CCO Metrics Demographic Methodology

About Demographic Reporting

REALD supports OHA's goal to eliminate health inequities by 2030

A key part of eliminating health inequities is complete and accurate reporting of demographic data. What gets measured gets counted. A lack of granularity in demographic data can mask inequities. We use race, ethnicity, language and disability (REALD) data because they offer more detailed demographic data than other sources.

Remember people are not numbers. Relying on quantitative data alone can have negative impacts. This dashboard is a starting point, laying the groundwork to engage communities in the future direction of the CCO Metrics Program. Exploring data in the context of community engagement, research and conversation is essential to understanding health inequities.

Accessibility

You can get this information in other languages, large print, braille or another format for free. Please contact us at Metrics.Questions@odhsoha.oregon.gov or 503-201-1949. We accept all relay calls.

We report REALD data:

To provide data back to communities that advocated for and led to the creation of the REALD legislation and standards.
To identify strengths and inequities in communities that experience structural racism and other forms of discrimination.
To inform how OHA allocates resources to effectively increase health equity.

Communities most impacted by health inequities determined the REALD categories. Data systems are not neutral, and data are often used to maintain imbalances of power. OHA recognizes that the data we have historically collected and used are insufficient for understanding community needs, experiences and desires. By reporting and providing REALD data, we aim to create the conditions needed for communities to engage in data justice.

CCO metrics come from multiple data sources. Below is an overview of each data source and REALD data availability.

Administrative (claims and hybrid): Claims are primarily used for health care payments but can also be used for utilization and other quality measures. Claims make up the majority of CCO metrics reporting. A few metrics use a hybrid of data sources, such as claims with immunization registry or claims with electronic health records (EHR). Claims do not ask REALD questions. However, claims include patient information, such as name, date of birth, member ID, and more, which can be linked to other databases.

Consumer Assessment of Healthcare Providers and Systems (CAHPS) survey: CAHPS is an annual survey collecting information on patient experiences with health care. Oregon has been conducting the CAHPS survey with patients on Medicaid since 1998 and began including REALD questions in 2019.

Electronic health records (EHR): EHRs are records kept by clinics during a health care visit. Currently, CCOs report EHR metrics as aggregate data only, without providing patient information.

	Demographic data collected?	Linked to demographic database?	Demographic data reported?
Administrative	No	Yes	Yes
CAHPS survey	Yes	No	Yes
EHR	No	No	No

For administrative metrics, we used the REALD & SOGI Repository to fill data gaps.

In 2023, OHA launched the REALD (race, ethnicity, language, disability) & SOGI (sexual orientation, gender identity) Repository. The repository is the first effort by any state government to develop a relational database containing the most complete demographic information possible. The initial repository draws on seven databases, as outlined below.

Database	Description
OregONEligibility (ONE)	The state's eligibility system to enroll in Oregon Health Plan and other public benefits
Oregon Public Health Epidemiologists' User System (ORPHEUS)	Case management system for case investigators of communicable disease
Memento Morbi (MM)	Communicable disease surveillance data system
OHA COVID-19 Reporting Portal (OCRP)	COVID-19 online data portal
At Risk Identification Alerting System (ARIAS)	Contact tracing system for COVID-19 (no longer active)
Oregon Pandemic Emergency Response Application (OPERA)	Case management system for case investigators of COVID-19 (no longer active)
Oregon Vital Events Registration System (OVERS)	Registry of births, marriages, divorces, registered domestic partnerships and deaths (added summer 2023)
CSV data	COVID-19 data from health care providers

As of May 2023, the Repository contained around 19.4 million unique records. Roughly 90% of those records came from ONE, with 10% of records coming from data sources in OHA's Acute and Communicable Disease Prevention (ACDP) Section. In 2024, OHA improved data processing and imputations in the Repository, leading to lower missing, unknown or declined rates.

Questions? Contact OHA-EI-REALD-SOGI-AllStaff@odhsoha.oregon.gov.

We expect to change and refine how we report REALD data as we engage with community. We will adjust our methodology as we learn more about the realities of health inequity in Oregon.
The REALD methodology here only applies to the CCO Metric: Demographic Disparities dashboard and is not for providing guidance on other OHA reporting efforts.
Due to changes in methodology, demographic data cannot be compared to what was published in previous CCO Metric reports.
Demographic data for administrative and CAHPS metrics come from different sources and are collected using different methods, and are therefore not comparable.
For administrative metrics, we use demographic data from the OHA REALD & SOGI Repository and other administrative databases to give us more complete data.
For CAHPS metrics, we only use demographic data provided by survey respondents.
In 2024, the CAHPS survey was conducted in English, Spanish, Chinese (Simplified Chinese written and Cantonese via phone), Russian and Vietnamese. Demographic data for CAHPS metrics may not be representative of the Oregon population.
The most detailed demographic data are provided whenever possible. However, rates for some groups are not displayed to protect member confidentiality.
Each person is assigned to a single category which allows for population-level analysis. See sections below for more information on how we assign members to categories.

Race or ethnicity

Race is a social construct

Race and racial categories are social constructs created through social processes of racialization. Racial categories do not reflect biological or cultural differences between groups. Differences between racial categories and the meaning ascribed to physical appearance or genetic differences are the result of “cultural, historical, ideological, geographical, and legal influences rooted in structural racism and white supremacy."¹

When significant differences in health outcomes exist between racialized groups, these differences reflect present day and historic exclusion from opportunities for health, which begin where we live, learn, work and play. This exclusion is a result of perceived membership to these racial categories.

_____________

¹ Mays, V. M., Ponce, N. A., Washington, D. L., & Cochran, S. D. (2003). Classification of race and ethnicity: Implications for public health. Annual review of public health, 24(1), 83.

REALD categories were determined by communities most impacted by health inequities. From 2018 to 2024, Oregon collected data for 40 race and ethnicity groups. REALD requires that answers are self-reported, and members can select multiple races or ethnicities. REALD also asks members to identify their primary race or ethnic identity.

Each person is assigned a single race category. A single race category allows for easier comparisons when looking at the population as a whole. A single race category does not represent an individual's racial identity, which may be multiracial, complex and intersectional. For this reason, a single race category is not reported at a member level. A person's full racial identity must be valued and honored when seeking care.

When a person selected more than one race or ethnicity, and did not select a primary, we used a least common group method. This method assigns a person to the least common group they selected. For administrative metrics, this method applies to less than 1% of members, as most select a primary race or ethnicity. To determine the least common racial/ethnic groups in Oregon, we used the Census American Community Survey (ACS) Public Use Microdata Sample (PUMS). An exception to this order is that Other and Multiracial groups come after the most common racial group in Oregon, white. For more information, see Reporting categories below.

Administrative (billing) claims:

Tribal affiliation imputed as American Indian. If a member indicated that they are affiliated with a federally recognized tribe and did not select a primary racial/ethnic identity, we imputed that member's primary race as American Indian.
Some languages were used to impute granular REALD race and ethnic identities. Ancestry, language and place of birth can be used to impute REALD race or ethnic identity. Approved languages are those that were not used during colonization. Therefore, languages such as English and Spanish are not used to impute REALD race or ethnic identity.
Some groups include historical, non-REALD compliant data. To provide as much data as possible, we include historical data from OregONEligibility (ONE), which is our largest source of demographic data in the REALD & SOGI Repository. These data were collected prior to the implementation of REALD standards. We note these data in the dashboard.

CAHPS survey

CAHPS data may not be representative of the Oregon population. In 2023 and earlier, the CAHPS survey was only conducted in English and Spanish, causing selection bias.
CAHPS did not ask primary race or ethnicity in 2019. In 2019, we assigned respondents with multiple race or ethnic identities to the least common group they selected. For all other years, we assign respondents to their primary race or ethnicity. With this change, results prior to 2020 cannot be compared to later years.

For measurement year 2024, administrative metrics used REALD standards from 2023, which include up to 40 race or ethnicity groups.

Groups are ordered from least to most common race and ethnicity in Oregon, based on 2015-2019 PUMS data:

Aggregate	Granular
Middle Eastern/North African	North African
	Middle Eastern
Native Hawaiian and Pacific Islander	Marshallese
	CHamoru (Chamorro)
	Samoan
	Communities of Micronesian Region
	Native Hawaiian
	Pacific Islander (not listed)
Black and African American	Afro-Caribbean
	Somali
	Ethiopian
	African (not listed)
	African American
	Black (not listed)
American Indian and Alaska Native	Canadian Inuit, Metis or First Nation
	Alaska Native
	Indigenous Mexican, Central American or South American
	American Indian
Asian	Cambodian
	Hmong
	Laotian
	South Asian
	Korean
	Asian Indian
	Filipino/a
	Japanese
	Communities of Myanmar
	Chinese
	Vietnamese
	Asian (not listed)
Hispanic and Latino/a/x/e	South American
	Central American
	Mexican
	Hispanic or Latino/a/x/e (not listed)
White	Slavic
	Eastern European
	Western European
	White (not listed)
Biracial/Multiracial	Biracial/Multiracial
Another race	Another race

Next year, administrative metrics will be updated to align with new REALD standards per Oregon Revised Statutes (ORS) 413.161. In 2024, REALD standards expanded to collect up to 71 race or ethnicity groups.

In 2024, the CAHPS survey was updated to align with new REALD standards per Oregon Revised Statutes (ORS) 413.161. In 2024, REALD standards expanded to collect up to 71 race and ethnicity groups.

When an individual selects more than one racial/ethnic group and does not select a primary race, they are assigned to the group they selected that is least common in Oregon. This method helps show smaller populations in the data. Race and ethnicity groups are ordered from least to most common in Oregon, based on 2024 population estimates from Portland State University Population Research Center (see table below).

Aggregate	Granular
Another race	Another race
Middle Eastern/North African/Southwest Asia and North Africa (SWANA)	Palestinian
	Israeli
	Iraqi
	Egyptian
	Turkish
	Syrian
	Lebanese
	Iranian
	Middle Eastern/North African/SWANA (not listed)
Native Hawaiian and Pacific Islander	Tongan
	Fijian
	Marshallese
	Samoan
	Communities of Micronesian Region
	CHamoru (Chamorro)
	Pacific Islander (not listed)
	Native Hawaiian
Jewish	Sephardic
	Ashkenazi
Black and African American	Haitian
	Nigerian
	Jamaican
	Somali
	Afro-Caribbean
	Ethiopian
	African (not listed)
	Black (legacy)
	African American
American Indian and Alaska Native	Canadian Inuit, Metis or First Nation
	Alaska Native
	Indigenous Mexican, Central American or South American
	American Indian
Asian	Pakistani
	Afghan
	Indonesian
	Communities of Myanmar
	Cambodian
	Hmong
	Laotian
	Thai
	Taiwanese
	South Asian
	Asian (not listed/legacy)
	Korean
	Japanese
	Asian Indian
	Vietnamese
	Filipino/a
	Chinese
Hispanic and Latino/a/x/e	Dominican
	Cuban
	Salvadoran
	Central American
	Afro-Latino/a/x/e
	Guatemalan
	Puerto Rican
	South American
	Hispanic or Latino/a/x/e (not listed/legacy)
	Mexican
White	Romanian
	Ukrainian
	Russian
	Slavic
	Polish
	Italian
	Scottish
	Irish
	English
	German
	White (not listed/legacy)

Language

Language access in health care is a fundamental right

We report language data to identify linguistic marginalization and missing or inadequate interpretation services. Health care services must be in a language members understand. If not, these services are inadequate and unjust. As former U.S. Surgeon General Regina Benjamin summarized, “If our patients don’t understand us well enough to make good health-care decisions, then we didn’t treat them.”

A person’s language preferences or needs may be complex and change depending on the setting. For example, the language a person uses at home may be different than the language they prefer to use in a doctor’s office. Factors beyond preferred or primary language, such as English proficiency and interpretation needs, must be considered to provide meaningful access to health care. Simply put, context matters.

As an example of why context matters for language access, not everyone who speaks English less than very well will ask for or receive interpretative services. A person’s willingness to ask for interpretation may be influenced by a variety of factors, including but not limited to:

geography,
availability of interpreters in their preferred language, and
trust in sharing personal matters with an interpreter who may be a member of the same small community.

English proficiency exists on a continuum. Those who self-report speaking English less than “very well” could mean little to no English. Or they could mean having just enough proficiency to complete an application written in uncomplicated English. People who self-report speaking English less than “very well” may perceive asking for an interpreter as an additional barrier to services. These barriers may include more time to set up services or fear of being seen as a nuisance by providers.

REALD asks a range of questions to capture the spectrum of language preferences and needs. Most questions are self-reported, and respondents can choose the languages they use at home and prefer to use in different settings. In April 2022, language options in the REALD & SOGI Repository expanded to over 7,000 languages.

In the Dashboard, each person is assigned a single language. A single language category allows for easier comparisons when looking at the population as a whole. However, no single language category can adequately capture language preferences and needs.

Administrative (billing) claims

We prioritize preferred spoken language for members who use language(s) other than English. If a member reported using a language other than English for any REALD question, we use the language they want to be communicated with in person, on the phone or video remote, also called preferred spoken language. If a member reported two or more preferred spoken languages, we prioritize non-English languages and languages that are less commonly used in Oregon, based on language data from the American Community Survey. We assign members to the English group if they:

reported only using English or
used language(s) other than English and preferred to be communicated with in English when in person, on the phone or video remote.

From 2018 to 2021, blank responses in ONE defaulted to English. OregONEligibility (ONE) is our largest source of demographic data in the REALD & SOGI Repository. In 2021 and prior, blank responses in ONE defaulted to English. This default did not allow us to determine if a response was declined or missing, and causes inconsistencies in language data for those years. For example, an individual may have reported needing an interpreter, but their preferred language was blank and now appears as English in ONE.
We use language data reported during enrollment, not during health care visits. When a member first enrolls in Oregon Health Plan, they are asked to answer REALD questions. A member’s responses to REALD questions may change over time. For example, a member may not need an interpreter during enrollment, since it is communicated in uncomplicated English. However, this member may ask for an interpreter during a health care visit to better understand medical terminology or a complex diagnosis. As such, the language data we use may not fully capture members’ language preferences and needs.
Requesting an interpreter does not mean an interpreter was provided. We cannot report if an interpreter was provided and, if so, the quality of those interpreter services. Requesting an interpreter does not necessarily lead to better health care outcomes. However, studies show that interpreters can positively impact health outcomes. Current evidence shows that the association between interpretation and improved outcomes is nuanced. The quality of interpretation services provided can positively impact quality of care. ¹

CAHPS survey

Spoken language reporting began in 2023. Starting in 2023, CAHPS began asking members for their preferred spoken language. That year response options were expanded to include English, Spanish, Arabic, Chinese, Russian and/or Ukrainian, Somali, and Vietnamese. Members also had the opportunity to add other languages not listed. If a member selected multiple languages, we prioritize non-English languages and languages that are less commonly used in Oregon. Also in 2023, the CAHPS children survey updated questions to focus on language preferences of guardians, whom minors largely depend on to access health care services.
CAHPS data may not be representative of the Oregon population. In 2023 and earlier, the CAHPS survey was only conducted in English and Spanish, causing selection bias.
Due to small sample sizes, we are unable to report spoken languages other than English and Spanish. To protect member confidentialty, we roll up all other groups into an "Another language" aggregate category.

____________________________

¹Heath, Hvass, & Wejse, 2023; Wiles et al., 2023

For administrative metrics, we report two language demographics: Spoken language and language access needs.

Spoken language: This is the language members want to be communicated with in person, on the phone or video remote. In 2024, we report CCO service rates for up to 79 spoken languages.

Language access needs: To better understand structural inequities, we report groups with potential language access needs. These include members who reported using a language other than English for any of the REALD language questions. We report three categories:

Bi-/Multilingual: Members who speak more than one language, but prefer to communicate in English and speak English "very well." These members may prefer to have written materials in a language other than English.
May need interpreter: Members who did not report needing or wanting an interpreter but prefer to communicate in a language other than English or speak English less than “very well.”
Interpreter requested: Members who reported needing or wanting an interpreter, or preferring a specific type of interpreter.

These data come from the Decision Support/Surveillance and Utilization Review System (DSSURS), which most closely match the data CCOs use for language services.

For members under age 15, we report their guardians' language preferences and needs. Minors largely depend on a parent or guardian to access health care services. Individual language is also more likely to be missing among minors. For example, children under age 5 are still learning language skills. Age 15 is the age of consent to medical and dental services. At this age, members may independently access health care services.

We report the language preferences members reported during enrollment. Data may not reflect requests made during a health care visit.

For CAHPS survey measures, we report spoken language. This is the language members want to be communicated with in person, on the phone or video remote.

Due to small sample sizes, we are unable to report spoken languages other than English and Spanish. To protect member confidentiality, we roll up all other groups into an "Another language" aggregate category.

For members under age 18, we report their guardians' spoken language. Minors largely depend on a parent or guardian to access health care services. The CAHPS children survey is completed by a guardian and questions focus on guardians' language preferences and needs.

We do not report language access needs for CAHPS metrics. For language access needs, we link administrative (billing) claims data with enrollment data. At this time, we do not link CAHPS survey responses with other data sources.

Disability

People with disabilities is a population experiencing health inequities

We report disability data as a proxy for two systems of oppression: ableism and disablism. First, ableism favors able-bodied people in policy and practices, which often restricts people with disabilities’ ability to fully participate in society (for example, lack of ramps, communication access). Second, disablism is the direct act of prejudice and discrimination against people who have disabilities (for example, discrimination in hiring).

People with disabilities are often excluded or overlooked in health care data, which makes them more likely to experience health inequities.1 The lack of data about health inequities experienced by people with disabilities is a form of structural disablism. Despite health inequities between people with and without disabilities being well-documented, public health generally does not consider people with disabilities as a population experiencing health inequities.¹

OHA recognizes people with disabilities as a population experiencing health inequities. Health inequities are differences in health that are unjust and avoidable. As part of our work to end health inequities, we commit to reporting disability data in the CCO Metrics: Demographic Disparities dashboard.

Disability does not mean illness

Inequitable health status of people with disabilities results from present day and historical exclusion from full and equitable participation in school, employment, stable housing, health care, civic life and more. Federal policies governing benefits and income restrictions also enforce poverty among people with disabilities. This enforced poverty restricts access to better schools, housing and other social determinants of health.

These exclusions and barriers accumulate over one’s life, creating greater health inequities, especially for those with long-term disabilities that impact daily limitations.

_________________________

¹ Krahn, G.L., Walker, D.K., Correa-De-Araujo, R. (2015). Persons With Disabilities as an Unrecognized Health Disparity Population. American Journal of Public Health, 105(2), S198.

There are many definitions of and ways to measure disability.

Disability can mean that a person has a condition that impacts participation in daily life. Eight REALD questions ask about functional limitations, or limits to activities people do every day because of a physical, mental, cognitive, emotional, or developmental condition. Daily activities include seeing, hearing, walking, learning, communication, cognition, self-care, and independent living. Not all conditions are captured using functional limitations. One question about mental health helps count more people with disabilities.

REALD questions reflect the great diversity among people with disabilities in the type of limitation(s) and age when they acquired their limitation(s). These questions help identify those who are most likely to experience social and health inequities due to disability.

Age plays a pivotal role in disability experience. Health trajectories are affected at certain times in life. For example, those who are born with or acquire a disability at a young age will likely experience more discrimination and greater environmental barriers than those who acquire a disability later in life. For members who respond yes to any of the functional limitation questions, we ask the follow-up question: “At what age did this condition begin?”

Not everyone is asked the full set of REALD disability questions. REALD functional limitation questions depend on age. For example, members under age 5 are excluded from questions about mobility (walking or climbing stairs), cognition (concentrating, remembering or making decisions), self-care (dressing or bathing), learning and communication. Members under age 5 are still developing these functions. Everyone is asked about hearing and vision limitations.

Members under age 15 are excluded from questions about independent living (doing errands alone in the community) and mental health (mood, intense feelings, controlling your behavior, or experiencing delusions or hallucinations).

In the Dashboard, each person is assigned a single disability group. A single disability group allows for easier comparisons when looking at the population as a whole. However, no single disability group can adequately capture a person’s health trajectory or exclusion from full participation in their community.

We report those with a cognitive, learning or mental health limitation together. To protect confidentiality, we suppress groups with small numbers. By reporting Learning/Cognitive/Mental health only as a single group, we can make more consistent comparisons across all CCOs and metrics.

Functional limitation questions may underrepresent some groups with disabilities. For example, children under age 5 are excluded from questions about mobility (walking or climbing stairs), cognition (concentrating, remembering or making decisions), self-care (dressing or bathing), learning and communication. As such, youth with disabilities other than hearing or vision may not be represented.

Administrative (billing) claims

To fill data gaps, we identify members eligible for disability services and supports. For the Independent living/Self-care+ category, we include members receiving Permanent Disability or long-term care (LTC) services. Members who are eligible for these programs experience greater barriers to accessing health care.
Starting in measurement year 2024, Independent living/Self-care+ no longer includes members who only qualify for Supplemental Securinty Income (SSI). Use caution when comparing 2024 data with prior years.

We report granular disability categories based on limitations to daily living, also known as functional limitations. These vary slightly by data source (administrative or CAHPS).

Administrative (billing) claims

2+ limitations
Members who reported having more than one of the following functional limitations, excluding Independent living/Self-care(+).

Blind/Low vision only
Members who only reported being blind or having serious difficulty seeing, even when wearing glasses (all ages).

Communication only
Members who only reported having serious difficulty communicating (understanding or being understood by others) using their usual (customary) language (ages 5 and older).

Deaf/Hard of hearing only
Members who only reported being deaf or having serious difficulty hearing (all ages).

Independent living/Self-care+
Members who reported having:

Difficulty doing errands alone such as visiting a doctor’s office or shopping because of a physical, mental or emotional condition (ages 15 and older), and/or
Difficulty bathing or dressing (ages 5 and older).

Members who did not respond to REALD disability questions but were identified as receiving:

Permanent Disability or
Long-term care (LTC) services.

Learning/Cognitive/Mental health only

Members who only reported having any of the following:

Learning: Serious difficulty learning how to do things most people their age can learn (ages 5 and older).
Cognitive: Serious difficulty remembering, concentrating or making decisions because of a physical, mental or emotional condition (ages 5 and older).
Mental health: Serious difficulty with mood, intense feelings, controlling their behavior, or experiencing delusions or hallucinations (ages 15 and older).

Mobility/Physical only
Members who only reported having serious difficulty walking or climbing stairs (ages 5 and older).

Non-disabled
Members who answered one or more of the REALD disability questions but did not report any functional limitation and were not identified as eligible for Permanent Disability or LTC services.

CAHPS Survey

In 2024, the CAHPS survey differed with two categories:

Independent living/Self-care

Members who only reported having:

Difficulty doing errands alone such as visiting a doctor’s office or shopping because of a physical, mental or emotional condition (ages 15 and older), and/or
Difficulty bathing or dressing (ages 5 and older).

Self-ID only

Members who identified as disabled or as having a condition in their own words. These members did not answer "yes" to function limitation questions. This option was added to the CAHPS survey in 2024.

For CAHPS metrics, we do not identify members who received Permanent Disability or long-term care (LTC) services.

We also report a disability aggregate roll-up of number and type of functional limitation(s):

1 limitation: Members who reported having one functional limitation, excluding Independent living/Self-care+ (Administrative) or Independent living/Self-care only (CAHPS).
2+ limitations: Members who reported having two or more functional limitations, excluding Independent living/Self-care+ (Administrative) or Independent living/Self-care only (CAHPS).
Any disability: Members with any reported or identified disability. We only report this category if all other categories are suppressed.
Independent living/Self-care+ (Administrative): Members who either:

Reported having:
- Difficulty doing errands alone such as visiting a doctor’s office or shopping because of a physical, mental or emotional condition (ages 15 and older),
- Difficulty bathing or dressing (ages 5 and older), and/or
Did not respond to REALD disability questions but were identified as receiving Permanent Disability or Long-term care (LTC) services.

Independent living/Self-care (CAHPS): Members who only reported having:

Difficulty doing errands alone such as visiting a doctor’s office or shopping because of a physical, mental or emotional condition (ages 15 and older), and/or
Difficulty bathing or dressing (ages 5 and older).

Self-ID only (CAHPS): Members who identified as disabled or as having a condition in their own words. These members did not answer "yes" to function limitation questions. This option was added to the CAHPS survey in 2024.

General Information

Questions about CCO Metrics reporting? Call 503-201-1949 or email Metrics.Questions@odhsoha.oregon.gov.
Questions about REALD? Contact OHA-EI-REALD-SOGI-AllStaff@odhsoha.oregon.gov.

Release 2025.1 (published November 25, 2025)

General updates:

2024 Consumer Assessment of Healthcare Providers and Systems (CAHPS) survey data will be added in a later release.
Starting with Release 2025.1, we now report groups whose service rates were suppressed to protect member confidentiality.

Changes to disability data:

All 2023 disability data refreshed using 2024 demographic data from the REALD & SOGI Repository. In the 2024.1 Release, many members who declined, did not know or did not respond to disability questions were likely assigned as non-disabled for administrative metrics. For disability, 2024 missing, unknown and declined rates also apply to 2023.
Starting in measurement year 2024, Independent living/Self-care+ no longer includes members who only qualify for Supplemental Securinty Income (SSI). Use caution when comparing 2024 data with prior years.

CCO Metrics Program (2025). CCO Metrics: Demographic Methodology. Webpage accessed [MM/DD/YYYY]. Portland, OR: Oregon Health Authority. https://www.oregon.gov/oha/HPA/ANALYTICS/Pages/CCO-Metrics-Methodology.aspx

CCO Metrics Demographic Methodology

About Demographic Reporting

REALD supports OHA's goal to eliminate health inequities by 2030

Accessibility

Why we report REALD data

Data sources for CCO metrics

About the REALD & SOGI Repository

Considerations

Race or ethnicity

Why race and ethnicity reporting matters

Race is a social construct

How data are collected

Data limitations

Race and ethnicity categories - Administrative (billing) claims

Race and ethnicity categories - CAHPS survey

Language

Why language reporting matters

Language access in health care is a fundamental right

How data are collected

Data limitations

Language categories - Administrative (billing) claims

Language categories - CAHPS survey

Disability

Why disability reporting matters

People with disabilities is a population experiencing health inequities

Disability does not mean illness

How data are collected

Data limitations

Disability categories (granular)

Administrative (billing) claims

CAHPS Survey

Disability categories (aggregate)

General Information

Contact us

Release notes

Release 2025.1 (published November 25, 2025)

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