Health Equity, Diversity & Inclusion Measures for Hospitals and Health System Dashboards

Domain 1: Data Collection, Stratification and Use

Desired Outcomes/ Measures

Intent of Measures

Operationalizing the Measure

Supporting Tools and Resources

Increase the collection, stratification and use of race, ethnicity, language (REaL) preference data.

Measure(s):

· Percent of workforce (staff and clinicians) trained regarding collection of self- reported REaL data.

· Percent of patient records with REaL data preference complete with opportunity for verification at multiple points of care, beyond just registration .

Data collection, stratification and use are essential to developing initiatives

to eliminate disparities in health outcomes. By collecting, stratifying and using REaL patient data along with other data points such as sexual orientation, gender identity, geographic location, veteran status and disability status, hospitals and health systems can better identify disparities

in patient

populations.

REaL data can be collected at various points of care or within the community. For example, Henry Ford Health System, an AHA 2020 Carolyn Boone Lewis Equity of Care Award Honoree, collects REaL data for more than 90% of patients, as a result of their “ We Ask Because We Care” campaign.

The data is stratified

and used to implement programs and improve outcomes in maternal and infant health, diabetes management and prevention, and other areas.

Addressing Health Care Disparities through Race, Ethnicity and Language (REaL) Data (2020)

This brief contains multiple resources and case studies of how

hospitals are using REaL data to better understand disparities in care.

URL: https://ifdhe.aha.org/addressing-health-care-disparities- through-race-ethnicity-and-language-real-data

Building an Organizational Response to Health Disparities (2020)

This resource features a compilation of reports, guides, toolkits,

training tools, webinars, books and articles regarding REaL data collection, stratification and use.

URL: https://www.cms.gov/About-CMS/Agency-Information/ OMH/Downloads/Data-Collection-Resources.pdf

Evaluation of the National Standards for Culturally and Linguistically Appropriate Services in Health and Health Care (National CLAS Standards) (2018)

This toolkit describes the National CLAS Standards and provides

meaningful and practical guidance on delivering culturally and linguistically appropriate services.

URL: https://minorityhealth.hhs.gov/assets/PDF/ Evaluation_of_the_Natn_CLAS_Standards_Toolkit_PR3599_ final.508Compliant.pdf

Framework for Stratifying Race, Ethnicity & Language Data (2014)

This guide provides a framework that allows hospitals and

health systems to stratify patient data to identify health care disparities. This framework consists of five steps.

URL: http://www.hpoe.org/Reports-HPOE/REAL-data- FINAL.pdf

Domain 1: Data Collection, Stratification and Use

Desired Outcomes/ Measures

Intent of Measures

Operationalizing the Measure

Supporting Tools and Resources

Increase the collection, stratification and use of data (sexual orientation, gender identity and disability status) among broader culturally diverse populations.

Measure(s):

· Percent of patient records with sexual orientation, gender identity and disability status data complete with opportunity for verification at multiple points of care, beyond just registration.

Atrium Health, AHA’s 2019 Carolyn Boone Lewis Equity of Care Award Honoree, developed a “ Demographic Data Wall,” which is used

to identify disparities in population health

measures and stratifies race, ethnicity, language, sexual orientation and gender identity data allowing clinical leaders to identify gaps in outcomes across populations.

Do Ask, Do Tell: A Toolkit for Collecting Data on Sexual Orientation and Gender Identity in Clinical Settings (2020) This toolkit provides specific sexual orientation and gender identity (SOGI) questions recommended by national LGBTQ organizations. It also describes how to collect these data in electronic health record (EHR) systems, how to use these data to support clinical processes, and how to train clinical staff to interact with LGBTQ patients in ways that are affirming and welcoming.

URL: https://doaskdotell.org/ehr/toolkit/

Ready, Set, Go! Guidelines and Tips For Collecting Patient Data on Sexual Orientation and Gender Identity (SOGI) (2018)

This guide helps hospital and health systems begin to

implement sexual orientation and gender identity (SOGI) data collection.

URL: https://www.lgbtqiahealtheducation.org/wp-content/ uploads/2018/03/Ready-Set-Go_2018.pdf

· Percent of workforce trained regarding collection of sexual orientation, gender identity and disability status for patients.

Washington Group Training on Disability Data Collection and Analysis (2015)

This training module aims to help understand the approach

and guiding principles of the Washington Group on Disability Statics and deepen knowledge of how to collect and analyze disability.

URL: https://hilearngo.handicap-international.org/ workspaces/176/open/tool/home#/tab/-1

Domain 1: Data Collection, Stratification and Use

Desired Outcomes/ Measures

Intent of Measures

Operationalizing the Measure

Supporting Tools and Resources

Identify and monitor the collection and use of patient social needs such as: food insecurity, housing stability, transportation

needs, education needs, social support, financial stability, employment, physical safety and other measures that are specific to your population’s needs.

Measure(s):

· Percent of patient records with social needs data complete with opportunity for verification at multiple points of care, beyond just registration.

· Percent of workforce trained regarding collection of social needs areas for patients.

Rush University Medical Center, an AHA 2019 Carolyn Boone Lewis Equity of Care Award Honoree, implemented social needs screening across the system and community settings

to identify risk factors associated with social needs (food insecurity, housing instability and transportation). For example, Rush works to mitigate the social determinants of health

(SDOH) through strategic partnerships that provide food delivery services to older adults.

PRAPARE Implementation and Action Toolkit (2019) Toolkit with resources, best practices and lessons learned to guide implementation, data collection and responses to social determinant needs. Contains standardized patient risk assessment tool as well as a process and collection of resources to identify and act on the SDOH.

URL: http://www.nachc.org/research-and-data/prapare/ toolkit/

Screening for Social Needs: Guiding Care Teams to Engage Patients (2019)

This tool helps hospitals and health systems facilitate sensitive

conversations with patients about their nonmedical needs that may be a barrier to good health.

URL: https://www.aha.org/toolkitsmethodology/2019-06- 05-screening-social-needs-guiding-care-teams-engage- patients

ICD-10-CM Coding for Social Determinants of Health (2018)

This brief provides an overview on ICD-10 coding for SDOH. It also features a list of AHA tools and resources for hospitals, health systems and clinicians that address the social needs and the SDOH.

URL: https://www.aha.org/system/files/2018-04/value- initiative-icd-10-code-social-determinants-of-health.pdf

Domain 2: Cultural Competency Training

Desired Outcomes/ Measures

Intent of Measures

Operationalizing the Measure

Supporting Tools and Resources

Implement and/or monitor cultural competency training amongst all employees and clinicians to ensure culturally responsive care within strategic planning

efforts, operations, yearly employee trainings, clinical care, social services and other

areas specific to your organization.

Measure(s):

Cultural competency and unconscious/ implicit bias trainings increase health care professionals’ understanding

of factors that are important to patients and

play a key role in care decisions. These trainings also provide

an opportunity for health care professionals to be mindful of unconscious and implicit biases that may occur when interacting with patients and team members.

Chatham Hospital, a member of the University of North Carolina Health System and an AHA 2020 Carolyn Boone Lewis Equity of Care Honoree, administers trainings

in communication, cultural competency and unconscious bias to employees. These trainings can be implemented yearly as part of continuing

education for employees.

Becoming a Culturally Competent Health Care Organization (2013)

This guide provides a high-level overview for becoming a

culturally competent health care organization and includes two case studies.

URL: http://www.hpoe.org/Reports-HPOE/becoming_ culturally_competent_health_care_organization.PDF

Building a Culturally Competent Organization: The Quest for Equity in Health Care (2011)

This guide explores the case for cultural competency and

provides guidance for health care leaders to build a culturally competent organization.

URL: https://www.aha.org/ahahret-guides/2011-05-11- building-culturally-competent-organization

· Percent of employees and clinicians who have completed cultural competency training.

· Percent of patient and family complaints related to cultural competency.

· Rate of patient satisfaction scores (HCAHPS, CG-CAHPS)

pre- and post- cultural competency training stratified by race, ethnicity and language preference.

Domain 2: Cultural Competency Training

Desired Outcomes/ Measures

Intent of Measures

Operationalizing the Measure

Supporting Tools and Resources

Increase unconscious and implicit bias training amongst all employees and clinicians to ensure that associations or attitudes that are reflexive do not alter perceptions, behaviors, interactions or decision-making.

Health Care organizations utilizing the Implicit Association Test (IAT) (2019)

This guide outlines four ways organizations can use the Implicit

Association Test to improve health equity and quality of care. URL: https://www.aonl.org/system/files/media/file/2019/04/ ifd-implicit-association-0419.pdf

Measure(s):

· Percent of employees and clinicians who have completed unconscious/implicit bias training.