Steven Lieberman

Assistant Director

Health and Human Resources Division

Congressional Budget Office

Lowering Medicare Costs: Regions or Beneficiaries?

National Health Policy ConferenceJanuary 28, 2004

Contents

1. Empirical observations

2. Potential payoffs from two “naïve” interventions– High-cost beneficiaries– High-cost regions

3. Next steps– Policy questions to lower spending– Criteria for evaluating policy interventions

Empirical Observations

– More is not better Patients in high-spending regions received 60 percent more

care No better quality of or access to care If spending in all regions were lowered to levels in the lowest

decile, Medicare spending would fall by 29 percent

– Medicare spending is concentrated Most expensive 5 percent of beneficiaries accounted for 47

percent of total Medicare spending during 1995-1999

– Degree of concentration is similar across HRRs

– Many high spenders have persistently high spending 18 percent of beneficiaries were in the top quartile of spenders

in each year for at least two consecutive years during 1995-1999

Distribution of Medicare Spending and Beneficiaries

4%

30%

15%

37%

40%

15%

17%

1%

1%

40%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Beneficiaries Spending

Notes: Data from a 5 percent random sample of fee-for-service (FFS) beneficiaries between 1995 and 1999.

Concentration of Medicare Spending

Notes: Data from a 5 percent random sample of fee-for-service (FFS) beneficiaries between 1995 and 1999. Spending reported in 1999 dollars.

Medicare Spending

Beneficiaries % of Total Mean

Top Quintile 84% $24,161

Fourth Quintile

12% $3,353

Third Quintile 3% $943

Bottom Two Quintiles

1% $155

Total 100% $5,753

Medicare Spending

Beneficiaries % of Total Mean

Top 1 % 17% $98,074

Top 5 % 47% $53,538

Top 10 % 66% $37,855

Distribution of Medicare Spending among HRRs

19% 20% 19%

29% 29% 30%

16% 16% 17%

36% 36% 34%

0%

20%

40%

60%

80%

100%

TopQuintileHRRs

All HRRs BottomQuintileHRRs

Top 1%

Top 1-5%

Top 5-10%

Low 90%

Notes: Data from a 5 percent random sample of fee-for-service (FFS) beneficiaries between 1995 and 1999. Excluded are beneficiaries who could not be assigned an HRR.

Persistence of Medicare Spending

High Cost

27% of Benes

75% of Costs

Low Cost

73% of Benes

25% of Costs

Persistent

18% of Benes

57% of Costs

Not Persistent

9% of Benes

18% of Costs

60% Alive

End of Year 5

40% Dead

End of Year 5

Year 1 Cohort of Beneficiaries

Notes: CBO analysis in “Concentration and Persistence of Expenditures among Medicare Beneficiaries.” Persistently high-cost group is defined as those who were in top 25 % of spending for at least 2 consecutive years during the 5-year period, 1995-1999.

Profiles of Beneficiaries by Spending Group

Spending Group (Mean Spending)

Top 5 Percent ($53,538)

Top 20 Percent ($24,161)

Bottom 40 Percent ($155)

Inpatient PPS Spending / Beneficiary $25,309 $11,119 None

Physician Spending / Beneficiary $8,872 $4,934 $129

Chronic Conditions•Congestive heart failure•Diabetes•Cognitive impairment

47%

35%

20%

36%

29%

16%

6%

10%

3%

Notes: Data from a 5 percent random sample of fee-for-service (FFS) beneficiaries between 1995 and 1999. Spending reported in 1999 dollars.

Contents

1. Empirical observations

2. Potential payoffs from two “naïve” interventions– High-cost beneficiaries– High-cost regions

3. Next steps– Policy questions to lower spending– Criteria for evaluating policy interventions

Potential Payoffs from Targeting High-Cost Beneficiaries vs. High-Cost Regions

By Beneficiary By HRR

% of Beneficiaries

% of Spending % of Beneficiaries % of Spending

Top 1% 16.7 % Top 0.7 % 1.2 %

Top 5% 45.8 % Top 4.9 % 7.0 %

Top 10% 65.1 % Top 9.8 % 13.1 %

Top Quintile 83.5 % Top 19.4 % 24.4 %

Fourth Quintile 12.0 % Next 20.3 % 21.9 %

Third Quintile 3.4 % Next 20.1 % 19.6 %

Bottom Two Quintiles

1.2 % Bottom 40.2 % 34.0 %

Notes: Data from a 5 percent random sample of fee-for-service (FFS) beneficiaries between 1995 and 1999. Excluded are beneficiaries who could not be assigned an HRR.

Potential Payoffs from Targeting High-Cost Beneficiaries vs. High-Cost Regions

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Percent of Beneficiaries

Per

cen

t o

f E

xpen

dit

ure

s

Beneficiaries ordered from most to least expensive

Beneficiaries order from most to least intensive Region

Possible Policy Interventions

Intervention Target Possible Examples

High-Cost Regions •Establish and fund Comprehensive Centers for Medical Excellence (CCMEs)•Revise FFS payments to reward efficient care and reduce payments for HRRs with excessive supply-sensitive care

High-Cost Beneficiaries •Introduce case management/ disease management programs•Use risk screening/ predictive modeling

High-Cost Beneficiaries in High-Cost Regions

•Reduce the number of teaching hospital beds in high-cost HRRs•Case manage high-cost beneficiaries in high-cost HRRs

Possible interventions through reducing capacity, changing reimbursements and creating new programs

Challenges of the High-Cost Beneficiaries Approach

Generating savings from high-cost beneficiaries requires:

– Identifying who is, or will be, high cost Who survives but remains high cost? Could interventions change cost or outcome?

– Developing and implementing effective interventions Requires achieving lower costs or improved outcomes Should interventions be provider or patient focused?

– Rigorously demonstrating net savings Possibly use randomized control groups Capture costs of intervention and changes in benefit

spending

Challenges of High-Cost Regions Approach

Generating savings from high-cost HRRs requires:– Identifying who/ what will change practice patterns/ utilization

What to target? Could interventions cause changes in cost or outcome?

– Developing and implementing effective interventions Requires achieving lower costs or improved outcomes Where or on what should interventions be focused?

– Rigorously demonstrating net savings Possibly use randomized control groups Capture costs of intervention and changes in benefit spending

1. Empirical observations

2. Potential payoffs of two “naïve” interventions– High-cost beneficiaries– High-cost regions

3. Next steps– Policy questions to lower spending– Criteria for evaluating policy interventions

Contents

Policy Questions to Lower Spending

1. How best to identify excess spending?

2. What interventions would reduce excess spending?

3. How do we evaluate results of different policy interventions?

Criteria for Evaluating Policy Interventions

Criteria Regions Beneficiaries

Target efficiency Also include beneficiaries with low spending in high-cost regions

Target a small group of beneficiaries with very high spending

Number of people disrupted

Many Relatively few

Return on intervention

Possibly generate broad delivery system changes in utilization & savings within high-cost HRRs

Focus on persistently high spenders could lower their spending, but effect on system cost unknown