Has pay-for-performance decreased access for
minority patients?
Andrew Ryan, Ph.D.
Schneider Institute for Health Policy,
The Heller School for Social Policy and Management,
Brandeis University
Acknowledgements
• Support
• Agency for Healthcare Research and
Quality
• Jewish Healthcare Foundation
2
Outline
• Potential unintended consequences of
pay-for-performance
• Pay-for-performance and disparities
• Methods
• Results
• Policy implications
3
Patient avoidance in pay-for-performance
• Patient avoidance, or “cream skimming”, occurs
when providers determine that it is in their interest
to avoid treating patients who are likely to reduce
provider performance on a publicly reported or
financially incentivized quality measure
•
In the absence of complete risk adjustment, providers
may engage in statistical discrimination: the applying of
perceived group characteristics to individuals (McGuire
et al. 2008)
• Documented extensively in the public quality reporting
literature (Burack et al. 1999; Dranove et al. 2003;
Epstein 2006; Narins et al. 2005)
4
Minority patients may be avoided in
pay-for-performance
•
Racial and ethnic minority patients may be perceived to
have higher unmeasured risk than non-Hispanic White
(henceforth "White") patients, in P4P and public quality
reporting programs.
• A study by Werner, Asch, and Polsky (2005) found that
disparities in rates of CABG procedures increased for
Black and Hispanic patients, relative to White patients,
after the implementation of the New York CABG public
quality reporting program.
•
Despite concerns raised by several authors (Casalino
et al. 2007, Chien et al. 2007; Hood 2007), there is no
empirical evidence on the effect of P4P programs on
patient avoidance.
5
The Premier Hospital Quality
Incentive Demonstration (PHQID)
•
•
•
•
•
•
Collaboration between Premier Inc. and CMS
Implemented in 4th quarter of 2003, continues today
Of the 421 hospitals (approximately 12% of IPPS hospitals) asked to
participate in the PHQID, 266 (63%) chose to participate (Lindenauer
et al. 2007)
Pays a 2% bonus on Medicare reimbursement rates to hospitals
performing in the top decile of a composite quality measure
Pays 1% bonus for hospitals performing in the second decile (80th 90th percentile) of a composite measure
Incentivized conditions
• Acute myocardial infarction (AMI)
• Heart failure
• Community-acquired pneumonia
• Coronary-artery bypass graft (CABG)
• Hip and knee replacement
Data and Methods
7
Data
• Medicare fee-for-service inpatient claims and
denominator files (2000-2006)
• Primary diagnoses for which beneficiaries were
admitted
• Secondary diagnoses, demographics, and type
of admission for risk adjustment
• Zip codes to link beneficiaries to HRRs in
which PHQID hospitals operated
• Source of inpatient admission
• Medicare provider of service files (2000-2006)
• Hospital characteristics
8
Methods
•
•
•
Evaluate the avoidance of minority patients with AMI,
heart failure, and pneumonia
Use patient and hospital zip codes to identify Medicare
beneficiaries living in hospital referral regions (HRR) of
PHQID hospitals.
For each condition for each race (White, Black,
Hispanic, Other race):
• Use linear probability model to estimate conditional
probabilities that patients living in these HRRs
receive care at PHQID hospitals before and after
the program as a function of:
• Beneficiary characteristics (Age, gender, race,
Elixhauser comorbidities)
• HRR fixed effects
• Test difference-in-differences:
• (Minority post – Minority pre) – (White post –
White pre)
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Methods continued
•
•
•
Hospital admission can occur through three sources:
• Emergency department
• Physician referral
• Transfer from other facility
Use multinomial logit model to estimate conditional
probability that patient is admitted from each source
(ED, referral, or transfer) to PHQID or non-PHQID
hospital (6 outcomes) before and after program as a
function of:
• Beneficiary characteristics (age, gender, race,
Elixhauser comorbidities)
For each source of admission, test difference-indifference-in-differences:
• [(Minority PHQID post – Minority PHQID pre) –
(Minority non-PHQID post – Minority non-PHQID pre)] –
[(White PHQID post – White PHQID pre) –
(White non-PHQID post – White non-PHQID pre)]
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Standard Error specification
• Multiple observations from same HRRs over
time give rise to group-level
heteroskedasticity
• Cluster-robust standard errors are estimated
(Williams 2000)
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Results
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Descriptive statistics
AMI
n
Age (mean)
White
Black
Hispanic
Other race
Non-White
1,190,474
139,785
24,149
31,048
194,982
75.7
71.7
74.3
73.4
72.3
Female (%)
Comorbidities (mean)
47.9
56.1
49.3
44.6
53.4
1.69
1.94
1.89
1.76
1.90
Admission through ED (%)
63.7
70.3
71.6
62.4
69.2
2,361,893
561,146
65,163
62,897
689,206
77.6
69.7
74.0
73.6
70.5
Heart failure
n
Age (mean)
Female (%)
Comorbidities (mean)
56.0
58.6
56.0*
52.7
57.8
1.92
2.07
2.11
1.97
2.07
Admission through ED (%)
67.1
72.6
75.2
65.2
72.1
2,226,619
288,399
50,732
66,648
405,779
76.6
70.7
74.2
74.7
71.8
Pneumonia
n
Age (mean)
Female (%)
Comorbidities (mean)
54.3
55.1
53.5
49.0
53.9
2.63
2.66
2.60
2.49
2.62
Admission through ED (%)
69.1
73.8
74.1
64.7
72.3
Note: *p >.05
Note: Test performed is Wald test of difference versus White
13
Proportion of admissions in PHQID hospitals
0
.05
.1
.15
.2
Adjusted Proportion of Admissions
to PHQID hospitals: AMI
.208 .211
.209
.214
.213
.206 .207
.2
.176 .179
.002
White
Black
.001
Hispanic
Pre
Post
-.015
Other
-.001
Minority
DID
Note: Orange triangle denotes significant effect
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Proportion of admissions in PHQID hospitals
0
.05
.1
.15
.2
Adjusted Proportion of Admissions to
PHQID hospitals: Heart Failure
.175 .177
.183
.188
.179
.17 .167
.158 .161
.003
White
Black
Pre
.183
.001
Hispanic
Post
-.005
Other
.002
Minority
DID
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Proportion of admissions in PHQID hospitals
.05
.1
.15
.2
Adjusted Proportion of Admissions to
PHQID hospitals: Pneumonia
.163 .163
.166 .168
.16 .163
.151 .153
.145
.138
.008
.002
.003
0
.002
White
Black
Pre
Hispanic
Post
Other
Minority
DID
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Source of Admission Analysis: AMI
.6
Emergency Department
Emergency Department
.559
.569
Proportion of AMI patients
.2
.4
.533 .531
Referral
Referral
.162 .154
.152 .142
.127 .129
.102 .096
.037 .035
.031 .032
.011
.006 -.005
0
.003
White
Non-PHQID Pre
PHQID Post
-.016 -.02
Other
Non-PHQID Post
DID
PHQID Pre
DIDID
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Summary of findings
• Analysis shows small reduction in the
proportion of “other race” patients admitted to
PHQID hospitals for AMI after the program.
• No effects observed for other races
• No effects observed for heart failure or
pneumonia
• Reduction in admissions driven by:
• Reduction in PHQID hospital ED use for
“other race” patients, although not
significant
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Conclusions & Policy implications
• Little evidence of minority patient
avoidance in the PHQID
• Patient avoidance may vary based on
design of P4P program
• P4P may have other unintended
consequences
• Unintended consequences of P4P
should continue be monitored
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