Provider Monitoring and Pay-for-Provider Monitoring and Pay-for-Performance When Multiple Performance When Multiple Providers Affect Outcomes:Providers Affect Outcomes:

An Application to Renal DialysisAn Application to Renal DialysisRichard Hirth, PhDRichard Hirth, PhDMarc Turenne, PhDMarc Turenne, PhDJack Wheeler, PhDJack Wheeler, PhD

Qing Pan, MSQing Pan, MSJoseph Messana, MDJoseph Messana, MD

University of MichiganUniversity of Michigan

Funding: Centers for Medicare and Medicaid Funding: Centers for Medicare and Medicaid Services contracts 500-2006-0048C & 500-00-0028Services contracts 500-2006-0048C & 500-00-0028

BackgroundBackground

• Measuring and rewarding performance Measuring and rewarding performance is a major focus of U.S. health policy is a major focus of U.S. health policy – Monitoring/reportingMonitoring/reporting

• Inform quality assurance/improvement effortsInform quality assurance/improvement efforts• Inform consumers regarding choice of providerInform consumers regarding choice of provider

– Payment system designPayment system design•P4P ties financial rewards to measured P4P ties financial rewards to measured

performanceperformance•Capitation/bundling presume a provider’s Capitation/bundling presume a provider’s

influence on resource use and manage influence on resource use and manage associated risksassociated risks

Key question in designing Key question in designing measurement/reward systemsmeasurement/reward systems

• Who should be measured/rewarded?Who should be measured/rewarded?– Practices/protocols of multiple types of Practices/protocols of multiple types of

providers can affect outcomes or efficiencyproviders can affect outcomes or efficiency• e.g., hospital/surgical team/surgeone.g., hospital/surgical team/surgeon

– Ideally, measure and reward the provider(-s) Ideally, measure and reward the provider(-s) most able to affect relevant outcomesmost able to affect relevant outcomes

• However, selection of locus for However, selection of locus for measurement or reward has not been measurement or reward has not been empirically drivenempirically driven

ChallengesChallenges

• In principal, performance could be In principal, performance could be measured/rewarded at multiple measured/rewarded at multiple levels, but difficult in practicelevels, but difficult in practice– Identifying the “responsible” providersIdentifying the “responsible” providers– Small n’s/excessive financial risk at Small n’s/excessive financial risk at

some levelssome levels– Obtaining valid and clinically meaningful Obtaining valid and clinically meaningful

performance dataperformance data

Renal Dialysis ExampleRenal Dialysis Example

• Outcomes and resource utilization may reflect Outcomes and resource utilization may reflect practices that vary across both dialysis facilities practices that vary across both dialysis facilities and nephrologistsand nephrologists

• However, measurement (e.g., Dialysis Facility However, measurement (e.g., Dialysis Facility Compare) and QI efforts (e.g., ESRD Networks) Compare) and QI efforts (e.g., ESRD Networks) focus on the facility, as do P4P proposalsfocus on the facility, as do P4P proposals– Implicitly attributes responsibility to the facility for the Implicitly attributes responsibility to the facility for the

practices of non-employee physicianspractices of non-employee physicians– Without incentives at the physician level, opportunities Without incentives at the physician level, opportunities

to improve care and efficiency may not be fully realizedto improve care and efficiency may not be fully realized– Provides no guidance to patients regarding choice of Provides no guidance to patients regarding choice of

physicianphysician

Appropriateness of Renal Appropriateness of Renal Dialysis for Studying Locus of Dialysis for Studying Locus of MeasurementMeasurement• Patients have ongoing relationships with Patients have ongoing relationships with

institutional provider and physicianinstitutional provider and physician• Data availability (most patients covered by Data availability (most patients covered by

Medicare)Medicare)• Demographic and clinical data available for case-Demographic and clinical data available for case-

mix adjustmentmix adjustment• Discretionary resource use can be measured Discretionary resource use can be measured

(e.g., drugs and labs)(e.g., drugs and labs)• Guidelines-based quality measuresGuidelines-based quality measures• Active policy context (current proposals to bundle Active policy context (current proposals to bundle

more services into a PPS and develop P4P)more services into a PPS and develop P4P)

Research QuestionResearch Question

• How much of the variation in How much of the variation in resource utilization and outcomes is resource utilization and outcomes is attributable to the dialysis facility at attributable to the dialysis facility at which the patient is treated vs. the which the patient is treated vs. the nephrologist responsible for nephrologist responsible for outpatient, dialysis-related care?outpatient, dialysis-related care?

DataData

• Outpatient institutional and Outpatient institutional and physician/supplier claims for hemodialysis physician/supplier claims for hemodialysis patients with Medicare as the primary patients with Medicare as the primary payer in 2004 (1.9M patient-months)payer in 2004 (1.9M patient-months)

• Case-mix adjustersCase-mix adjusters– Demographics, body size, conditions present at Demographics, body size, conditions present at

onset of ESRD (Medical Evidence Form)onset of ESRD (Medical Evidence Form)– Approximately 40 diagnoses reported on claimsApproximately 40 diagnoses reported on claims

• Only recent claims used to define acute conditions Only recent claims used to define acute conditions (e.g., GI bleed)(e.g., GI bleed)

Outcome MeasuresOutcome Measures

• Resource utilizationResource utilization• Medicare Allowable Charges (MAC) per dialysis session Medicare Allowable Charges (MAC) per dialysis session

for services delivered in conjunction with dialysisfor services delivered in conjunction with dialysis– Injectable medications (primarily EPO, iron, vitamin D)Injectable medications (primarily EPO, iron, vitamin D)– Lab tests billed by facility or ordered by nephrologistLab tests billed by facility or ordered by nephrologist– Miscellaneous suppliesMiscellaneous supplies

• Societal perspectiveSocietal perspective– MAC include Medicare payment and patient copay MAC include Medicare payment and patient copay

obligationsobligations

• Clinical outcomesClinical outcomes• Anemia management: Hematocrit (Hct) ≥ 33%Anemia management: Hematocrit (Hct) ≥ 33%• Adequacy of dialysis: Urea reduction ratio (URR) ≥ Adequacy of dialysis: Urea reduction ratio (URR) ≥

65%65%

ProvidersProviders• For each patient-month, used PINs to For each patient-month, used PINs to

identify the dialysis facility billing the identify the dialysis facility billing the most sessions and the physician billing most sessions and the physician billing the Monthly Capitation Paymentthe Monthly Capitation Payment

• 85% random sample of facility-85% random sample of facility-physician pairs treating at least 5 physician pairs treating at least 5 patients selected for analysis (n=9994)patients selected for analysis (n=9994)– 24.6 patients and 151.2 patient-months 24.6 patients and 151.2 patient-months

per facility/physician pairper facility/physician pair

MethodsMethods

• Variance Components AnalysisVariance Components Analysis• Yijk = β’Xijk + γj + ηk + εijkYijk = β’Xijk + γj + ηk + εijk

– Yijk is the outcome for patient i under the care of physician j Yijk is the outcome for patient i under the care of physician j in facility kin facility k

– Xijk is a vector of characteristics of patient i with physician j Xijk is a vector of characteristics of patient i with physician j in facility kin facility k

– β is a vector of estimated regression coefficients for Xijk β is a vector of estimated regression coefficients for Xijk

– γj is physician j’s random intercept. For all patients cared for γj is physician j’s random intercept. For all patients cared for by physician j, their outcomes increase/decrease by a by physician j, their outcomes increase/decrease by a common amount γj. γj is distributed N(0,ξ2). common amount γj. γj is distributed N(0,ξ2).

– ηk is facility k’s random intercept which is distributed ηk is facility k’s random intercept which is distributed N(0,ω2)N(0,ω2)

– εijk is the residual after adjusting for all covariates and εijk is the residual after adjusting for all covariates and random effects for patient i with physician j in facility k, random effects for patient i with physician j in facility k, which is distributed N(0,σ2)which is distributed N(0,σ2)

Results: Selected Results: Selected CharacteristicsCharacteristics

VariableVariable % of Patients% of PatientsAge 70+Age 70+ 45.845.8

FemaleFemale 46.846.8

Non-whiteNon-white 43.743.7

<4 months of RRT<4 months of RRT 12.212.2

Congestive Heart FailureCongestive Heart Failure 32.732.7

Peripheral Vascular Peripheral Vascular DiseaseDisease

30.530.5

Septicemia w/in 6 Septicemia w/in 6 monthsmonths

14.614.6

Extent of Crossover Extent of Crossover between Facilities and between Facilities and PhysiciansPhysicians• To statistically distinguish facility and To statistically distinguish facility and

physician level variation, it is necessary physician level variation, it is necessary that some facilities have multiple that some facilities have multiple physicians or some physicians treat physicians or some physicians treat patients at multiple facilitiespatients at multiple facilities– In nearly 2/3 of facilities, more than one In nearly 2/3 of facilities, more than one

physician billed MCPs for physician billed MCPs for ≥≥ 5 patients (Figure 1) 5 patients (Figure 1)– More than half of physicians billed for More than half of physicians billed for ≥≥ 5 5

patients’ MCPs in multiple dialysis facilities patients’ MCPs in multiple dialysis facilities (Figure 2)(Figure 2)

Physicians per FacilityPhysicians per Facility

0

200

400

600

800

1000

1200

1400

1600

Fre

qu

ency

of

faci

litie

s

1 2 3 4 5 6 7 8 9 ≥10

Number of physicians per facility

Figure 1: Frequencies of Physicians per Facility

Facilities per physicianFacilities per physician

0

500

1000

1500

2000

2500

Fre

qu

ency

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ph

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1 2 3 4 5 6 7 8 9 11

Number of facilities per physician

Figure 2: Frequencies of Facilities per Physician

Outcomes varied at both the Outcomes varied at both the physician and facility levelsphysician and facility levels

•Each figure illustrates variation at the Each figure illustrates variation at the physician, facility, and patient levels as the physician, facility, and patient levels as the mean for the outcome variable +/- 1 SDmean for the outcome variable +/- 1 SD

• In each case, outcomes varied more at the In each case, outcomes varied more at the facility level than at the physician levelfacility level than at the physician level

• In each case, unexplained variation across In each case, unexplained variation across patients exceeded the variation at either of patients exceeded the variation at either of the provider levelsthe provider levels

Resource use per patientResource use per patient

Figure 4: Unexplained MAC ($) per session Attributable to Facilities and Physicians

mean+SD

mean+SD

mean+SD

mean mean meanmean-SD

mean-SD

mean-SD$20.00

$40.00

$60.00

$80.00

$100.00

$120.00

$140.00

Source of Variation

$ p

er

sessio

n

mean+SD $88.56 $101.25 $136.33

mean $81.80 $81.80 $81.80

mean-SD $75.04 $62.35 $27.27

Physician Facility Patients

% of patient months % of patient months w/Hctw/Hct≥≥3333

Figure 5: Unexplained % of Months with Hct>33 Attributable to Facilities and Physicians

mean+SDmean+SD

mean+SD

mean mean meanmean-SD

mean-SD

mean-SD50%

60%

70%

80%

90%

100%

Source of Variation

Perc

en

t o

f m

on

ths w

ith

HC

T>33

mean+SD 84% 87% 100%

mean 81% 81% 81%

mean-SD 78% 75% 52%

Physician Facility Patients

% of months with URR% of months with URR≥≥65%65%

Figure 6: Unexplained % of Months with URR>65 Attributable to Facilities and Physicians

mean+SD

mean+SDmean+SD

mean mean mean

mean-SD

mean-SD

mean-SD70%

75%

80%

85%

90%

95%

100%

Source of Variation

Perc

en

t o

f m

on

ths w

ith

UR

R>65

mean+SD 95% 99% 100%

mean 92% 92% 92%

mean-SD 89% 85% 71%

Physician Facility Patients

ConclusionsConclusions

• Because variation attributable to facilities is Because variation attributable to facilities is consistently larger, if monitoring/P4P targets only consistently larger, if monitoring/P4P targets only one type of provider, the facility is the appropriate one type of provider, the facility is the appropriate locuslocus

• Nonetheless, existence of variation across Nonetheless, existence of variation across physicians implies that quality reports, bundling physicians implies that quality reports, bundling and P4P may place facilities at risk for outcomes and P4P may place facilities at risk for outcomes they only partially controlthey only partially control

• Cooperation between managers and physicians to optimize Cooperation between managers and physicians to optimize outcomes and resource utilization will become increasingly outcomes and resource utilization will become increasingly important under P4P programs and proposed reforms to pay important under P4P programs and proposed reforms to pay prospectively for drugs and lab testsprospectively for drugs and lab tests

• Methods to align the incentives of dialysis facilities and Methods to align the incentives of dialysis facilities and nephrologists should be developednephrologists should be developed

ConclusionsConclusions• Financial impact of variation in resource Financial impact of variation in resource

use is largeuse is large• Facility-level SD of $19.45 per session translates to Facility-level SD of $19.45 per session translates to

$155,600 for a facility performing 8000 HD treatments $155,600 for a facility performing 8000 HD treatments annuallyannually

• If policy-makers and insurers can better If policy-makers and insurers can better understand sources of outcome variation, understand sources of outcome variation, they will be better able to develop incentive they will be better able to develop incentive systemssystems

• Likewise, such information can be used by Likewise, such information can be used by providers to anticipate and manage providers to anticipate and manage financial risks and opportunities under financial risks and opportunities under prospective payment and P4Pprospective payment and P4P

LimitationsLimitations

• Random effects identify the statistical contribution of Random effects identify the statistical contribution of providers to observed outcomes, but cannot distinguish providers to observed outcomes, but cannot distinguish differences arising from discretionary practices from differences arising from discretionary practices from those arising from unobserved case mix differencesthose arising from unobserved case mix differences– However, we control for a broader set of comorbidities than do However, we control for a broader set of comorbidities than do

the current, publicly reported dialysis facility outcomes datathe current, publicly reported dialysis facility outcomes data

• MAC is a utilization based measure of cost; actual input MAC is a utilization based measure of cost; actual input costs are not availablecosts are not available

• Standardized Mortality Ratios (SMRs) are also reported Standardized Mortality Ratios (SMRs) are also reported at the dialysis facility level but were not studied hereat the dialysis facility level but were not studied here– The factors studied here are likely to be more sensitive to The factors studied here are likely to be more sensitive to

provider practices than SMRsprovider practices than SMRs