Transcript Document

USING RACE AND ETHNICITY DATA
AS TOOLS FOR QUALITY
IMPROVEMENT
Romana Hasnain-Wynia, PhD
GIH PHONE CONFERENCE
JUNE 7, 2005
What We Don’t Know
• Why and How disparities occur
- Quality of care hindered because of bias and
prejudice
- Quality of care hindered because of communication,
language, or cultural barriers
• Which interventions are effective at reducing or eliminating
disparities
• What proportion of observed disparities are amenable to
improvements in health care
• How to collect relevant data respectfully -- and when
Why HCOs Should Collect Data On Patient
Race/Ethnicity And Language
Internal Factors
•Valid and reliable data are fundamental building blocks for identifying
differences in care and developing targeted interventions.
• Being responsive to communities: Pressing community health problems
such as disparities in care can be addressed more effectively if health care
organizations and health professionals build the trust of the community by
documenting accomplishments.
•Link race and ethnicity information to quality measures to examine
disparities and undertake targeted interventions
•Ensure the adequacy of interpreter services, patient information materials,
and cultural competency training for staff
External Factors
•Federal and state reporting requirements e.g. CMS has
implemented policies to use race and ethnicity data for quality
improvement purposes, under Medicare + Choice managed care
plans are required to identify racial and ethnic disparities in
clinical practice
•Accreditation the Joint Commission on the Accreditation of
Healthcare Organizations and the National Committee for Quality
Assurance may require race/ethnicity data collection
Focus on data is good only insofar
that we remember:
“It is not the data, it is what you do with it”
-------Maryland Hospital Indicator Project
“ We can not manage what we can not measure.”
---David Kindig, M.D., M.P.H., University of Wisconsin School
of Medicine
Patient Experiences with the
Health Care System
Percent who say that they have felt that a doctor judged them unfairly
or treated them with disrespect because of ….
25
20
15
Whites
African American
Latinos
10
5
0
Ability to pay
Race/ethnicity
Speak English
Kaiser Family Foundation Survey of Race, Ethnicity, and
Medical Care, October 1999
Results
Hospitals that did not collect data on race and ethnicity were asked
why.
• Sixty-seven percent felt is was unnecessary
• No reliable system for data collection (18%)
• Lack of a good classification system (15%)
• Data too costly to maintain (7%)
• Data would be unreliable (7%)
• Not authorized by the hospital though it was legally (7%)
• Prohibited by law or external regulation (4%)
Barriers to Collecting Data
• Resource limitations
• Legal concerns
• Categorization
• System/organizational barriers
• Staff training
• Patients’ perceptions/language
and culture
• Validity and reliability of
data
Other Health Care Organizations
Medical Group Practices
• Less likely to collect race/ethnicity information than hospitals
• 75% didn’t collect data because they thought it was unnecessary or
That the collection was potentially disturbing to patients.
(Nerenz, et al. 2003).
Health Plans
•Health plans do not routinely capture information on race/ethnicity
of their members and do not assess quality of care stratified by race
and ethnicity (Nerenz, et al. 2002)
•AHIP notes that collection of data by health plans is fragmented.
•AHIP and RWJ study found that 74% of plans that responded to a
survey collect information on enrollment.
•Health plans cite same barriers to data collection
Study Questions
• How do people feel about being asked about
their race and ethnicity?
• Do attitudes change when they know the
rationale for collecting this data? (e.g., desire
to measure quality of care and ultimately
reduce disparities)?
• Do people prefer an open-ended format versus
choosing from a list of options?
*This pilot study was conducted at Northwestern University (NU) School of Medicine/
Northwestern Memorial Hospital (NMH).
NU/NMH site Principal Investigator, David W. Baker, MD, MPH
Most Patients Agreed That It Was Important to
Collect Race/Ethnicity Data
“It is important for hospitals & clinics to collect
information from patients about their race or
ethnic background.” Would you say that you:
Strongly Agree
Somewhat Agree
Unsure
Somewhat Disagree
Strongly Disagree
43%
37%
6%
10%
4%
NU/NMH pilot study, site Principal Investigator: David W.Baker, MD, MPH
Even Stronger Support that Hospitals
Should Examine Differences in Quality
“It is important for hospitals & clinics to conduct
studies to make sure that all patients get the same
high quality care regardless of their race or ethnic
background.” .” Would you say that you:
Strongly Agree
Somewhat Agree
Unsure
Somewhat Disagree
NU/NMH pilot study, site Principal Investigator: David W.Baker, MD, MPH
93%
4%
2%
1%
Significant Concerns About How This
Data Might Be Used
“How concerned would you be that this data could
be used to discriminate against patients?
Not concerned at all 34%
A little concerned
Somewhat concerned
Very concerned
15%
20%
31%
14% said somewhat/much less likely to go to a
hospital/clinic that collected race/ethnicity data.
NU/NMH pilot study, site Principal Investigator: David W.Baker, MD, MPH
Thoughts
• Open-ended questions appear to work well.
• Minimal time required to answer.
• Still, many patients uncomfortable.
• Separate question about Latino/Hispanic?
• Need to include questions on language barriers.
• No validation yet of back-end coding.
• Implementation/evaluation planned for NMH.
NU/NMH pilot study, site Principal Investigator: David W.Baker, MD, MPH
The Case For A Uniform Framework
• Eliminate current fragmentation in data systems within and across
HCOs
• Can serve as a tool for organizations to achieve comparability
• Can increase efficiency and accuracy and reduce redundancy and costs
• Provide a solid foundation for targeting quality of care initiatives and
reduce disparities.
• By linking clinical data with race/ethnicity and language, HCOs
would be able to track the care process and develop interventions that
target quality improvement efforts for their most vulnerable populations.
What Do We Need?
Reliable Race, Ethnicity and Language Data
•National Performance Measures
•Electronic Health Record Systems
What Do We Have:
•Health Plans—HEDIS quality measures
•Hospitals---CMS quality measures
•Ambulatory Care Setting-Ambulatory Care Performance
measures
Improving Quality For All Reduces
Disparities
The gap between blacks and whites in the adequacy of hemodialysis
dose decreased from 10% to 3%.
The gap between female and male patients decreased from 23% to
9%.
Source: Sehgal, Impact of Quality Improvement efforts on Race and Sex Disparities in Hemodialysis. JAMA,
Volume 289(8). Feb 26, 2003.996–1000.
Project Goals
• Measure disparities in inpatient quality of care for three
conditions (Acute Myocardial Infarction, Heart Failure,
Pneumonia).
• Assess hospital response to reporting these data (through
case studies)
• Assess the feasibility of implementing the Uniform
Framework for collecting race, ethnicity, and primary
language data at Northwestern Memorial Hospital
Project Team
•
Health Research and Educational Trust:
Principal Investigator (PI), Romana Hasnain-Wynia, PhD
Project Coordinator, Debbie Pierce
•
Northwestern Memorial Hospital:
Co-PI, David Baker MD, MPH
Co-Investigator, Joe Feinglass, PhD
•
Henry Ford Health System:
Co-PI, David Nerenz, PhD
•
Massachusetts General Hospital:
Co-PI, Joel Weissman, PhD
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.
3,793 hospitals are participating as of May 5, 2005.
Focus on three conditions
•Acute Myocardial Infarction
•Heart Failure
•Pneumonia
Ten Measures
Derived from evidence in the medical literature and tested extensively in the
hospital setting.
http://www.cms.hhs.gov/quality/hospital/
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.
• UHC is conducting analyses of these 123 hospitals for this
project.
• We are currently in the midst of data analyses.
Initial Analysis
• Looked at data from 89 hospitals
(time frame: Quarter 3 2002- Quarter 1 2004)
• Total Admissions, 118, 279
• We examined mean rates and median times (in minutes for
continuous measures) for each of the quality measures.
• In preliminary analyses, found differences in mean rates and
median times for measures requiring personal interaction with
patients.
Further Analyses Showed:
There are substantial disparities ACROSS hospitals for all the
measures. Those hospitals serving a high percentage of minority
patients do worse on all the measures…they are the poorer quality
hospitals based on these indicator.
Next:
•Examine disparities across hosp more carefully controlling for
clustering etc..
•Examine disparities within hosp
•Discuss the policy levers for both
•Will present at AcademyHealth in Boston end of June.
LET ME POINT OUT THAT….
•This work wouldn’t have been possible without race and
ethnicity data
•OR without national performance measures which are
uniformly collected
•EMR would make this endeavor easier but not all hospitals
are there yet…..
Closing Comments
•We have made headway but have a long way to go…
•Where next—pushing the envelop a bit
•Better data on patient demographics (not just r/e)
•Ability to link these data to performance measures in multiple
settings (health plan, hosp, ambulatory care) to REALLY look at
processes of care and health outcomes to truly target interventions
at the clearest points of vulnerability
•Movement to a National Health Information Technology system
EMR