Download - Querying Patients About Race and Ethnicity

www.CenterForUrbanHealth.org

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% 1st or 2nd 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

CliniciansPlanning & 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

Birthplace Language(s)

Race or ethnicityQuestion

Religious preference

Race or ethnicity Question

Marital status


Four methods

Method 1 Method 2 Method 3 Method 41. Hispanic?

(y/n)

2. Race? (OMB list)

3. Ethnicity?

(Open-ended)

1. Ethnicity? (Open-ended)

2. Race? (OMB list)

1. Race? (OMB list +

Hispanic)


1. Race? (OMB list +

White HispanicBlack Hispanic)



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

Outcomes of Interest

Method

One TwoThre

eFour

Interviews (n) 76 56 59 39

No answer to race Q (%)

21.1 3.6 0.0 2.6

Chose available response to race Q (%)

78.9 87.5 100.0 92.3

Answered ethnicity Q (%)

85.5 100.0 94.9 92.3

Avg Time (mins) 1.1 0.9 1.0 1.2


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