The Department of Health Policy
Hospital Collection and Use of
Patient Race, Ethnicity and
Language Data
Christal Ramos, MPH
Karen Jones, MS
Marsha Regenstein, PhD
Research Objective
• Collection of race, ethnicity and language (REL)
data is important for hospitals to be able to
– Understand who their patients are
– Identify and address potential disparities among their
patients
• This study examined
– The extent to which hospitals collect and use REL
data
– Whether over time collection has increased
Study Design
• Telephone surveys developed by GW researchers and
reviewed by external experts
• Study population:
– 2005: 502 hospitals, 46% response rate
– 2007: 547 hospitals, 52% response rate
• Acute care hospitals were randomly selected from
the AHA database
• Survey results were weighted by hospital governance
and teaching status to reflect make-up of American
hospital industry
Hospital Data Collection Practices in
2005 and 2007 (%)
2005
2007
100
80
78.4 81.0
60
50.2 51.0
50.5
41.9
40
20
0
Collect Race
Collect Ethnicity*
Collect Language
Source: GWU Survey of Data Collection Practices of Acute Care Hospitals, 2007; NPHHI Survey of Data Collection
Practices of Acute Care Hospitals, 2005.
*Indicates that the responses are significantly different (p<.05)
Categories for Collection
• 86.8 percent of hospitals that collect race collect
categories that are consistent with OMB
(Revised) Standards for Classification of Federal
Data on Race.
– However, 80 percent of these hospitals also included
Hispanic as a race category rather than in a separate
ethnicity question
• 13.6 percent of those interviewed asked for
clarity on the meaning of ethnicity
EHRs and Sharing of Race and Ethnicity
Data across Sites of Service or
Providers (%)
100
80
60
40
37.6
25.8
16.8
16.3
20
0
Have EHRs,
sharing at all
sites
Have EHRs,
sharing at
some sites
Have EHRs,
do not allow
sharing
Source: GWU Survey of Data Collection Practices of Acute Care Hospitals, 2007
No EHRs
Barriers to Collection of Race,
Ethnicity and Language Data (%)
Hospitals that collect
Hospitals that do not collect
100
80
60
40
38.4
45.2
29.0
36.2
31.6
20
9.3
13.0 17.8
0
Staff reluctance
to ask
Patient
reluctance to
provide data*
Lack of hospital
policies*
Source: GWU Survey of Data Collection Practices of Acute Care Hospitals, 2007
*Indicates that the responses are significantly different (p<.05)
Concerns of
legal liabity
Hospitals that Do Not Collect REL
Data reporting “No Demonstrated
Need” as a Barrier (%)
100
80
60
51.6
53.5
2005
2007
40
20
0
Source: GWU Survey of Data Collection Practices of Acute Care Hospitals, 2007; NPHHI Survey of Data Collection Practices of
Acute Care Hospitals, 2005.
Hospital Considerations in Decisions to
Collect Data (% Very Important)
To comply with data reporting requirements
75.5
To identify need for interpreter services or translation
53.7
To assess variations in quality
39.4
To assess/compare satisfaction
34.5
To assess/compare health outcomes
32.0
To assess/compare utilization of health services
29.6
To develop and market for specialized programs
26.1
Research purposes
18.3
Source: GWU Survey of Data Collection Practices of Acute Care Hospitals, 2007
Hospital Use of Data to Identify
Disparities (%)
60
40
20
7.1
2.9
7.3
0
Identified disparities by Identified disparities by
race, ethnicity or
primary or preferred
country of origin
language
Source: GWU Survey of Data Collection Practices of Acute Care Hospitals, 2007
Identified any
disparities
Hospital Use of Data to Identify
Disparities
• Attempted to interview 40 hospitals whose
survey responses indicated they have
used data to identify disparities
– Spoke with 26 hospitals
– Many could not identify who should be
interviewed to learn how they used this data
– Some said they do not specifically use REL
data to identify disparities
– 7 hospitals participated in interviews
Uses of Data to Identify and Address
Disparities Found in Interviews
• Standardization of the collection of race and
ethnicity data provided the data needed to
analyze quality measures and patient
satisfaction by race and ethnicity (University of
Wisconsin Hospitals and Clinics)
• Use of ethnicity and clinical data identified a high
prevalence of diabetes among Somali patients
and led to a hospital policy to screen all Somali
patients for diabetes (Olmstead Medical Center)
Other Examples Given in
Interviews
• Use of ethnicity data for grant applications
• Use of data to identify cultures to emphasize in diversity
trainings for staff
• Use of race, ethnicity and language data to identify
languages needed for interpreter services
• Identification of races/ethnicities for diversity fair in the
hospital with food and information on different cultures
• Use of community race data to identify opportunities for
business development and marketing
• Use of language data to identify the need for a diabetes
management class in Spanish
• Use of data for reporting to the state as required
Conclusions
• Hospital race, ethnicity and language data
collection did not significantly progress (or
has held steady) between 2005 and 2007.
• Although most hospitals have information
on the race, ethnicity and language of their
patients, very few hospitals have used this
data to identify disparities.
Implications for Policy, Delivery or
Practice
• Policies and tools are needed to help hospitals
progress in collecting this important data.
• Similar efforts should encourage hospitals and
other providers to use data to identify and address
disparities.
• Models/examples need to be shared to open up
possibilities of how REL data can be used.
• Both MIPPA and the Stimulus Bill provide the
Secretary of HHS opportunity to address collection
and use of REL data. Information on the current
state of the hospital industry in terms of REL data
collection and use can help inform these decisions.