academy health june 27, 2005 boston, ma romana hasnain-wynia, ph.d
DESCRIPTION
Disparities in Inpatient Quality of Care Measures by Race and Ethnicity ____________________________. Academy Health June 27, 2005 Boston, MA Romana Hasnain-Wynia, Ph.D. Health Research and Educational Trust. Co-authors. David W.Baker, MD, MPH Raj Behal, MD, MPH Joe Feinglass, PhD - PowerPoint PPT PresentationTRANSCRIPT
Disparities in Inpatient Quality of Care Measures by Race and Ethnicity
____________________________
Academy HealthJune 27, 2005Boston, MA
Romana Hasnain-Wynia, Ph.D.Health Research and Educational Trust
Co-authors
• David W.Baker, MD, MPH
• Raj Behal, MD, MPH
• Joe Feinglass, PhD
• David Nerenz, PhD
• Joel S. Weissman, PhD
PROJECT
Linking Race and Ethnicity Data to Inpatient Quality of Care Measures
Funding: The Commonwealth Fund
Background
• Hospital Quality Alliance– One of many efforts in CMS’s overall Hospital Quality
Initiative to foster hospital quality improvement through a variety of quality measurement and improvement opportunities
– >4,000 hospitals participating
• Focus on Three Conditions– Acute Myocardial Infarction (AMI)– Heart Failure– Pneumonia
Background
• Evidence indicates that quality improvement efforts, when linked to data on race and ethnicity, can reduce disparities in care and improve quality– Mukamel and Mushlin “Quality of Care Information Makes a
Difference: An Analysis of Market Share and Price Changes Following Publication of the New York State Cardiac Surgery Report Care.” Medical Care; 36:1998
– Schneider and Lieberman “Publicly Disclosed Information About the Quality of Healthcare: Response to the US Public.” Quality in Health Care. 2001
Background
• Health care disparities should be brought into the mainstream quality assurance and continuous quality improvement discussions– Fiscella, et al. “Inequality in Quality: Addressing
Socioeconomic, Racial, and Ethnic Disparities in Health Care. JAMA. 2000
Data Source
• University Health System Consortium (UHC)– UHC is an alliance of academic health centers in the
United States aimed at improving performance levels in clinical, operational, and financial areas.
– UHC is collecting the quality measures for the three conditions with patient race and ethnicity information for 123 hospitals.
– We are working with UHC to conduct analyses.
– >7,000 cases per condition
Methods
• Create performance quintiles• Present data by % racial minorities seen at
hospitals in each quintile• Exclusion if <50 total cases or <15 minority cases• Develop multivariate models
– Model 1: unadjusted
– Model 2: adjusted for individual characteristics, including co-morbidities, payer, age, gender
– Model 3: Model 2 + adjusted for organizational effects (between hospital variation)
Performance quintiles by % minority patients seen
0
1020
3040
5060
70
Smokingcessation
counseling
ASA atarrival
ASA at DC PCI w/in120 min
1st quintile 2nd quintile 3rd quintile 4th quintile 5th quintile
Rate-based measures(higher quintile = better performance)
% Minority AMI measures
Top and bottom quintiles by % minority patients seen
0
1020
3040
5060
70
Smokingcessation
counseling
ASA atarrival
ASA at DC PCI w/in120 min
1st quintile 5th quintile
Rate-based measures(higher quintile = better performance)
% Minority AMI measures
Top and bottom quintiles by % minority patients seen
0
10
20
30
40
50
60
70
Beta-blockeron arrival
ACEI forLVSD
DCinstructions
LVFassessment
1st quintile 5th quintile
Rate-based measures(higher quintile = better performance)
% Minority Heart Failure measures
Top and bottom quintiles by % minority patients seen
0
10
20
30
40
50
60
O2assessment
Vaccination Bloodcultures
Smokingcessation
1st quintile 5th quintile
Rate-based measures(higher quintile = better performance)
% Minority Pneumonia measures
Top and bottom quintiles by % minority patients seen
0
10
20
30
40
50
60
70
Abx w/in 8hrs
Abx w/in 4hours
Abx selectionin ICU
Abx selectionnon-ICU
1st quintile 5th quintile
Rate-based measures(higher quintile = better performance)
% Minority Pneumonia measures
Top and bottom quintiles by % minority patients seen
0
10
20
30
40
50
60
70
time tothrombolysis
Time to PCI Time toantibiotics
1st quintile5th quintile
Time-based measures(higher quintile = worse performance)
% Minority
Multivariate models adjusting for individual factors and hospital effects
AMI
Measures
Model 1
Unadjusted
Model 2
Adj. for demos, incl. co morbidities
Model 3
Adj. for between hospital effects
Smoking Cessation
-0.47 (-0.56—0.38) -0.47 (-0.58—0.37) -0.20 (-0.32—0.09)
B-Blocker at arrival
-0.18 (-0.30 --0.06) -0.20 (-.32—0.07) 0.03 (0.08—0.12)
B-Blocker at discharge
-0.29 (-0.39—0.19) -0.31 (-0.42—0.21) -0.05 (-0.14- 0.07)
Aspirin at arrival 0.05 (-0.16-0.21) 0.11 (-0.06-0.28) 0.23 (0.03-0.44)
Aspirin at discharge
-0.21 (-0.34--0.08) -0.17 (-.030—0.04) 0.11 (-0.04-0.26)
Multivariate models adjusting for individual factors and hospital effects
Heart Failure Measures
Model 1
Unadjusted
Model 2
Adj. for demos, incl. co morbidities
Model 3
Adj. for between hospital effects
Smoking Cessation
-0.34 (-0.42—0.26) -0.33 (-0.41—0.25) -0.14 (-0.24—0.04)
D/C Instructions -0.44 (-0.47—0.40) -0.41 (-0.45—0.37) -0.02 (-0.07-0.03)
Assess LV Function
-0.24 (-0.30—0.18) -0.25 (-0.31—0.18) 0.06 (-0.02-0.15)
Multivariate models adjusting for individual factors and hospital effects
Pneumonia Measures
Model 1
Unadjusted
Model 2
Adj. for demos, incl. co morbidities
Model 3
Adj. for between hospital effects
Smoking Cessation
-0.60 (-0.70—0.50) -0.57 (-0.67—0.47) -0.20 (-0.33—0.08)
Antibiotics w/in 4 hours
-0.28 (-0.32—0.23) -0.16 (-0.21—0.13) 0.10 (0.05 – 0.15)
Quality Challenges for the Underserved
Who You Are
Where You Go
Pt Centered Care for the Underserved
Quality in Underserved
Settings
Slide by A. Beal
Considerations• There is some within hospital variation
• There is clearly variation between hospitals with the data showing that performance on some of the CMS quality measures is poorer in hospitals serving a large number of minorities
• Examine hospital characteristics (payer mix, urban location, age of facility, etc…)
• Be careful. For example, what will be the outcome of Pay for Performance?
• Should quality improvement efforts focus on hospitals serving a large % of minority patients. Focus on factors amenable to improvement.
Policy Focus
“Policies designed to equalize patients’ treatment within hospitals will not erase disparities at the national level. What is necessary to erase health care disparities is to implement national policies designed to improve the overall treatment of all patients, which in turn will have a disproportionate effect on reducing racial,ethnic,and geographic disparities in health care and health outcomes.”
K. Baicker, A. Chandra, and J. S. Skinner (2005).“Geographic Variation in Health Careand the Problem of Measuring Racial Disparities.” Perspectives in Biology and Medicine.