change.

For instance, the California Medical Association has

proposed an increase in the number of localities in the

state from 9 to 19.

Given that CMS has not reconfigured the localities in at

least 8 years (and, in some cases, 40 years), the localities

likely do not correspond to market boundaries for the

inputs physicians use in furnishing services. As a result,

Medicare is probably overpaying in some geographic

areas and underpaying in others.

To revisit the locality boundaries, MedPAC plans to use

data on input prices by county and identify cases in which

the boundaries are inconsistent with variation in input

prices beyond a predefined threshold. We can then model

the effects of alternative locality configurations. The

Commission could recommend alternative locality

boundaries as appropriate.

204 Review of CMS’s p reliminary estimate of the p hysician u p date for 2006

Physician fee schedule payment localities

FIGURE

9-4

Note: States with no shaded regions have one payment locality. Additional payment localities in the other states are indicated by variation in area shading.

Source: MedPAC analysis.
Valuing services in the physician fee

schedule

The fee schedule’s RVUs are a key element of the

payment system because the RVUs determine how

payment rates vary, one service relative to another.

Initially, research at Harvard University led to the RVUs

that were implemented with the fee schedule in 1992. The

expectation was that payment rates would rise for E&M

services relative to other services, such as surgery and

other procedural services. Analyses by the Physician

Payment Review Commission (PPRC) and others showed

that such changes in payment rates occurred (PPRC 1997,

Iglehart 2002).

In addition to the changes in payment rates anticipated

with implementation of the fee schedule, other factors

have affected payments for physician services. CMS has

reviewed and modified the RVUs for selected services

after receiving recommendations from the RVS Update

Committee (RUC).12 CMS has established RVUs for 

new services using a similar process of receiving

recommendations from the RUC. The volume of 

services has changed.

To understand the effects of these other factors affecting

payments, MedPAC contracted with The Urban Institute

for analyses of changes in RVUs over time and how those

changes interact with growth in the volume of services. 

To measure these effects, the contractor developed a

measure of RVU volume, which comprises units of

service weighted by each service’s RVU.

Preliminary findings from this work describe the effects of

periodic RVU review,13 the interaction between changes

in RVUs and growth in the volume of services, and the

effects of introducing new services—all during the first 

10 years of experience with the physician fee schedule

(Maxwell, Zuckerman, and Berenson 2005). In general,

the findings highlight the importance of new services and

the importance of the choices that CMS and the RUC

make about the services whose RVUs are reviewed. 

The following specific findings are of particular interest 

to MedPAC:

• By 2002, CMS had not reviewed or revised the RVUs

for about 50 percent of services, but those services

accounted for only 16 percent of volume. For the

services that accounted for the remaining 84 percent

of volume, CMS had established the RVUs with

recommendations from the RUC.

• CMS’s review of RVUs has led to substantially more

increases than decreases in RVUs because the process

by which CMS and the RUC consider potentially

misvalued services has given priority to services that

may be undervalued rather than services that may be

overvalued. The reviews have yielded this result even

though the factors that can lead to a service becoming

misvalued—technology diffusion, learning by doing,

technology substitution, personnel substitution,

reengineering, patient severity, and mandatory

documentation—suggest that both undervalued and

overvalued services are an issue.14

• Growth in units of service has driven growth in RVU

volume for some services; however, for other services,

growth in RVUs per unit of service was the more

important factor underlying growth in volume.

• In addition to volume growth, the introduction of new

services has shifted the distribution of total RVU

volume among services. For E&M services, the result

has been an offset of the gains in RVU volume that

the services experienced because of increased RVUs. 

MedPAC plans further work on the process for valuing

services in the fee schedule. An initial step will be to

continue the work on RVU volume, looking at the 

effects of volume growth and changes in RVUs on the

distribution of payments by service and also by physician

specialty. Next, we plan to consider the process for

selecting services for review to determine whether this

process adequately identifies services whose RVUs may

need to decrease. This effort will include monitoring 

the next review of RVUs for physician work, scheduled

for completion in 2007, so we can assess whether the

process is becoming more successful in identifying both

undervalued and overvalued services. We also plan to

consider the process that CMS uses to establish RVUs for

new services. In doing so, we will explore ways to ensure

further review of the RVUs after physicians have gained

some familiarity and become more efficient in furnishing

new services. In addition, to ensure that RVUs account for

the cost of an efficient physician’s services, we plan to

examine the RVUs for practice expense and the extent to

which the RVUs represent the marginal cost (not just the

average cost) of furnishing a given service.15 We also plan

to explore how CMS might distinguish the marginal costs

incurred by physicians who demonstrate superior

productive efficiency per unit of service.

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 205
Determining practice expense RVUs

On average, payments for practice expense account for

about 44 percent of spending under the physician fee

schedule. As discussed in MedPAC’s Report to the

Congress: Impact of Resource-Based Practice Expense

Payments for Physician Services (2004b), CMS derived

resource-based practice expense RVUs for the physician

schedule with the best data available at the time. However,

some of those data are becoming out of date—for instance,

much of the data on physicians’ aggregate practice costs

date back to the mid- to late- 1990s. Although CMS 

has received supplemental data from some physician

specialties, the accuracy of practice expense payments is

becoming more of an issue as time passes. MedPAC plans

to continue analyzing the data that CMS uses to establish

practice expense payments and the methods that it uses to

derive these payments. 

Changing the unit of payment

Compared to other payment systems, the unit of payment

in the physician fee schedule is very small. The fee

schedule includes payment rates for many of the discrete

services that a physician furnishes—visits, imaging

studies, laboratory and other diagnostic tests, and

procedures. In some cases, the physician furnishes the

services during a single encounter with a patient. In other

cases, the physician furnishes the services during multiple

encounters over a period of time. Such a small unit of

payment raises a long-standing concern about whether it

gives physicians a financial incentive to increase the

volume of services (MedPAC 1999). To address this

concern, MedPAC could explore options for increasing

the size of the unit of payment to include bundles of

services that physicians often furnish together or during

the same episode of care. MedPAC’s work would address

procedures for identifying the relevant services,

determining payment methods for the services, and

analyzing the implications for quality of care. 

206 Review of CMS’s p reliminary estimate of the p hysician u p date for 2006
Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 207

1 The 17 percent increase in spending for Part B drugs must

include a large increase in the volume of the drugs because

spending increased despite a drop in payment rates for the

drugs. In 2004, CMS implemented a statutory reduction in

the payment formula for the drugs, which reduced payment

rates for them by 10 percentage points.

2 The Congress established floors under geographic practice

cost indexes (GPCIs) as part of the Medicare Prescription

Drug, Improvement, and Modernization Act of 2003.

Effective for the first time in 2004, the floors raised

payments in Alaska for physician work, practice expense,

and professional liability insurance (PLI). Elsewhere,

payments went up for practice expense only. To analyze the

effects of the GPCI floors, we used 2003 claims data from

100 percent of beneficiaries to determine how spending in

that year would have changed if the floors had been in effect

in that year. We conducted this analysis by payment locality

and procedure code and then aggregated the results by type

of service. The results were that the GPCI floors increased

spending as follows: visits, 1.0 percent; minor procedures,

0.8 percent; imaging, 0.5 percent; and major procedures, 1.0

percent.

3 For minor procedures, the residual also includes a change in

the structure of payments for chemotherapy administration.

Although 2004 data are not yet available on the effect of 

this change, the 2003 data show that chemotherapy

administration accounted for about 3 percent of spending 

for minor procedures.

4 In CMS’s methodology for determining relative value units

(RVUs) for practice expense, the technical components of

imaging services and other diagnostic tests are in a category

called the nonphysician work pool. The practice expense

RVUs for those technical component services are not yet

resource based. CMS plans to propose resource-based RVUs

for those services in 2005.

5 For the SGR, physician services include services commonly

performed by a physician or performed in a physician’s

office. In addition to physician fee schedule services, these

services include diagnostic laboratory tests and most of the

drugs covered under Medicare Part B. To estimate this

factor, CMS uses a weighted average of the Medicare

Economic Index (MEI), a measure of changes in input prices

for physician services, the change in payment rates for

laboratory services legislated by the Congress, and a

weighted average of the change in payment rates for Part

B–covered drugs.

6 As required by the MMA, the real GDP per capita factor in

the SGR is a 10-year moving average.

7 For the update, physician services include only those services

in the physician fee schedule.

8 Historical changes in the MEI are published by the CMS

Office of the Actuary (2005).

9 For further discussion of changes in spending due to law and

regulation, see MedPAC’s Report to the Congress: Growth

in the Volume of Physician Services (2004a).

10 For purposes of this discussion, we include localities in the

continental United States (i.e., excluding Alaska, Hawaii,

Puerto Rico, and the U.S. Virgin Islands).

11 In the methodology for determining practice expense RVUs,

CMS defines two types of costs: direct and indirect. Direct

costs are costs attributable to specific services, such as the

earnings of nonphysician clinical personnel, equipment, and

supplies. Indirect costs are not as readily assigned to services

and include the earnings of administrative personnel, rent,

and utilities.

12 The RVS Update Committee is a committee involving the

American Medical Association and national medical

specialty societies.

13 By law, RVUs are reviewed every five years.

14 The list of sources of changes in physician work is from

CMS. It was prepared for the review of physician work

RVUs that was completed in 2002 (CMS 2000).

15 MedPAC has discussed the goal of basing payment rates on

a provider’s marginal cost in a previous report (MedPAC

2001).

Endnotes
Boards of Trustees, Federal Hospital Insurance and Federal

Supplementary Medical Insurance Trust Funds. 2005. 2005

annual report of the Boards of Trustees of the Federal Hospital

Insurance and Federal Supplementary Medical Insurance Trust

Funds. Washington, DC: Boards of Trustees.

Bureau of Economic Analysis, Department of Commerce. 

2005. Current-dollar and real gross domestic product [Excel

spreadsheet]. Washington, DC: BEA. February 25.

http://www.bea.gov/bea/dn/gdplev.xls.

Centers for Medicare & Medicaid Services, Department of Health

and Human Services. 2004. Medicare program: Revisions to

payment policies under the physician fee schedule for calendar

year 2005. Final rule. Federal Register 69, no. 219 (November

15): 66236–66427.

Centers for Medicare & Medicaid Services, Department of Health

and Human Services. 2003. 2003 information: Practice expense

input file. http://www.cms.hhs.gov/physicians/pfs/default.asp.

Centers for Medicare & Medicaid Services, Department of Health

and Human Services. 2000. 2000 information: Five-year review

of work relative value units. http://www.cms.hhs.gov/physicians/

pfs/wrvu-toc.asp.

Iglehart, J. K. 2002. Medicare’s declining payments to

physicians. New England Journal of Medicine 346, no. 24 (June

13): 1924–1930.

Institute of Medicine. 2001. Crossing the quality chasm: A new

health system for the 21st century. Washington, DC: National

Academies Press.

Kuhn, H. B., Centers for Medicare & Medicaid Services,

Department of Health and Human Services. 2005. Letter to 

Glenn M. Hackbarth, Medicare Payment Advisory Commission.

March 31.

Maxwell, S., S. Zuckerman, and R. Berenson. 2005. First 10

years of the fee schedule: RVU and volume changes. Presentation

at MedPAC meeting, April 22, Washington, DC.

Medicare Payment Advisory Commission. 2005. Report to the

Congress: Medicare payment policy. Washington, DC: MedPAC.

Medicare Payment Advisory Commission. 2004a. Report to the

Congress: Growth in the volume of physician services.

Washington, DC: MedPAC.

Medicare Payment Advisory Commission. 2004b. Report to the

Congress: Impact of resource-based practice expense payments

for physician services. Washington, DC: MedPAC.

Medicare Payment Advisory Commission. 2001. Report to the

Congress: Medicare payment policy. Washington, DC: MedPAC.

Medicare Payment Advisory Commission. 1999. Report to the

Congress: Medicare payment policy. Washington, DC: MedPAC.

Office of the Actuary, Centers for Medicare & Medicaid

Services, Department of Health and Human Services. 2005.

Estimated sustainable growth rate and conversion factor, for

Medicare payments to physicians in 2006. Baltimore: CMS.

http://www.cms.hhs.gov/providers/sgr/sgr2006p.pdf.

Physician Payment Review Commission. 1997. Annual report to

Congress. Washington, DC: PPRC.

Precht, P. 2005. CMS: High-tech imaging growth feeds record

spike in Medicare physician spending. Inside Health Today

[E-mail newsletter]. April 1.

Technical Review Panel on the Medicare Trustees Report. 2004.

Review of the assumptions and methods of the Medicare trustees’

financial projections. Washington, DC: Technical Review Panel

on the Medicare Trustees Report. December.

208 Review of CMS’s p reliminary estimate of the p hysician u p date for 2006

References
Commissioners’ voting

on recommendations

APPENDIX A

In the Medicare, Medicaid, and SCHIP Benefits Improvement and Protection Act of 2000, the Congress required

MedPAC to call for individual Commissioner votes on each recommendation, and to document the voting record in its

report. The information below satisfies that mandate.

Chapter 1: Monitoring the implementation of Part D

The Secretary should have a process in place for timely delivery of Part D data to congressional support agencies

to enable them to report to the Congress on the drug benefit's impact on cost, quality, and access.

Yes: Bertko, Burke, Crosson, DeBusk, DeParle, Durenberger, Hackbarth, Milstein, Muller, Nelson,

Reischauer, Scanlon, Smith, Stowers, Wolter

Absent: Raphael, Wakefield

Chapter 2: Medicare Advantage payment areas and risk adjustment

2A The Congress should establish payment areas for Medicare Advantage local plans that have the following

characteristics:

• Among counties in metropolitan statistical areas, payment areas should be collections 

of counties that are located in the same state and the same metropolitan statistical area.

• Among counties outside metropolitan statistical areas, payment areas should be 

collections of counties in the same state that are accurate reflections of health care 

market areas, such as health service areas.

Yes: Bertko, Burke, Crosson, DeBusk, DeParle, Durenberger, Hackbarth, Milstein, Muller, Nelson,

Raphael, Reischauer, Scanlon, Smith, Stowers, Wolter

Absent: Wakefield

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 211

Commissioners’ voting

APPENDIX A

on recommendations
2B The Secretary should update health service areas before using them as payment areas in the Medicare Advantage

program. In addition, the Secretary should make periodic updates to health service areas to reflect changes in

health care market areas that occur over time.

Yes: Bertko, Burke, Crosson, DeBusk, DeParle, Durenberger, Hackbarth, Milstein, Muller, Nelson,

Raphael, Reischauer, Scanlon, Smith, Stowers, Wolter

Absent: Wakefield

Chapter 3: The Medicare Advantage program

3A The Congress should eliminate the stabilization fund for regional preferred provider organizations.

Yes: Bertko, Burke, Crosson, DeBusk, DeParle, Durenberger, Hackbarth, Milstein, Muller, Nelson,

Raphael, Reischauer, Smith, Stowers, Wolter

No: Scanlon

Absent: Wakefield

3B The Secretary should calculate clinical measures for the fee-for-service program that would permit CMS to

compare the fee-for-service program to Medicare Advantage plans.

Yes: Bertko, Burke, Crosson, DeBusk, DeParle, Durenberger, Hackbarth, Milstein, Muller, Nelson,

Raphael, Reischauer, Scanlon, Smith, Stowers, Wolter

Absent: Wakefield

3C The Congress should clarify that regional plans should submit bids that are standardized for the region’s

Medicare Advantage–eligible population. 

Yes: Bertko, Burke, Crosson, DeBusk, DeParle, Durenberger, Hackbarth, Milstein, Muller, Nelson,

Raphael, Reischauer, Scanlon, Smith, Stowers, Wolter

Absent: Wakefield

3D The Congress should remove the effect of payments for indirect medical education from the Medicare Advantage

plan benchmarks. 

Yes: Bertko, Burke, Crosson, DeBusk, DeParle, Durenberger, Hackbarth, Milstein, Muller, Nelson,

Raphael, Reischauer, Scanlon, Smith, Stowers, Wolter

Absent: Wakefield

3E a) The Congress should set the benchmarks that CMS uses to evaluate Medicare Advantage plan bids at 100

percent of the fee-for-service costs. 

Yes: Bertko, Burke, Crosson, DeBusk, DeParle, Durenberger, Hackbarth, Milstein, Muller, Nelson,

Raphael, Reischauer, Scanlon, Smith, Stowers, Wolter

Absent: Wakefield

212 Commissioners’ voting on recommendations
b) At the same time, the Congress should also redirect Medicare’s share of savings from bids below the

benchmarks to a fund that would redistribute the savings back to Medicare Advantage plans based on quality

measures. 

Yes: Bertko, Burke, Crosson, DeBusk, DeParle, Durenberger, Hackbarth, Milstein, Muller, Nelson,

Raphael, Reischauer, Scanlon, Smith, Stowers, Wolter

Absent: Wakefield

3F The Congress should put into law the scheduled phase-out of the hold-harmless policy that offsets the impact of

risk adjustment on aggregate payments through 2010.

Yes: Bertko, Burke, Crosson, DeBusk, DeParle, Durenberger, Hackbarth, Milstein, Muller, Nelson,

Raphael, Reischauer, Scanlon, Smith, Stowers, Wolter

Absent: Wakefield

Chapter 4: Payment for dialysis

4A The Congress should direct the Secretary to:

• eliminate differences in paying for composite rate services between hospital-based and freestanding 

dialysis facilities; and 

• combine the base composite rate and the add-on adjustment.

Yes: Bertko, Burke, Crosson, DeBusk, DeParle, Durenberger, Hackbarth, Milstein, Muller, Nelson,

Raphael, Reischauer, Scanlon, Smith, Stowers, Wolter

Absent: Wakefield

4B The Secretary should: 

• eliminate differences in paying for injectable drugs between hospital-based and freestanding dialysis

facilities; and 

• use average sales price data to base payment for all injectable dialysis drugs that are separately 

billable in 2006.

Yes: Bertko, Burke, Crosson, DeBusk, DeParle, Durenberger, Hackbarth, Milstein, Muller, Nelson,

Raphael, Reischauer, Scanlon, Smith, Stowers, Wolter

Absent: Wakefield

4C The Congress should give the Secretary the authority to periodically collect average acquisition cost data 

from dialysis providers and compare it with average sales price data. The Secretary should collect data on 

the acquisition cost and payment per unit for drugs—other than erythropoietin—that hospital-based 

providers furnish.

Yes: Bertko, Burke, Crosson, DeBusk, DeParle, Durenberger, Hackbarth, Milstein, Muller, Nelson,

Raphael, Reischauer, Scanlon, Smith, Stowers, Wolter

Absent: Wakefield

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 213
Chapter 5: Payment for post-acute care

No recommendations

Chapter 6: Payment for pharmacy handling costs in hospital outpatient departments

6A The Secretary should establish separate, budget-neutral payments to cover the costs that hospitals incur for

handling separately paid drugs, biologicals, and radiopharmaceuticals.

Yes: Bertko, Burke, Crosson, DeBusk, DeParle, Durenberger, Hackbarth, Milstein, Muller, Nelson,

Raphael, Reischauer, Scanlon, Smith, Stowers, Wolter

Absent: Wakefield

6B The Secretary should:

• define a set of handling fee APCs that group drugs, biologicals, and radiopharmaceuticals based on attributes

of the products that affect handling costs;

• instruct hospitals to submit charges for those APCs; and

• base payment rates for the handling fee APCs on submitted charges, reduced to costs.

Yes: Bertko, Burke, Crosson, DeBusk, DeParle, Durenberger, Hackbarth, Milstein, Muller, Nelson,

Raphael, Reischauer, Scanlon, Smith, Stowers, Wolter

Absent: Wakefield

Chapter 7: Critical access hospitals

No recommendations

Chapter 8: Using clinical and cost effectiveness in Medicare

No recommendations

Chapter 9: Review of CMS's preliminary estimate of the physician update for 2006

No recommendations

214 Commissioners’ voting on recommendations
Acronyms

AAP average acquisition payment

AAPCC adjusted average per capita cost

ACCC Association of Community Cancer Centers

ACR adjusted community rate

ADC average daily census

ADL activity of daily living

AHA American Hospital Association

AIDS acquired immunodeficiency syndrome

AMCP Academy of Managed Care Pharmacy

AMI acute myocardial infarction

AHRQ Agency for Healthcare Research and Quality

APACHE Acute Physiology and Chronic Health Evaluation

APC ambulatory payment classification

APR–DRG all patient refined diagnosis related group

ARC Actuarial Research Corporation

ASHP American Society of Health-System Pharmacists

ASP average sales price

ASPE Assistant Secretary for Planning and Evaluation

AWP average wholesale price

BBA Balanced Budget Act of 1997

BBRA Balanced Budget Refinement Act of 1999 

BEA Bureau of Economic Analysis

BIPA Medicare, Medicaid, and SCHIP Benefits

Improvement and Protection Act of 2000

BMI body mass index

B–N budget neutrality

CAH critical access hospital

CAHPS Consumer Assessment of Health Plans Survey

CBA cost–benefit analysis

CBO Congressional Budget Office

CCR cost-to-charge ratio

CEA cost-effectiveness analysis

CEO chief executive officer

CMS Centers for Medicare & Medicaid Services

CMS–HCC CMS–hierarchical condition category

COP condition of participation

COPD chronic obstructive pulmonary disease

CORAR Council on Radionuclides and

Radiopharmaceuticals

COX–2 cyclo-oxygenase–2

CY calendar year

DCG diagnostic cost group

DME durable medical equipment

DoD Department of Defense

DRG diagnosis related group

DSH disproportionate share

DUR drug utilization review

DVT deep vein thrombosis

E&M evaluation and management

EHR electronic health record

EPO erythropoietin

ESRD end-stage renal disease

ER emergency room

FDA Food and Drug Administration

FDG fluorodeoxyglucose F18

FDG–PET (18)F-fluorodeoxyglucose and positron 

emission tomography

FEHB Federal Employees Health Benefits [Program]

FFS fee-for-service

FIMTM Functional Independence Measure

FPL federal poverty level

GAF geographic adjustment factor

GAO Government Accountability Office [formerly

General Accounting Office]

GDP gross domestic product

gFOBT guaiac-based fecal occult blood test

GI gastrointestinal

GME graduate medical education

GPCI geographic practice cost index

GPO group purchasing organization

HbA1c hemoglobin A1c

HCC hierarchical coexisting condition

HCC hierarchical condition category

HCCA health care commuting area

HCFA Health Care Financing Administration

HCPCS Healthcare Common Procedures Coding System

HCPP health care prepayment plan

HCL hydrochloride

HEDIS Health Plan Employer Data and Information Set

HIV human immunodeficiency virus

HHA home health agency

HHRG home health resource group

HHS Department of Health and Human Services

HMO health maintenance organization

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 217

Acronyms
HOS Health Outcomes Survey

HOPD hospital outpatient department

HRR hospital referral region

HSA health savings account

HSA health service area

HSCRC Health Services Cost Review Commission

HWI hospital wage index

ICD–9–CM International Classification of Diseases, Ninth

Revision, Clinical Modification

ID identification

IDTF independent diagnostic testing facility

iFOBT immunochemical fecal occult blood test

IHS Indian Health Service

IME indirect medical education

IN indium

IOM Institute of Medicine

IPF inpatient psychiatric facility

IPPS inpatient prospective payment system

IRF inpatient rehabilitation facility

IRF–PAI Inpatient Rehabilitation Facility–Patient

Assessment Instrument

IV instrumental variable

IV intravenous

JCAHO Joint Commission on Accreditation of Healthcare

Organizations

LOS length of stay

LTCH long-term care hospital

M+C Medicare+Choice

MA Medicare Advantage

MA–PD Medicare Advantage–Prescription Drug [plan]

MAF medical assistance facility

MCBS Medicare Current Beneficiary Survey

MDS Minimum Data Set

MedPAC Medicare Payment Advisory Commission

MedPAR Medicare Provider Analysis and Review file

MEI Medicare Economic Index

MEPS Medical Expenditure Panel Survey

MMA Medicare Prescription Drug, Improvement, and 

Modernization Act of 2003

MRI magnetic resonance imaging

MSA metropolitan statistical area

MSA medical savings account

MTMP medication therapy management program 

N/A not applicable, not available

NCQA National Committee for Quality Assurance

NDC national drug code

NHS National Health Service

NICE National Institute for Health and Clinical

Excellence (United Kingdom)

NIDDK National Institute of Diabetes and Digestive and

Kidney Diseases

NIOSH National Institute for Occupational Safety 

and Health

NORC National Opinion Research Center

NRC Nuclear Regulatory Commission

NRHA National Rural Health Association

NTA nontherapy ancillary

OASDI Old-Age, Survivors, and Disability Insurance

OASIS Outcome and Assessment Information Set

OIG Office of Inspector General

OMB Office of Management and Budget

P&T pharmacy and therapeutics

PAC post-acute care

PACE Program of All-Inclusive Care for the Elderly

PAI patient assessment instrument

PBM pharmacy benefit manager

PCT pragmatic, or practical, clinical trial

PDA personal digital assistant

PDP prescription drug plan

PET positron emission tomography

PFFS private fee-for-service

PhRMA Pharmaceutical Research and 

Manufacturers of America

PIP–DCG principal inpatient diagnostic cost group

PLI professional liability insurance

POS point of service

PPE personal protective equipment

PPI producer price index 

PPO preferred provider organization

PPRC Physician Payment Review Commission

PPS prospective payment system

PRO peer review organization

PSI patient safety indicator

QALY quality-adjusted life year

QIO quality improvement organization

QMB Qualified Medicare Beneficiary

RBC red blood cell

RPCH rural primary care hospital

RUC Relative Value Scale Update Committee

RUCA Rural–Urban Commuting Area

218 Acronyms
RUG resource utilization group

RUG–III resource utilization group, version III

RVS relative value scale

RVU relative value unit

SCHIP State Children’s Health Insurance Program

S/HMO social health maintenance organization

SGR sustainable growth rate

SHIP State Health Insurance Assistance Program

SLMB Specified Low-Income Medicare Beneficiary

SNF skilled nursing facility

SNOMED Systematized Nomenclature of Medicine

SNP special needs plan

SPAP State Pharmacy Assistance Program

SSA Social Security Administration

Tc technetium

TPN total parenteral nutrition

U.S. United States

U.S.C. United States Code

USP the U.S. Pharmacopeia

USPSTF U.S. Preventive Services Task Force

USRDS United States Renal Data System

VA Department of Veterans Affairs

WWAMI Washington, Wyoming, Alaska, Montana, 

and Idaho

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 219

More about MedPAC

Term expired April 2005

Nancy-Ann DeParle, J.D.

JPMorgan Partners

Washington, DC

David F. Durenberger, J.D.

National Institute of Health Policy

University of St. Thomas

Minneapolis, MN

Carol Raphael

Visiting Nurse Service of New York

New York, NY

Mary K. Wakefield, Ph.D.,

R.N., F.A.A.N.

Center for Rural Health

University of North Dakota

Grand Forks, ND

Nicholas J. Wolter, M.D.

Deaconess Billings Clinic

Billings, MT

Term expires April 2007

John M. Bertko, F.S.A.,

M.A.A.A.

Humana Inc.

Louisville, KY

Sheila P. Burke, M.P.A.,

R.N., F.A.A.N.

Smithsonian Institution

Washington, DC

Francis J. Crosson, M.D.

The Permanente Federation, LLC

Oakland, CA

Arnold Milstein, M.D., M.P.H.

Pacific Business Group on Health

San Francisco, CA

Ralph W. Muller, M.A.

University of Pennsylvania

Health System

Philadelphia, PA

William J. Scanlon, Ph.D.

Health policy consultant

Oak Hill, VA

Term expires April 2006

Autry O. V. “Pete” DeBusk

DeRoyal

Powell, TN

Glenn M. Hackbarth, J.D.

Alan R. Nelson, M.D.

American College of Physicians

Washington, DC

Robert D. Reischauer, Ph.D.

David A. Smith, M.Ed.

Demos

New York, NY

Ray E. Stowers, D.O.

Oklahoma State University 

College of Osteopathic Medicine

Tulsa, OK

Report to the Congress: Issues in a modernized Medicare program | June 2005 223

Commission members

Glenn M. Hackbarth, J.D., chairman

Independent consultant

Bend, OR

Robert D. Reischauer, Ph.D., vice chairman

The Urban Institute

Washington, DC

John M. Bertko, F.S.A., M.A.A.A., is vice president and

chief actuary for Humana Inc., where he manages the corporate

actuarial group and directs the coordination of work by actuaries

in Humana’s major business units, including public programs,

commercial, individual, and TRICARE. Mr. Bertko has extensive

experience with risk adjustment and has served in several public

policy advisory roles, including prescription drug benefit design.

He served the American Academy of Actuaries as a board

member from 1994 to 1996 and as vice president for the health

practice area from 1995 to 1996. He was a member of the

Actuarial Board for Counseling and Discipline from 1996

through 2002. Mr. Bertko is a fellow of the Society of Actuaries

and a member of the American Academy of Actuaries. He has a

B.S. in mathematics from Case Western Reserve University.

Sheila P. Burke, M.P.A., R.N., F.A.A.N., is the Smithsonian

Institution’s deputy secretary and chief operating officer. Before

joining the Smithsonian, she was executive dean and lecturer in

public policy at the John F. Kennedy School of Government,

Harvard University, Cambridge. From 1986 to 1996, Ms. Burke

was chief of staff for former Senate Majority Leader Bob Dole

and was elected secretary of the Senate in 1995. She currently

serves as a board member of the Kaiser Family Foundation, the

Kaiser Commission on Medicaid and the Uninsured, the

Academy for Health Services Research and Health Policy, the

American Board of Internal Medicine Foundation, WellPoint

Health Networks, Chubb Insurance, and the University of San

Francisco. She is a member of the Institute of Medicine and the

National Academy of Public Administration. She also sits on the

national advisory council at the Center for State Health Policy

and has chaired the National Academy of Social Insurance’s

project on Restructuring Medicare for the Long-Term. Ms. Burke

holds a B.S. in nursing from the University of San Francisco and

an M.P.A. from Harvard University.

Francis J. Crosson, M.D., is executive director of the

Permanente Federation of medical groups that make up the

physician component of Kaiser Permanente. He also cochairs the

Kaiser Permanente Partnership Group, the organization’s

management committee. He joined Kaiser Permanente in 1977. In

1988 he was appointed associate executive director of the

Permanente Medical Group and served in that position until his

current appointment. He also has experience with prescription

drug arrangements and has led efforts on comprehensive public

report cards on clinical quality, management of a drug formulary,

and adoption of a state-of-the-art electronic medical record. He

currently is chair-elect of the Board of Directors of the American

Medical Group Association. Dr. Crosson received his

undergraduate degree in political science from Georgetown

University and his M.D. degree from Georgetown’s School of

Medicine.

Autry O. V. “Pete” DeBusk is chairman, chief executive

officer, and founder of DeRoyal, a global supplier of medical

products and services in the acute care, patient care, wound care,

and original equipment manufacturing markets. Mr. DeBusk

formed his first company in 1970 with a patent he received on an

orthopedic product. In 1976 he consolidated his many product

lines into one company, DeRoyal Industries. A member of several

community organizations, Mr. DeBusk is also chairman of the

Board of Trustees at Lincoln Memorial University in Harrogate,

TN, as well as a founder of the Autry O. V. DeBusk facility, Boys

and Girls Club, Powell, TN. As an innovative leader in the

medical industry, he received a prestigious award from Duke

University in 2000 recognizing his original contributions to

orthopedic surgery. He received his B.S. degree from Lincoln

Memorial University and attended graduate school at the

University of Georgia.

Nancy-Ann DeParle, J.D., is a senior adviser to JPMorgan

Partners, LLC, and adjunct professor of health care systems at the

Wharton School of the University of Pennsylvania. From 1997 to

2000, she served as administrator of the Health Care Financing

Administration (HCFA), which is now the Centers for Medicare

& Medicaid Services. Before joining HCFA, Ms. DeParle was

associate director for health and personnel at the White House

Office of Management and Budget. From 1987 to 1989, she

served as the Tennessee Commissioner of Human Services. She

has also worked as a lawyer in private practice in Nashville, TN,

and Washington, DC. She is a trustee of the Robert Wood

Johnson Foundation and a board member of Accredo Health,

Cerner Corporation, DaVita, Guidant Corporation, Triad

Hospitals, and the National Quality Forum. Ms. DeParle received

a B.A. degree from the University of Tennessee; B.A. and M.A.

degrees from Oxford University, where she was a Rhodes

Scholar; and a J.D. degree from Harvard Law School.

David F. Durenberger, J.D., is president of Policy Insight,

LLC; senior health policy fellow at the University of St. Thomas

in Minneapolis, MN; and chairman of the National Institute of

Health Policy. He is also president of the Medical Technology

Leadership Forum and a member of the Kaiser Foundation

Commission on Medicaid and the Uninsured, the Board of the

National Committee for Quality Assurance, and the National

Commission for Quality Long Term Care. From 1978 to 1995, he

served as the senior U.S. Senator from Minnesota, as a member of

the Senate Finance Committee and chairman of its health

subcommittee. He was a member of the Senate Environment

Committee; Government Affairs Committee; and the committee

now known as the Health, Education, Labor, and Pensions

Committee. He chaired the Senate Select Committee on

Intelligence. Senator Durenberger is a graduate of St. John’s

University, received his J.D. degree from the University of

Minnesota, and served as an officer in the U.S. Army.

Report to the Congress: Issues in a modernized Medicare program | June 2005 225

Commissioners’ biographies
Glenn M. Hackbarth, J.D., is chairman of the Commission

and an independent consultant living in Bend, OR. He has

experience as a health care executive, government official, and

policy analyst. He was chief executive officer and one of the

founders of Harvard Vanguard Medical Associates, a

multispecialty group practice in Boston that serves as a major

teaching affiliate of Harvard Medical School. Harvard Vanguard

was created from the staff-model delivery system that was the

original core of Harvard Community Health Plan. Mr. Hackbarth

previously served as senior vice president of Harvard Community

Health Plan. From 1981 to 1988, he held positions at the U.S.

Department of Health and Human Services, including deputy

administrator of the Health Care Financing Administration. Mr.

Hackbarth received his B.A. from Pennsylvania State University

and his M.A. and J.D. from Duke University.

Arnold Milstein, M.D., M.P.H., is medical director of the

Pacific Business Group on Health (PBGH) and U.S. health care

thought leader at Mercer Human Resource Consulting. PBGH is

the largest health care purchasers coalition in the United States.

Dr. Milstein focuses on performance improvement methods for

large health care purchasers and providers, clinical performance

measurement, and the psychology of clinical performance failure.

He cofounded both the Leapfrog Group and the Consumer

Purchaser Disclosure Project, and heads clinical standards setting

for both initiatives. He is an associate clinical professor at the

University of California at San Francisco. Dr. Milstein has a B.A.

in economics from Harvard, an M.P.H. in health services

planning from the University of California at Berkeley, and an

M.D. degree from Tufts University. 

Ralph W. Muller, M.A., is chief executive officer of the

University of Pennsylvania Health System, one of the largest

academic health systems in the country. Most recently he served

as managing director of Stockamp & Associates, a hospital

consulting firm, and as a visiting fellow at the King’s Fund in

London. From 1985 to 2001, he was president and chief

executive officer of the University of Chicago Hospitals and

Health Systems. Before joining the hospital, he held senior

positions with the Commonwealth of Massachusetts, including

deputy commissioner of the Department of Public Welfare. Mr.

Muller is past chairman of the Association of American Medical

Colleges, past chairman of the Council of Teaching Hospitals 

and Health Systems, and past vice chairman of the University

Health System Consortium. He is past chairman of the National

Opinion Research Center, a social service research organization,

and serves on the board of the National Committee for Quality

Assurance. Mr. Muller received his B.A. in economics from

Syracuse University and his M.A. in government from 

Harvard University.

Alan R. Nelson, M.D., is an internist–endocrinologist who was

in private practice in Salt Lake City until he became chief

executive officer of the American Society of Internal Medicine

(ASIM) in 1992. After the merger of ASIM with the American

College of Physicians (ACP) in 1998, Dr. Nelson headed the

Washington office of ACP–ASIM until his semi-retirement in

January 2000 and now serves as special adviser to the executive

vice president and chief executive officer of ACP. He was

president of the American Medical Association from 1989 to

1990. Dr. Nelson also serves on the Board of Trustees of

Intermountain HealthCare, a large integrated health system whose

headquarters are in Salt Lake City. A member of the Institute of

Medicine (IOM) of the National Academy of Sciences, he serves

on the IOM Roundtable on Environmental Health Sciences

Research and Medicine and was chairman of the study committee

on Racial and Ethnic Disparities in Health Care. Dr. Nelson

received his M.D. from Northwestern University.

Carol Raphael is president and chief executive officer of the

Visiting Nurse Service (VNS) of New York, the country’s largest

voluntary home health care organization. VNS programs include

post-acute and long-term care, rehabilitation, hospice, mental

health services, and a managed care plan for dually eligible

Medicare and Medicaid beneficiaries. Ms. Raphael developed the

Center for Home Care Policy and Research, which studies the

management, cost, quality, and outcomes of home- and

community-based services. Previously, Ms. Raphael served as the

executive deputy commissioner of the Human Resources

Administration in charge of the Medicaid and public assistance

programs in New York City. Ms. Raphael has served on several

Robert Wood Johnson Foundation advisory committees and New

York State panels, including the New York State Hospital

Review and Planning Council and the Medicaid Reform Task

Force. She is on the boards of Lifetime Healthcare, Future Health,

and the American Foundation for the Blind and is a member of

the Pfizer Hispanic Advisory Board and the Kaiser Permanente

Planning Group for Geriatric Care. She was a Visiting Fellow at

the King’s Fund in London and is a fellow of the New York

Academy of Medicine. She has an M.P.A. from Harvard

University’s Kennedy School of Government.

Robert D. Reischauer, Ph.D., is vice chairman of the

Commission and president of The Urban Institute. Previously, he

was a senior fellow with the Brookings Institution, and from 1989

to 1995 he was the director of the Congressional Budget Office.

Dr. Reischauer currently serves on the boards of the Academy of

Political Sciences, the Center on Budget and Policy Priorities, and

the Committee for a Responsible Federal Budget. He also is a

member of the Institute of Medicine, the National Academy of

Public Administration, and Harvard Corporation. Dr. Reischauer

received his A.B. degree from Harvard College and his M.I.A.

and Ph.D. from Columbia University.

William J. Scanlon, Ph.D., is a health policy consultant. 

Until April 2004, he was managing director of health care 

issues at the General Accounting Office (now the Government

Accountability Office [GAO]). At GAO, he oversaw

congressionally requested studies of Medicare, Medicaid, the

private insurance market and health delivery systems, public

health, and the military and veterans’ health care systems. Before

joining GAO in 1993, he was co-director of the Center for Health

226 Commissioners’ biographies
Policy Studies and an associate professor in the Department of

Family Medicine at Georgetown University and had been a

principal research associate in health policy at The Urban

Institute. His research at Georgetown and The Urban Institute

focused on the Medicare and Medicaid programs, especially

provider payment policies, and the provision and financing of

long-term care services. He has been engaged in health services

research since 1975. Dr. Scanlon has published extensively and

has served as a frequent consultant to federal agencies, state

Medicaid programs, and private foundations. He has a Ph.D. in

economics from the University of Wisconsin at Madison.

David A. Smith, M.Ed., is a senior fellow at Demos, a New

York-based public policy research center. He previously served

as director of the Public Policy Department at the AFL–CIO.

Prior to joining the AFL–CIO, he served as senior deputy budget

director and as commissioner of economic development for the

City of New York. Mr. Smith spent most of the 1980s in

Washington as an aide to Massachusetts Senator Edward M.

Kennedy and as a senior economist at the Joint Economic

Committee. Mr. Smith has taught economics and public policy at

the University of Massachusetts and the New School for Social

Research and is a senior fellow at the Century Foundation. He is a

member of the Board of Directors of Public Campaign and a

fellow of the National Academy of Social Insurance. Mr. Smith

attended Tufts University and received an M.Ed. from Harvard

University.

Ray E. Stowers, D.O., is director of the Oklahoma Rural

Health Policy and Research Center as well as associate dean of

rural health in the Department of Family Medicine at Oklahoma

State University Center for Health Sciences. He was in private

rural practice for 25 years at Family Medicine Clinics, Inc., in

Medford, OK, and serves on the Policy Board of the National

Rural Health Association. Dr. Stowers is a member of the Board

of Trustees of the American Osteopathic Association and has

served that organization in many capacities, including several

related to physician coding and reimbursement issues. He has

been on the Physician Payment Review Commission and was a

founding member of the American Medical Association’s

Relative Value Update Committee. Dr. Stowers received B.S. and

B.A. degrees from Phillips University in Oklahoma and his D.O.

degree from the University of Health Sciences College of

Osteopathic Medicine in Kansas City, Missouri.

Mary K. Wakefield, Ph.D., R.N., F.A.A.N., is director of

and professor at the Center for Rural Health at the University of

North Dakota. Dr. Wakefield has held administrative and

legislative staff positions in the U.S. Senate and served on many

public and private health-related advisory boards. Dr. Wakefield

is a member of the Institute of Medicine of the National Academy

of Sciences and serves on the Committee on Quality Health Care

in America. She is a fellow of the American Academy of

Nursing. She has served on a number of rural health–related

committees, including the National Advisory Committee on Rural

Health, Office of Rural Health Policy, and Health Resources and

Services Administration. Dr. Wakefield received her B.S. in

nursing from the University of Mary, Bismarck, North Dakota,

and her M.S. and Ph.D. from the University of Texas at Austin.

Nicholas J. Wolter, M.D., is a pulmonary and critical care

physician who serves as chief executive officer for Deaconess

Billings Clinic (DBC) in Billings, Montana. DBC is a regional,

not-for-profit medical foundation consisting of a multispecialty

group practice, tertiary hospital, critical access hospital affiliates,

health maintenance organization, research division, and long-term

care facility serving a vast rural area in the northern Rockies. Dr.

Wolter began his Billings Clinic practice in 1982 and served as

medical director of the hospital’s intensive care unit from 1987 to

1993. He began his leadership role with the successful merger of

the clinic and hospital in 1993. Dr. Wolter is a diplomate of the

American Board of Internal Medicine and serves on the boards of

many regional and national health care organizations. He has a

B.A. degree from Carleton College, an M.A. degree from the

University of Michigan, and an M.D. degree from the University

of Michigan Medical School.

Report to the Congress: Issues in a modernized Medicare program | June 2005 227

Mark E. Miller, Ph.D.

Executive director

Sarah Thomas, M.S.

Deputy director

Special assistant to the 

executive director

Annissa McDonald

Administrative staff

Reda H. Broadnax, B.S., 

Executive officer

Wylene Carlyle

Mathew Chase

Diane E. Ellison

Donna M. Fletcher

Tina Jennings, MTESL

Plinie (Ann) Johnson

Cynthia Wilson

Analytic staff

Jack Ashby, M.H.A.

Jill Bernstein, Ph.D.

Cristina Boccuti, M.P.P.

Niall Brennan, M.P.P.

Sharon Bee Cheng, M.S.

David V. Glass, M.S.

Timothy F. Greene, M.B.A.

Scott Harrison, Ph.D.

Kevin J. Hayes, Ph.D.

Sally Kaplan, Ph.D.

Kathryn Linehan, M.P.H.

Craig K. Lisk, M.S.

Karen Milgate, M.P.P.

Nancy Ray, M.S.

Rachel Schmidt, Ph.D.

Joan Sokolovsky, Ph.D.

Jeffrey Stensland, Ph.D.

Ariel Winter, M.P.P.

Chantal Worzala, Ph.D.

Daniel Zabinski, Ph.D.

Research assistants

Chad Ellimoottil

Margo Harrison

Sarah Kwon

Re p ort to the Congress: Issues in a modernized Medicare p rogram | June 2005 229

Commission staff

601 New Jersey Avenue, NW • Suite 9000 • Washington, DC 20001

(202) 220-3700 • Fax: (202) 220-3759 • www.medpac.gov