Implications of The Medicare Prospective Payment System (PPS) for Small Dialysis Organizations

Fredric Finkelstein, MDAlan Kliger, MDHospital of St. RaphaelYale UniversityNew Haven, CT

John Kochevar, PhD Mark StephensKochevar Research Associates

Annotated ASN 2011 Presentation

Purpose

To determine :

• The financial impact of the PPS on small dialysis organizations.

• The consequences of gains/losses for treatment practices, facility sale or closure.

Background

• Facility patient costs and outcomes vary widely.

• Variations are due to patient and facility characteristics, geography, facility efficiency, etc.

• We focused on which facilities might gain or lose income, which patients were most costly, and what strategies were being considered to maintain financial solvency

BackgroundDetailed analysis of the CMS Facility Impact file showed high variation in PPS payments.

Average Avg System Average IncomeAvg Individual Range Individual

Ownership Type N Income (000) % Gain/Loss Gain/Loss (000) % Gain/Loss % Gain/Loss

LDO 3205 1,954$ -3.6% (70)$ -2.2% -26% to +87%

Regional Chain 651 1,799$ -0.1% (1)$ 1.4% -34% to +65%

Independent 516 1,667$ 0.9% 15$ 5.0% -38% to +80%

Hospital 576 1,629$ 3.6% 58$ 9.0% -24% to +110%

Total 4,948 1,865$ -2.0% (37)$ 0.4% -38% to +110%

The top quintile of income losing facilities will lose much more than 2% income.

Ownership NumberAverage

Income Loss % Income Loss

LDOs 641 264,000$ ███████████████-12.7%

Regional Chains 131 187,000$ █████████████-11.1%

Independents 103 179,000$ ███████████-9.6%

Hospitals 115 134,000$ █████████-7.7%

Total 990 230,000$ █████████████-11.6%

Methods Sample • Quota sample of SDOs selected by region, size, urbanicity

(rural, suburban, urban), chain status, % minority in zip code. • Randomly selected within cells. • Final sample: 41 Facilities, 3039 patients. Interviews• Four interviews each facility: facility characteristics,

treatment practices, financials, plans for changes. Patient Data• Form 2728. Comorbidity check list, 2009 treatments,

payments, EPO, Hgb, hospitalizations for 2009.

Methods Calculations• Calculated PPS payments for 2011 and subtracted from 2009

payments, up-dated for inflation.Cautions• Under-represents facilities in South, those at high risk.• The number of SDO facilities has declined since 2009.

Facilities Patients Region % % Midwest 34 33 Northeast 27 32 South Atlantic 7 4 South Central 10 7 West 22 24 Total 100% 100%

The Reality Check sample was older, more patients were new to dialysis, and they had fewer comorbidities.than the CMS sample.

Total Patient Months

% of Total Patient Months

UM-KECC % of Total Patient

Months

Age: 18 - 44 2,641 10.0% 14.0%

45 - 59 6,653 25.2% 25.2%

60 - 69 6,211 23.5% 23.2%

70 - 79 6,302 23.8% 25.1%

80 + 4,637 17.5% 12.3%

Underweight (BMI < 18.5) 1,149 4.3% 3.9%

Duration of renal replacement therapy < 4 months 1,642 6.2% 5.6%

Pericarditis (during prior 0-3 months)* 57 0.2% 0.4%

Pneumonia/Other Infections (during prior 0-3 months)* 487 1.8% 1.7%

Gastrointestinal bleeding (during prior 0-3 months)* 261 1.0% 1.2%

Hereditary hemolytic or sickle cell anemia* 223 0.8% 2.4%

Myelodysplastic syndrome* 73 0.3% 1.1%

Monoclonal gammopathy* 50 0.2% 1.4%

Total Patient Months 26,444 100.0% 100.0%Source: Patient 2728 Form, Clinical Comorbidity Form, and PPS Calculation ModelNote: Table percentages do not total to 100% because patients may be counted in multiple categories.UM-KECC % of patients from February 2008 UM-KECC report, based on 2002-2004 patient data.* Patients were counted if coded "Yes" on these conditions.

Patient Characteristics

Patient Characteristics

CMS Projected Income Reduction Present Study Sample Income Reduction2007 Data ¹ 2009 Data

• 4951 Facilities: - 2.0%• Top Quintile: -12.0%• Income reductions higher:

LDOsSouthMinority areas

¹ Final Rule, Table 35

Payment Reductions

• 41 facilities: - 5.1%• Top Quintile: - 15.3%• Income reductions higher:

RuralNortheast

Facilities in our sample were projected to lose more than the CMS average.

Many facilities in our sample reported cutting ESA use in 2009.

Payment Reductions

For 38 Facilities in Present Study

Impact File (2007) - $ 338,016 (-0.4%)

Our Calculations (2009) - $3,885,676 (-4.9%)

We double checked our calculation model and compared it to a similarmodel created for the NRAA. The payment reductions reported in theImpact file were not predictive of our sample’s reductions or others.

Average Income Gain/Loss/TxTotal N=3039 -$15Quintiles

1 -$1022 -$ 303 -$ 24 $ 21

5 $ 54

Average Annual Payments Per Patient

CR/SB Payments $26,930

PPS Payments $25,422

Difference -$ 1,508

Income Reductions Per Patient, Per Treatment

Facilities will lose income on a small portion of patients.

Patient Average Income Gains/Losses Per Treatment By Quintile

Income Losses/Gains by QuintileN 607

Biggest Reductions

608 608 608 608Biggest Gains

Avg $ Change in Income per Tx

- $101.63 - $30.08 - $1.81 $21.04 $54.46

% Died 2009 19.6% 14.6% 14.1% 10.9% 10.9%

% Black 38.4% 30.8% 27.1% 26.8% 24.1%

% Rural 14.5% 10.2% 8.2% 8.2% 11.0%

% New to Dialysis 9.1% 8.4% 9.9% 17.1% 46.9%

Characteristics not in the PPS accounted for large income gains and losses.

Rural

African American

3+ co-morbidites

< Age 65

Death during year

-35 -30 -25 -20 -15 -10 -5 0

-$31

Characteristics of Patients with Highest Income Losses Per Treatment

AVERAGE INCOME LOSS PER TREATMENT

-$18

-$18

-$24

-$26

Characteristics combined produced even higher income losses.

Comorbidities and ESA Use

Comorbidity PPS Adjustors Related to ESA Use p < 0.05

HIV X

Hemolytic/Sickle Cell Anemias X X

Cancer X

Diabetes X

Peripheral Vascular Disease X

SHPT X

Pneumonia X X

Septicemia X

GI Bleed X X

Inability to Ambulate X

Inability to Transfer X

Need assistance with ADL X

The PPS failed to include ESA related comorbidities.

Multiple Comorbidities and ESA Use

Number of ComorbiditiesTotal 0 1 2 3 4+

Patient N 3039 382 847 664 437 709

ESA $/Tx $51. $47. $47. $49. $50. $60.

ESA Units/Tx (000)

5.5 5.2 5.0 5.3 5.6 6.4

Gain/Loss /Tx $15 $3.8 $7.6 $12 $17 $30

The PPS case mix adjustors do not pay more for multiple comorbidities.

Facilities with sicker patients lost more money and it was not only because of ESA use.

Facility Loss /Gain Analysis

< -$26 -$25 to - $20 -$19 to -$9 -$8 to +$.24 >$ 0.25

Facility N 8 8 9 8 8

Patient N 446 827 642 649 430

% Patients losing > $5000 37% 23% 17% 13% 7%

Av. ESA Annual Costs $6660 $6160 $5080 $3780 $4510

Av. Hgb 11.5 11.4 11.4 11.5 11.3

% Black 45% 38% 19% 12% 36%

% 4+ Comorbidities 33% 23% 35% 20% 20%

% New to Dialysis 15% 18% 19% 21% 17%

Losses/Gains are due to an interaction of patient burden and facility practices.

Average Loss / Gain/ Tx by Facility

Note: All differences were statistically significant.

ESAs – Average Payments and Costs

PPS Bundle ESA Payment /Tx (2011)Base Rate $53With Adjustments $57

Average ESA /Tx Costs - Cost Reports 2009 LDOs $65MDOs $54SDOs $41

Average ESA/Tx Reimbursements 2009Sample SDOs $51

All costs / reimbursements adjusted to 2011 for inflation.

Financial HealthWill reduced Medicare revenues drive SDOs out of business?

Wide variation in % Medicare treatmentsAverage % Medicare treatments 73%Range 40-95%

Multiple sources of income, all in flux Medicare, Medicaid, HMOs, PPO, Copays, Nursing homes

Individual units have different revenue and cost profiles.

No clear patterns emerged. Some units can survive a 5% cut in Medicare revenue. Others will be in trouble and require subsidies, staff cuts or closure.

Responses to the Bundle: Positives

• No salary reductions• No further staff reductions, including nursing, social

work, and dietary support• No reductions in time spent with patients• No change in dialysis time• No facilities were considering immediate closure.

Final interviews with clinicians and financial managers.

Nearly total agreement:

• Likely more selective in admissions (40%) with admission of fewer charity cases (47%) and fewer non-compliant cases (45%).

• Likely more patients refused by other facilities (63%).

• Likely more patients remain in local hospitals (37%).

• Likely reduction in lab tests (80%).

• Likely reduction in equipment spending (65%).

Responses to the Bundle: Negatives Cost shifting and selectivity

Responses: Practice Changes

• Likely to change anemia protocol (90%) and to lower hemoglobin target (75%).

• Likely to change to subcutaneous EPO (68%).

• Likely to send more patients for transfusions (55%)

• More likely to send patients to hospital if they require costly medications (50%).

Response: Reevaluation of Practice Patterns• Likely reducing EPO will lead to more patients below

Hgb 10 (65%).

• But, impression is that reducing EPO and lowering Hgb target will not have negative impact on quality of life (65%), overall health (50%), and mortality of patients (80%)_

• Likely to increase use of cinacalcet (86%) and calcitriol (78%) and decrease use of paracalcitol (75%).

• Likely to increase home dialysis use (60%) but anticipate slow increase

• Likely to work with other physicians to improve pre dialysis care (74%).

PPS Challenges for SDOs

• The PPS is likely to cut payments more than 2%, much more for rural and minority facilities.

• Outlier payments and case mix adjustors do not work as planned.

• Facilities are cutting and shifting costs but this will not solve the problem of high cost patients.

• Few expect to close this year, but they are vulnerable to additional cuts in private insurance and Medicaid.

• The potential risk for patients and the health care delivery system needs to be more closely examined.