Collecting and Using Race, Ethnicity and Language Data: From Documentation to Action

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Collecting and Using Race, Ethnicity and Language
Data From Documentation to Action

• Romana Hasnain-Wynia, PhD
• Director, Center for Healthcare Equity
• Northwestern University,
• Feinberg School of Medicine
• April 23, 2008

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Institute of Medicine Definition of Health Care
Disparity

• Difference in treatment provided to members of
  different racial (or ethnic) groups that is not
  justified by the underlying health conditions or
  treatment preferences of patients.

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Health Care Should Be

• Safe
• Effective
• Patient-Centered
• Timely
• Efficient
• Equitable

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Major Reports on Disparities
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Racial and ethnic disparities inhealth care

• In patients with insurance, disparities exist for
• Mammography (Gornick et al.)
• Amputations (Gornick et al.)
• Influenza vaccination (Gornick et al.)
• Lung Ca Surgery (Bach et al.)
• Renal Transplantation (Ayanian et al.)
• Cardiac catheterization angioplasty (Harris et
  al, Ayanian et al.)
• Coronary artery bypass graft (Peterson et al.)
• Treatment of chest pain (Johnson et al.)
• Referral to cardiology specialist care (Schulman
  et al.)
• Pain management (Todd et al.)

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A National Problem

• African Americans are
• Less likely to have a kidney transplant, surgery
  for lung cancer, bypass surgery
• More likely to have a foot amputation
• More likely to die prematurely
• Latinos/Hispanics are
• Less likely to receive pain medications
• What about other groups? Chinese? Vietnamese?
  Pakistanis? Nigerian? Somali? Haitian? etc.?

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Articulating Units of Accountability

• We Do Not Know
• At which level the responsibility lies
• National
• State
• Local
• Organizational
• Our patient populations
• What works, what doesnt

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Data Are Important!

• IOM-Unequal Treatment Confronting Racial and
  Ethnic Disparities in HealthCare
• Physicians for Human Rights Right to Equal
  Treatment
• AHRQ Healthcare Disparities Report
• National Research Council Eliminating
  Disparities-Measurement and Data Needs

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Questions

• HOW to collect relevant data to assess
• WHY and HOW disparities occur
• Which interventions are effective at reducing or
  eliminating disparities
• What proportion of observed disparities are
  amenable to improvements in health care

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Data Collection

• Why collect data?
• Documentation of disparities across broad groups
• Improve care for populations served
• Reward good performance (e.g., Performance-based
  incentives such as P4P)
• Broad categories for documentation
• Granular data needed to improve quality of care
  within organizations (community health centers,
  hospitals, etc)

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Why Collect Race/Ethnicity/Language Data?
Internal Factors (granular)

• Valid and reliable data are fundamental building
  blocks to improve quality of care
• Link race and ethnicity information to quality
  measures
• Ensure the adequacy of interpreter services,
  patient information materials, and
  cultural competency training for staff
• Be responsive to your community
• External Factors (broad)
• Reporting to the JCAHO, CMS, NCQA
• State mandates
• Regional Comparisons
• Performance based incentives (e.g., P4P)

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Perspectives on Data Collection

• Hospitals
• Health Plans
• Medical Group Practices
• Physician Practices (with lt5 physicians)

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Hospitals
78 Report Collecting Race and Ethnicity66
Report Collecting Primary Language
Race/Ethnicity
Urban
Rural
Teaching Hosp.
State Mandate
No Mandate
Non-Teaching
Source Who, When, and How The Current State of
Race, Ethnicity, and Primary Language Data
Collection in Hospitals, Romana Hasnain-Wynia,
Debra Pierce, and Mary A. Pittman, The
Commonwealth Fund, May 2004
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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)
• 54 collect race/ethnicity data
• 56 collect primary language
• 74 collect at enrollment
• 5 collect after enrollment

Source AHIP, 2006
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Medical Group Practices

• Less likely to collect race/ethnicity information
  than hospitals
• 75 didnt collect data because they thought it
  was unnecessary
• Source Nerenz, Currier, Paez, 2004

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Physician Practices with lt5 Physicians

• 45 collect
• 78 that collected have EMR
• Only 1 practice linked data to quality measures

Hasnain-Wynia, R, et al. Commission to End
Health Care Disparities Paper. 2007.
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Barriers To Collecting Data

• Patients/enrollees perceptions about why this
  information is being collected
• Discomfort in explicitly asking
  patients/enrollees to provide this information.
• Appropriate categories

• Validity and reliability of data
• Legal concerns
• System/organizational barriers
• Profiling
• Time-Consuming

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Tell People Why You are Asking

• Now I would like you to tell me your Race and
  Ethnic Background. We use this to review the
  treatment patients receive and make sure everyone
  gets the highest quality of care.

Baker DW, Cameron KA, Feinglass J, Georgas P,
Foster S, Pierce D, Thompson J., Hasnain-Wynia R.
Patients Attitudes Toward Health Care Providers
Collecting Information About Their Race And
Ethnicity. J Gen Intern Med. Vol 20 (10).
October 2005.
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OMB Categories

• ETHNICITY QUESTION
• Do you consider yourself Hispanic/Latino?
• Yes
• No
• Declined
• Unavailable/Unknown

• RACE QUESTION
• Which category best describes your race?
• American Indian/Alaska Native
• Asian
• Black or African American
• Native Hawaiian/Other Pacific Islander
• White
• Multiracial
• Declined
• Unavailable/Unknown

Hasnain-Wynia, R, Pierce, D, Reiter, J, Haque, A.
and Greising, C. Toolkit for Collecting Race,
Ethnicity, and Primary Language Data from
Patients. Version 2.0. September, 2007.
www.hretdisparities.org
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If Using OMB Categories and Not Splitting
Race/Ethnicity

• -African American/ Black
• -Asian
• -Caucasian/White
• -Hispanic/Latino/White
• -Hispanic/Latino/Black
• -Hispanic/Latino/Declined
• -Native American
• -Native Hawaiian/Pacific Islander
• -Multiracial
• -Declined
• -Unavailable/Unknown

Hasnain-Wynia, R, Pierce, D, Reiter, J, Haque, A.
and Greising, C. Toolkit for Collecting Race,
Ethnicity, and Primary Language Data from
Patients. Version 2.0. September, 2007.
www.hretdisparities.org
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2000 Metropolitan Chicago Tuberculosis Rates per
100,000 population, by Race/Ethnicity and Foreign
Born-Status
White Non-Hispanic
2.2 Black Non-Hispanic 17.5 Hispanic
9.8 Asian
32.4 Foreign-born 16.7 Source
Centers for Disease Control, National Center for
HIV, STD, and TB Prevention
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CDC-Codes-Example
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A Project in Chicago
ADVANCE Aligning Demographic Variables and
National Clinical Evaluation
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Goals

• Standardize a process for collecting patient
  demographic data on patient race, ethnicity,
  language, health literacy (education),
  acculturation (years lived in the US), and
  socioeconomic status (family size, insurance,
  income).
• Link patient demographic data with national
  clinical performance measures in an electronic
  health record system.
• Show health care processes and outcomes for
  specific conditions stratified by key patient
  demographic information (to identify targeted
  opportunities for QI).

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Collecting Patient Demographic Information
Practical Recommendations
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Adult Diabetes Performance Measures-Current
System Captures the following
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Adult Diabetes Performance Measures-New System
Would Capture the following
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Recommendations For Standardization

• Who provides the information
• When to collect
• Which racial and ethnic categories to use
• Where and how data are stored
• Address patients concerns
• Provide staff training

Hasnain-Wynia, R and Baker D.W. Obtaining Data
on Patient Race, Ethnicity, and Primary Language
in Health Care Organizations Current Challenges
and Proposed Solutions. Health Services
Research. August 2006.
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Address Concerns of the Community

• Involve community leaders in all aspects of
  planning and design of
• processes for data collection, analysis, and
  use of data for quality
• improvement
• Take all possible opportunities to communicate
  with community groups about the reasons for
  collection of data and use of data for quality
  improvement.
• Collect the data in a meaningful context
• Dont break promisesif data on race/ethnicity
  are being used for
• a specific purpose like expansion of interpreter
  services, then make sure those service expansions
  actually occur.

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Systematic Implementation

• Training and education components should include
• Policy context
• Revised policies
• New fields
• Screens
• Leadership-staff materials
• Staff scripts
• FAQs and potential answers
• Specific scenarios
• Staff questions
• Monitoring

• Conduct education and feedback sessions with
  leadership and staff
• Define issues and concerns and identify how you
  will respond to them

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Thank You! r-hasnainwynia_at_northwestern.edu