Why Collect Data Using a Uniform Framework

The uniform framework provides a process improvement tool for health care organizations to systematically collect race, ethnicity, and primary language information from patients or their caregivers. Using this framework results in more accurate and complete data. Health care organizations with data from their own institutions may, in turn, use the information to reduce health care disparities, develop targeted initiatives to improve quality of care, and provide patient-centered care.

The elements of a uniform framework include:

1. A rationale for why the patient is being asked to provide information about his/her race, ethnicity, and primary language.
   
2. A script for staff to use each time so that they ask questions in a uniform fashion.
   
3. A method for allowing patients to self-identify their race, ethnicity, and primary language.
   
4. A standardized approach for "rolling up" granular responses to the Office of Management and Budget (OMB) categories for analytical and reporting purposes.
   
5. Assurances that the data will be held confidential and that a limited number of people will have access to the data, and a mechanism to guarantee this claim.

• Current Practices
• Standardization
• Benchmarking

Look to the blue Links column to the right for helpful resources.

Current Practices

Hospitals

Hospitals play a major role in a community's health care delivery system. But their infrastructure for collecting and using race, ethnicity, and language data is underdeveloped, leading to problems of redundancy, inefficiency, and inaccuracy.

• 78% to 82% of hospitals report collecting race data.
• Far fewer collect ethnicity data.
• 66% of hospitals collect primary language data in the patient medical record.
• 38% maintain a database of patients' primary language, which can be tracked over time.
• 56% collect race/ethnicity data in more than one unit.
• Within the same hospital, different units use different categories.
• Over 50% of hospitals report collecting race/ethnicity data by observation.
• 86% provide limited categories.
• 13% provide a "write-in" response, but these text responses are often not used.
• 10% provide granular race/ethnicity categories tailored to their community's demographics.
• 25% report linking race/ethnicity and language data to quality of care measures.

Medical Group Practices

Little is known about the collection of data on race and ethnicity in medical group practices. Medical groups are less likely than hospitals to collect race and ethnicity data (Nerenz, Currier, and Paez 2004).

• 75% of medical groups that responded to one survey did not collect race/ethnicity data because they thought it was unnecessary or that collection was potentially disturbing to patients.
• Medical groups that collected the data did so primarily for internal quality improvement or disease management purposes, and some were closely affiliated with hospitals that collected data on race/ethnicity as part of the inpatient registration process.
• Recognizing this gap is particularly important. We know far less about health care disparities in the outpatient setting as compared with the inpatient setting.

Community Health Centers (CHCs)

Perhaps because of the tremendous diversity of patients seen at CHCs and their mandate to have their boards of directors represent their communities, CHCs appear to be ahead of the curve in collecting information on patient's race and ethnicity.

• The Bureau of Primary Health Care (BPHC) has demonstrated success in collecting data in this setting. BPHC's Universal Data System stores data from 700 grantees at 3,000 health care sites.
• The BPHC has established specific racial, ethnic, and primary language data collecting and reporting requirements applicable to its network of CHCs.
• The success of these programs provides evidence to other medical groups that this information can be routinely obtained from patients in outpatient practices.

Health Plans

In a study released by America's Health Insurance Plans (AHIP) and the Robert Wood Johnson Foundation, over half (53.5%) of 137 plans that were surveyed collect data that identifies the race or ethnicity of their enrollees.

• 78.2% of Medicaid health plans collect race and ethnicity data.
• 74.3% of Medicare plans collect race and ethnicity data.
• 50.9% of commercial plans collect race and ethnicity data.

Health plans report they collect such data to identify enrollees at risk for certain conditions, to support educational and other communication efforts directed to diverse populations, and to structure quality improvement efforts.

Look to the blue Links column to the right for helpful resources.

Standardization

We recommend the following practices for standardizing race, ethnicity, and primary language data collection in health care organizations:

Who provides the information
Information should always be provided by patients or their caretakers. It should never be done by observation alone.

When to collect
Collection should take place upon admission or patient registration to ensure appropriate fields are completed when the patient begins treatment (for plans, at enrollment).

What racial and ethnic categories should be used
Start with the U.S. Census or the Office of Management and Budget (OMB) categories. Health care organizations can provide more granular categories (to use for internal purposes), but these granular categories should have the capacity to be aggregated to the broader OMB categories for reporting purposes.

Where should data be stored
Data should be stored in a standard electronic format for easy linking to clinical data.

Patient Concerns
Concerns should be addressed up front and clearly, prior to obtaining information.

Staff training
Employers need to provide ongoing training and evaluation to staff.

Benchmarking

Benchmarking is necessary. Health care organizations need to know where they stand to see where they are going. For example, are quality improvement interventions making a difference? Should our organization be doing things differently?

Collecting accurate data helps your organization track progress over time. In addition, it allows for comparisons within organizations, across organizations, as well as at a national level. Most national level data are obtained from health care organizations. If the data your organization collects are accurate, it contributes to accurate comparisons and reporting at all levels.

Look to the blue Links column to the right for helpful resources.