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Querying Patients About Race and Ethnicity
 

Querying Patients About Race and Ethnicity

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Identifying disparities in delivery of healthcare requires data about pt race and ethnicity. Overlapping but competing agendas on how best to obtain data. Articulates the issues and suggests best ...

Identifying disparities in delivery of healthcare requires data about pt race and ethnicity. Overlapping but competing agendas on how best to obtain data. Articulates the issues and suggests best method, based on experiment performed at Hennepiin County Medical Center. Presented at MN Health Services Research, March 07.

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    Querying Patients About Race and Ethnicity Querying Patients About Race and Ethnicity Presentation Transcript

    • MN Health Services Research Conference. 06MAR07 Querying Patients About Race and Ethnicity at Hennepin County Medical Center Yiscah Bracha,M.S. Research Director, CUH
    • Need for patient race data:
      • For providers to identify and eliminate instances of disparities in delivery of medical care
      • For researchers to monitor disparities:
        • Comparisons across geographic region
        • Trends over time
        • Associations with other factors
    • Natl. Research Shows:
      • Not all providers obtain patient race data
      • Among providers that do, querying is uncomfortable
        • Patients feel privacy invaded, suspicious about how data will be used;
        • Registrars reluctant to query them
      • Inconsistency in questions asked & response categories used
    • Goal:
      • Establish method to query patients about:
        • Race
        • Ethnicity
        • Other personal demographic characteristics
      • Qualities of method:
        • Respectful towards patients
        • Quick and easy to administer
        • Captures clinical important differences
        • Enables reporting using OMB classification
    • Setting: Hennepin County Medical Center
      • Publicly-owned, urban, safety net in downtown Minneapolis, MN
      • Level one trauma center
      • Hospital: 19,000 patients per year
      • Clinics: 168,000 outpatients per year
        • On-campus primary care (3 clinics)
        • Community-based primary care (3 clinics)
        • 20+ on-campus specialty clinics
    • Hennepin County Medical Center (HCMC):
      • Multi-racial
        • ~30% American-born Caucasian
        • ~20% African-American
        • ~12% 1 st or 2 nd generation African immigrant
        • ~21% Hispanic
        • ~13% Asian, Native American, European immigrant
      • Multi-ethnic
        • African-American vs. African-born
        • European-American vs. European-born
        • Hmong vs. Vietnamese vs. Indian
        • Mexican vs. Ecuadoran vs. Columbian
      • Multi-lingual
        • Interpreter services in > 60 languages
        • Spanish, Somali, Hmong most common non-English languages
    • The Question:
      • What is the best way to query ptts about race/ethnicity to satisfy following needs:
        • Speed during encounter
        • Patient feels they’ve truly “identified” themselves
        • Clinicians & planners get fine distinctions
        • Everyone can report using OMB categories
    • Who needs what?
      • Registries * Clinical Researchers * Public Health Departments
      • Fixed response choices
      • OMB reporting format
      • Clinicians
      • Planning & Marketing
      • Fine distinctions
      • Interviewer/
      • Patient Pair
      • Patient-perception
      • Simple
      • Short
    • HCMC Experiment
      • Conducted in January and February 2006
      • Used 4 HCMC registrars/schedulers (2 staffed Spanish telephone line)
      • Four methods tested
        • Each tested by 2+ interviewers, on 2+ days
        • Each tested until > 30 interviews took place
      • Outcomes of interest
        • Registrar feedback on ease of administration
        • Percent questions refused & incomplete interviews
        • Average administration time
    • HCMC Experimental Methods
      • Proposed data entry screen mimicked with Microsoft Access
      • Registrar switched to Access screen at appropriate time during live patient interview
      • Access recorded:
        • Responses provided (including refusals)
        • Time to administer entire set of questions
    • Four Methods Tried Marital status Race or ethnicity Question Religious preference Race or ethnicity Question Language(s) Birthplace
    • Four methods 1. Race? (OMB list + White Hispanic Black Hispanic) 2. Ethnicity? (Open-ended) 1. Race? (OMB list + Hispanic) 2. Ethnicity? (Open-ended) 1. Ethnicity? (Open-ended) 2. Race? (OMB list) 1 . Hispanic? (y/n) 2. Race? (OMB list) 3. Ethnicity? (Open-ended) Method 4 Method 3 Method 2 Method 1
    • Qualitative Results
      • Asking Hispanic ethnicity first doesn’t work
        • Next Q about race confuses patients
        • Too many questions if query about birthplace as well
      • Asking general ethnicity first doesn’t work
        • Too many choices
        • “ What’s the difference between ‘race’ and ‘ethnicity’”?
      • Asking race first:
        • Works for U.S. born
        • Works for Hispanic if responses include Hispanic
        • Doesn’t work for foreign-born non-Hispanic, but can overcome w.ethnicity Q follow-up
    • Quantitative Results 2.6 0.0 3.6 21.1 No answer to race Q (%) 1.2 1.0 0.9 1.1 Avg Time (mins) 92.3 94.9 100.0 85.5 Answered ethnicity Q (%) 92.3 100.0 87.5 78.9 Chose available response to race Q (%) 39 59 56 76 Interviews (n) Four Three Two One Method Outcomes of Interest
    • Preferred Method to Ask Qs:
      • What is your race?
        • White
        • Black or African American
        • Hispanic
        • Asian
        • Native American
        • Other
      • What is your ethnicity?
        • Over 60 possible choices suggested by
          • Nationality
          • Religion
          • Race
          • Language
    • On-going issues at HCMC:
      • Technology:
        • Cannot program EHR screen in preferred way
        • Low “fix” priority given new EHR launch
      • Registrar discomfort:
        • Regular staff still uncomfortable querying, especially in person
        • Inadequate training; no time to train
      • Inconsistent with OMB standard
        • But OMB standard known to generate incomplete race responses for Hispanics
    • Future directions at HCMC:
      • After launch of EHR settles down:
        • Work w/vendor to overcome technical glitches
        • Improve training for registration staff
        • Monitor question completion rates
        • Conduct addl experiment to test comfort with alternative questions
    • Implications of HCMC results:
      • Conflict:
        • Providers need:
          • Local detail not available in national categories
          • Relief from administrative burden (e.g., difficult to “roll up” detailed categories)
          • Way to overcome patient resistance
        • Researchers want:
          • Consistency across providers & localities (inimical to local detail)
          • Rigor in data collection methods (imposes administrative burden on providers)
    • Possible resolution of conflict:
      • Same question order, slightly different text:
        • Q1: “What race do most people think you are?”
        • Choices: Standard OMB list plus Hispanic
        • Q2: “What race or ethnicity do you consider yourself?”
        • Choices: Locally determined by population(s) provider serves
    • Possible advantages to alternative:
      • Questions not as intrusive, thus may lessen discomfort
      • Answers offer ability to distinguish between disparities due to:
        • How patient is perceived by medical staff;
        • Culturally-influenced patient behaviors & beliefs
      • Researchers get standardization; local providers get detail.
    • Extra slides: Office of Management & Budget Statistical Directive 15 (OMB Standard)
    • OMB federal standard:
      • Established in 1997, after years of research & debate
      • Mandatory for all federal data systems
        • Not mandatory for state or private data systems
        • In absence of alternative standard, some states & private entities have adopted it
        • Some strongly advocate it be made mandatory for all
    • Features of OMB Standard
      • Two questions:
        • Hispanic origin? (y/n)
        • Race
          • White
          • Black or African American
          • Asian
          • Pacific Islander
          • Native American or Alaskan native
          • Other
      • Multiple responses to race question permitted
    • Universal adoption of OMB standard?
      • Heavily influenced by “identity” politics due to use in US Census
      • Causes confusion, discomfort during administrative workflow
      • Known to generate non-answers to race question by Hispanics (research conducted by Census Bureau)
      • Some IT systems cannot handle 2 questions, or multiple responses
    • Extra slides: Issues to consider in question administration:
    • Who will ask questions?
      • Registrar (when ptt calls for appointment) vs. clinician (when rooming patient):
        • Advantages of registrar:
          • Can propagate universally throughout system
          • Epic already includes race question on registration screen
          • BUT:
            • Lots of administrative detail to capture at that time
            • Registrars not accustomed to asking personal questions
            • Patient concern that answer will affect care
        • Advantages of clinician:
          • Flows with usual questions that clinicians ask
          • Patient already getting care;
          • BUT:
            • Difficult for clinician to find the proper screen
            • Difficult to propagate universally
    • If registrar asks, when during interview:
      • Beginning vs. End:
        • Advantages of beginning:
          • Q already programmed in that part of the screen
          • Comes before Qs about payment source:
        • Advantages of End:
          • Registrar has had time to establish rapport