Using Data to Reduce Disparities and Disproportionalities in Human Services
Disparities and disproportionalities in human services and behavioral health can threaten child, youth, and family development and well-being, as well as performance in school and on the job. Examples include lack of access to prevention programs, treatment services, or other community resources, and lack of cultural competence. Poverty, which is disproportionate among racial and ethnic groups, is a critical factor to access and quality of care.
Developing and implementing effective strategies to reduce such disparities and disproportionalities can be challenging and requires significant planning, monitoring, and coordination. Developed by AIR and the Cultural Competence Action Team of SAMHSA’s Technical Assistance Partnership for Child and Family Mental Health, the Blueprint for Using Data to Reduce Disparities/Disproportionalities in Human Services and Behavioral Health Care enables communities and states to develop and implement data-driven strategies through a step-by-step process that includes
- readiness assessment;
- community engagement;
- identification of disparities and/or disproportionalities;
- gathering, disaggregating, analyzing, and synthesizing data;
- design of data-driven intervention strategies;
- evaluation of interventions and continuous quality improvement;
- replication; and
- sustainability.
Key to this process is the disaggregation of data to compare with local, county, state, or national data to assess differences/similarities or over/underrepresentation to help make conclusions about the presence or absence of disparities and disproportionalities.
In 2011, the U.S. Department of Health and Human Services (HHS) released the HHS Action Plan to Reduce Racial and Ethnic Health Disparities. An overarching priority in this plan is to assess the impact of federal investments, such as grants, on the reduction of disparities in communities across the country. The Blueprint is a tool that addresses the HHS priority and provides a concrete, data-driven process for implementation on the ground.