1.
TRANSFORMING HEALTH CARE THROUGH RESEARCH AND EDUCATION
June 2012
Deborah Bohr, MPH
Andy Bostick, MA, MPP
Eliminating Health
Care Disparities:
Why and How

2.
Session Objectives
• Understand why hospitals must take the lead
in eliminating disparities in care
• Learn about the various dimensions of health
care disparities
• Review health facts for Robeson County
• Explore strategies for collecting REaL data
• Learn how to use REaL data to reduce health
care disparities and improve health equity

3.
BACKGROUND ON HEALTH
CARE DISPARITIES

4.
Elements of Quality Health Care
• Safe
• Effective
• Patient-Centered
• Timely
• Efficient
• Equitable

5.
STEEEP Examples
IOM Domain Examples
Safe Central Line infections
Timely Radiology turn-around times
Effective Appropriate discharge meds
Efficient Average length of stay
Equitable ???
Patient Centered Patient/employee satisfaction

6.
Disparities in Health Care
• Systematic review of a large
body of research found
significant variation in the rates
of medical procedures by race,
even when insurance status,
income, age, and severity of
conditions were comparable
• Findings indicated that minority
patients were less likely to be
given appropriate cardiac
medications or to undergo
bypass surgery, and are less
likely to receive kidney dialysis
or transplants. Conversely,
minority patients were more
likely to receive such as lower
limb amputations for diabetes
and other conditions.

7.
Disparities in Health Care
• Disparities still
exist:
• African Americans received
substandard care relative to
Whites for 41% of quality
measures
• Asians and American Indians
and Alaska Natives received
substandard care relative to
Whites for about 30% of quality
measures
• Hispanics received
substandard care relative to
non-Hispanic Whites for 39% of
measures

8.
Causes of Health Care Disparities
• Poor provider-patient communication
• Patient mistrust
• Stereotyping and bias
• Access to evidence-based practice

9.
National Call to Action to Eliminate Health Care
Disparities
• Joint effort of the American College of Healthcare
Executives, American Hospital Association, Association of
American Medical Colleges, Catholic Health Association of the
United States, and National Association of Public Hospitals and
Health Systems to eliminate health care disparities
• Goals include:
• Increase the collection of race, ethnicity and language
preference data
• Increase cultural competency training for clinicians and
support staff
• Increase diversity in governance and management

10.
ROBESON COUNTY
POPULATION FACTS

11.
Robeson County Population Composition
29.00%
24.30%
38.40%
0.70%
0.10%
2.50%
2010 Racial Demographic Data
White
African
American/Black
American Indian and
Alaska Native
Asian
Native Hawaiian and
Other Pacific Islander
Two or more races

12.
Robeson County Population Composition
8.1%
91.9%
2010 Ethnic Demographic Data
Hispanic or Latino
Non-Hispanic

13.
Racial Differences in Health Care Access
From NC Center for Health Statistics

14.
Racial Differences in Chronic Disease Incidence
From NC Center for Health Statistics

15.
Racial Differences in Mortality Rates
From NC Center for Health Statistics

16.
WHY ADDRESS HEALTH
CARE DISPARITIES?

17.
Ethical Case
• All medical centers and their staff want
to provide the same quality of care to
ALL their patients

18.
Business Case
• Quality differentials can affect HCAHPS
Scores, which has implications for hospital revenue
under value-based purchasing and pay-for-
performance models
• Disparities in care can be costly to hospitals as they
contribute to the following:
• Extended length of stay
• Preventable re-admissions
• Hospital-acquired conditions

19.
Risk Management Case
• Medical errors
• Poor or inadequate informed consent
• Discounting pain and suffering through
miscommunication
• Failure to recognize or take into
account the patient’s
cultural, religious, or ethnic beliefs

20.
Legal Case
• Section 4302 of the Affordable Care Act of
2010
• Medicare Improvements for Patients and
Providers Act of 2008
• Title VI of the Civil Rights Act of 1964
• Section 504 of the Rehabilitation Act of 1973
• Title II of the Americans with Disabilities Act
of 1990

21.
Quality Case
• SAFETY
• Communication difficulties may lead to misdiagnosis
and inappropriate treatment and limit the process of
truly informed consent
• EFFECTIVENESS
• Minority patients tend to receive fewer key
diagnostic and therapeutic procedures
• PATIENT CENTEREDNESS
• Minority patients are more likely feel they will receive
unequal treatment and are less satisfied with quality
of care they receive
• TIMELINESS
• Minority and LEP patients receive less timely care
which may lead to differences in quality

22.
Accreditation and Regulation Case
• Joint Commission
• National Quality Forum
• Community benefit and not-for-profit
status

23.
Current Realities, however…
• Sociocultural barriers:
• Language and nonverbal
communication
• Health practices and beliefs
• Role of family members in health
care decision-making
• Patient knowledge and expectations
of health system

24.
Beginning the Journey…
The quest to eliminate health care
disparities begins with the following:
• Leadership buy-in
• Understanding the health needs of the
communities you serve
• Incorporating this goal into your overall
quality improvement and strategic plans

25.
REDUCING DISPARITIES
THROUGH THE USE OF REAL
DATA

26.
What is REaL data?
• REaL data refers to the following
patient demographic information:
• Race
• Ethnicity
• Primary Language

27.
Why Define Race?
The purpose of defining race is to
provide common language to promote
uniformity and comparability for the
collection and reporting of race and
ethnicity.

28.
What is Race?
“ (Race) reflects self-identification by
persons according to the race or races
with which they most closely identify.
These categories are sociopolitical
constructs and should not be
interpreted as being scientific or
anthropological in nature.
Furthermore, the race categories have
both racial and national-group origins.”
(Source: National Center for Education Statistics Institute of
Education Services; http://nces.edu)

29.
OMB Race Categories
• The Race Categories are:
• American Indian or Alaska Native
• Asian
• African American or Black
• Native Hawaiian or Other Pacific
Islander
• White

30.
Useful, if not Perfect
• The OMB Categories are not perfect. The
race and ethnic categories were developed
by the federal government to be able to
monitor and help prevent discrimination in
housing, education and other areas.
• The U.S. Census uses these categories to
track the rapidly changing demographics in
the U.S.

31.
OMB Race Categories
Defined• American Indian or Alaskan Native: a person
having origins in any of the original people of
North and South America (including Central
America) and who maintains tribal affiliation
or community attachment.
• Asian: A person having origins in any of the
original peoples of Far East, Southeast Asia
or Indian subcontinent, including for
example, Cambodia, China, India, Japan, Ko
rea, Malaysia, Pakistan, the Philippine
Islands, Thailand, and Vietnam.

32.
OMB Race Categories
• African American or Black: A person having
origins in any of the black racial groups of
Africa.
• Native Hawaiian or Other Pacific Islander: A
person having origins in Hawaii or Pacific
Islands not specified in the Asian racial
category, e.g., Micronesia, Fiji, Tahiti

33.
OMB Race Categories
• White: A person having origins in any of the
original peoples of Europe, the Middle East
or North Africa.
HRET modification—Added Category:
• Multiracial: A person having origins in more
than one of the above categories. (Some
organizations allow the coding of up to 3
races.)
• Declined
• Unavailable (patient incapacitated)

34.
What is Ethnicity?
Ethnicity is a term which represents
social groups with a shared
history, sense of
identity, geography, and cultural roots
which may occur despite racial
difference.

35.
Defining Ethnicity
• Consider Puerto Ricans as an example
of an ethnicity. Many Puerto Ricans
represent various races.
• Ethnicity shapes a group's culture - the
food, language, music, and customs.
• For many patients, nationality or heritage
are synonymous with ethnicity.

36.
Why We Need Subpopulation
Data
• Race is a broad category. For
example, Native Hawaiians and Other Pacific
Islanders comprise more than 25 diverse
groups with various historical
backgrounds, languages, and cultural
traditions.
• Research has documented different health
risks and health status within smaller
population groups, e.g., Puerto Rican
individuals versus Honduran individuals.
Researchers need data on subgroups or
ethnicity.

37.
Ethnic Categories within
Race• American Indian or Alaskan Native
• Hopi, Navaho, Cree, Lumbee
• African American/Black
• Ethiopian, Kenyan, Dominican, Haiti
an, etc.
• White
• European, Middle
Eastern, Israeli, French, Irish, North
African

38.
Ethnic Categories within Race
• Native Hawaiian or Other Pacific Islander
• Polynesian, Samoan, Fijian, etc.
• Asian
• Asian Indian, Thai, Korean, Pakistani, etc.
• Multi-ethnic/Multiple, Unavailable, Declined

39.
English Proficiency
• How would you rate your ability to speak
English?
• Excellent, very good, good, fair, poor?
• Some hospitals collect these data via drop-
down screens like race and ethnicity by
registration or admitting staff

40.
Language Preference
Questions
• What language do you feel most
comfortable speaking?
• In what language would you prefer to
receive written materials?
• For minors, ask these questions of
parents or guardians
• These data are recorded via drop-down
screens like race and ethnicity by
registration/admitting staff

41.
Language Preference Tools

42.
Language Preference Tools
• “I-Speak” cards and point-to posters
help staff determine language
preferences of LEP individuals (A
Patient-centered Guide to
Implementing Language Services
Across Services in Healthcare
Organizations, www.omhrc.gov/Assets/
pdf/Checked/HC-LSIG.pdf)

43.
Deaf and Hard of Hearing Populations
• Effective communication is equally
important in this population;
miscommunication can lead to
misdiagnosis or delayed treatment.
• Many can speak even though they
cannot hear.
• People who are deaf or hard of hearing
use a variety of ways to communicate.

44.
Deaf and Hard of Hearing Populations
• Hospitals must provide a variety of services
and aids, depending on abilities of the
person:
• Sign language interpreters (various)
• Oral interpreters
• Cued speech interpreters
• CART—Computer Assisted Real-
time Transcription

45.
COLLECTING REAL DATA

46.
Explaining Why to the Patient
• Sample scripts are provided in
subsequent slides:
• Community responsiveness
• Quality of care
• Cultural competence
• A combination of the above

47.
Community Responsiveness Rationale
We want to know your
race, ethnicity, and preferred
language to help us develop
services to meet the needs of all
the populations we serve.

48.
Quality of Care Rationale
We want to make sure that all of
our patients get the best possible
care. We would like to ask you to
tell us your race, ethnicity, and
preferred language so that we can
review the treatment that all
patients receive and make sure
that everyone gets the highest
quality of care.

49.
Cultural Competence Rationale
We want to know the
race, ethnicity and preferred
language of each of our patients to
help us provide care that is
respectful of everyone’s cultural
background.

50.
Combination Rationale
We would like to know your
race, ethnicity and preferred language.
This will help us in a couple of ways. It
will help us… and … . (For example, it
will help us provide care that respects
your cultural background and will help
ensure that we provide the most
appropriate care and services to all our
patients.)

51.
Handling Patient Responses
• Some patients will question why they
are being asked for their ethnicity and
race.
• They will have questions and
comments.
• We want you to feel comfortable
answering whatever questions
patients ask.

52.
Patient Response Matrix
• The Patient Response Matrix is based
on actual patient responses other
hospitals have received to race/ethnicity
questions.
• The matrix is intended to be used as a
tool to help you respond in the best
possible manner.
• You may have more examples to add
and incorporate into the training of new
staff in coming months.

53.
Patient Responses—Routine
Patient Response Suggested Response Hints Code
“I'm American"
“Would you like to use an
additional term for race that is
listed on this card?” “I can code
American as well (for ethnicity).”
As patient
self-
identifies
"Can't you tell by looking at
me?"
“Well, usually I can. But sometimes
I'm wrong, so we think it is better to
let people tell us.”
As patient
self-
identifies
"I don’t know. What are the
responses?
“Please look at this card--you can
say white, Black or Africa-
American, Latino or Hispanic,
Asian, American Indian or Alaska
Native, Pacific Islander or Native
Hawaiian, some other race or any
combination of these.“
As patient
self-
identifies
"I was born in Nigeria, but I've
really lived here all my life.
What should I say?"
“Nigerian is great—we’ll list that as
your country of origin as well as
your ethnicity.” “Could you also
state your race as listed on this
card?”
As patient
self-
identifies

54.
Patient Responses—Routine
Code
Hispanic If
patient
declines to
list a separate
race, code
Preferred Not
to Answer in
Race slot.
Code
Hispanic
“The federal government has
designated Hispanic as an
ethnicity. I will record Hispanic
as your ethnicity. Do you also
want to list as race, as described
on this card?”
Thank you.”
“Why isn’t Hispanic a race?”
I am Latino/Latina/Puerto
Rican
Up to 3
races“Many people are multi-racial and
you can provide me with up to
three races that you see on this
card.”
I am more than one race—
how many can I list.”
N/A
“Administrators will see these
data and researchers may use
non-patient identified data for
their studies. No one else will
see these data.”
“How will this information be
used?”
CodeHintsSuggested ResponsePatient Response

55.
Returning Patients with Incomplete Data
Patient Response Suggested Response Code Hint
A patient returning for care
with the “Preferred Not to
Answer” code.
None—skip the race and ethnicity
questions
N/A—already
coded
Don’t
ask
again
A patient returning for care
with the “UN” or "Unable to
provide information" code.
Proceed to ask for the information
per routine

56.
Tougher Questions
Patient Response Suggested Response Code Hint
"I'm Human“ “Would you prefer not to
answer? If so, that is fine.”
Preferred Not to Answer or
Declined
Do not
say
Refused
"It's none of your
Business"
“I'll put down that you prefer not
to answer, which is fine.” “ “
"Why do you care?
We're all human
beings“
“Well, it is important for our
organization to know all of the
different populations we treat in
order to provide the most
appropriate services and the
most individualized care.”
“
DON'T SAY: I'll just code as a
refusal
“

57.
Tougher Questions
Patient Response Suggested Response Code Hint
What do you mean this is
part of your patient-
centered care approach?
“Everyone is unique and we want to
be sure that we know as much
about you as possible in order to
individualize your care.”
If patient declines
further
information, code
Preferred Not To
Answer or
Declined
"Who looks at this?"
“The only people who see this
information are registration staff,
administrators for the hospital and
the people involved in quality
improvement and oversight.”
“
"Are you trying to find out
if I'm a US citizen?“
“No. Definitely not. Also, you should
know that the confidentiality of what
you say is protected by law.”
“

58.
Top FAQs
• Why are data being collected about
race, ethnicity and language?
• This information helps us understand
the various patient populations we
serve. We want to provide the best
care to all our patients.
• It is also required by agencies that
oversee the care hospitals provide.

59.
Top FAQs
• How will data on race, ethnicity and
language affect my care?
• Your care will meet the highest
patient care standards. Information
about race and ethnicity will help
us… this answer will depend on the
rationale that the organization
selects.

60.
Top FAQs
• I am an American citizen; why are
race, ethnicity and preferred language
being asked?
• This information helps us to better
understand our various patient
populations, provide more culturally
competent care, and comply with
federal, state and accrediting
agencies.

61.
Top FAQs
• What is the difference between race
and ethnicity?
• Race reflects self-identification by
persons according to the race or
races with which they most closely
identify. Ethnicity is a term which
represents social groups with a
shared history, sense of
identity, geography and cultural roots
which may occur despite racial
differences.

62.
Top FAQs
• Why aren’t more races listed?
• A federal working group came up
with the list to meet the needs of 30
very diverse federal agencies. The
rationale was to have a relatively
short list of races and to allow for a
much greater list of ethnicities to
recognize unique religious, cultural
and geographic characteristics.

63.
Top FAQs
• What is the difference between
“Hispanic” and “Latino?”
• There is no difference. OMB accepts
Hispanic or Latino. However, for
ease of coding our organization has
chosen Hispanic. If patient responds
“Latino,” code as “Hispanic.”

64.
Top FAQs
• Why isn’t Hispanic a race?
• The Federal government decided that
some individuals of the White, Indian
(North, Central and South American),
and Black races would consider
themselves Hispanic because they speak
a common language (Spanish) and have
a common cultural heritage or ethnicity.
It was decided to consider Hispanic an
ethnicity, rather than a race. However,
many individuals will self-identify their
race as Hispanic.

65.
Top FAQs
• Why is “Pakistani” considered Asian
and not Middle Eastern?
• There is no Middle Eastern race in
order to limit the number of different
races. This illustrates the importance
of collecting ethnicity information as
well as race information. Identifying
“Pakistani” as the ethnicity tells us
much more than “Asian” as a race.

66.
Monitoring Progress
• Your supervisor will meet with you
as a group or one-on-one to ask:
• how your patients are responding to
be asking their race and
ethnicity, and
• how you feel the process is
working—what’s working and what
could be improved.

67.
Monitoring Progress
• Your supervisor will also be
monitoring the number of
Unknowns to determine if some
staff are having more difficulty than
others obtaining race, ethnicity and
preferred language.

68.
SRMC’S DATA COLLECTION
PRACTICES

69.
Physician Services Data Collection

70.
Medical Center Data Collection

71.
Home Health/Hospice Data Collection

72.
UTILIZING REAL DATA TO
REDUCE DISPARITIES

73.
Tailoring Interventions
• If disparities in outcomes are
discovered, design culturally-tailored
interventions

74.
Monitoring Quality of Care Outcomes
REaL data should be used to measure
the following quality differentials:
• Clinical outcomes
• Patient satisfaction
• Process measures

75.
Sample Dashboard: Colorectal Cancer Incidence
Rate by Race/Ethnicity
Cases per 100,000 population
From Santium Hospital

76.
Sample Hospital Equity Report
From RWJF

77.
Other Sample Dashboard Topics
• Hospital Quality Alliance Measures (Process
Measures):
• AMI, HF, Pneumonia, SCIP, HCAHPS
• NQF-endorsed Standards for Serious
Reportable Events
• AHRQ measures
• Cardiovascular, Cancer Outcomes*
* Where many medical centers start

78.
CASE STUDIES

79.
Montefiore Medical Center
Objective Interventions
Standardize REaL collection Train registration staff and modify
Information systems
Improve AMI & CHF care for all
Montefiore patients
Patient and provider centered
materials, improvement methods
Evaluate quality of care by
demographic group
Monthly reporting of AMI and CHF
measures by demographic group;
data analyzed by Quality Dept.
Improve communication with post-
discharge providers
CHF-specific discharge planning

80.
New York-Presbyterian
OVERVIEW: Serves predominantly Hispanic community with high rates of
asthma, diabetes, heart disease and depression. ACTIONS:
Established work group to improve care coordination and culture
competency through 4 strategies: 1) Patient-centered medical
homes focused on diabetes, CHF, asthma and depression; 2)
Centralization of call center functions such as scheduling, test
results, and follow-up for 7 outpatient sites; 3) Employment of
bilingual and bicultural community health workers and navigators in
medical homes and in emergency departments; and 4)Implemented
4-hour training program to build workforce better able to address
linguistic, culture and health literacy needs . Physicians receive
training with patient-based cross-cultural care, which assists with
cultural competency and communication with patients and families.
Physicians become more aware of their patients and their own
perceptions. RESULTS: As of May 2011, 600 employees rec’d
cultural competency training. Collaborative helped decrease # ED
visits for ambulatory-sensitive condition by 9.2 %

81.
Baylor Office of Health Equity
OVERVIEW: Baylor’s Office of Health Equity (OHE) aims to reduce
variation in health outcomes among it diverse patient populations.
Diabetes is a severe epidemic & more than 2X as likely to occur in
minority populations. REaL data analysis indicated disparities in
diabetes management within Baylor’s primary care practices.
ACTIONS: OHE developed a Diabetes Equity Project (DEP) to reduce
disparities in diabetes care and outcomes in nearby Hispanic com-
munities. Enrollment began 9/09. Steps taken: 1) Community health
worker recruitment and training, 2) Building on local clinic partnerships
& integrating community health workers into Baylor’s overall care
coordination strategy, and 4) developing electronic diabetes registry to
track patient metrics and facilitate disease management
communication between community health workers and primary care
clinicians. RESULTS: > 800 patients enrolled; A1C values
improving, suggesting sustainable diabetes control can be achieved
for participants who previously had poor control by augmenting “usual
care” with community health worker-led patient education & advocacy.

82.
Communication Suggestions
• Community leaders & community meetings
• Hospital Newsletters
• Local newspaper articles, TV news
• Targeted brochures to local households
• Posters, table-top signs in Admitting
• Laminated cards for registrants to hand out
• On medical center Web site
• Community focus groups

83.
Using REaL—Leading Practices
1. Use equity dashboard to report org’l performance
2. Inform & customize language translation services
3. Review performance indicators such as
LOS, admissions and avoidable readmissions
4. Review process of care measures
5. Review outcomes of care
6. Analyze provision of certain preventive care
7. Analyze patient satisfaction scores

84.
Getting Started
What Leadership Can Do:
• Understand your own attitudes and skills—
start with self-assessment tool
• Engage the communities you serve &
understand your community’s needs
• Standardize REaL data collection
• Work with outside experts to begin to analyze
process and outcome data on 1 diagnosis,
e.g., cardiovascular care, stratified by race
once REaL data collection in place

85.
Resources
• Massachusetts General Hospital Disparities
Solutions Center
• http://www2.massgeneral.org/disparities solution/guide.html
• Expecting Success: Excellence in Cardiac Care
• http://www.rwj.org/pr/product.jsp?id=36180
• HRET Disparities Toolkit
• http://www.hretdisparities.org/
• RWJF- Creating Health Equity Reports
• http://www.rwjf.org/pr/product.jsp?id=29173
• Hospitals in Pursuit of Excellence
• http://www.hpoe.org

86.
QUESTIONS?

87.
Contact Us
• Deborah Bohr
• dbohr@aha.org
• Andy Bostick
• nbostick@aha.org