The features included in the ACG System have been widely discussed in past blogs. Patient Need Groups, Social Determinants of Health (SDoH) and predictive modeling are all familiar topics from the last few months. Today we introduce the next big driver in patient outcomes – race, ethnicity and health disparities in a population that are a product of these factors.   

A growing body of research in the last few years has pointed to the rising importance of the connections between a patient’s race and their future health outcomes. ACG System users have the tools at hand to effectively measure disparities within their populations – read more to find out how.   

Why Should Organizations Use Race and Ethnicity Data? 

Health care organizations and providers already use SDoH as part of the full breadth of overall population health. To recap, SDoH include food insecurity, economic instability and educational disparities as social issues that, when unmet, directly impact the health care costs and life expectancy of a population.  

As crucial as nutrition and education are in population health, race and ethnicity also have a significant impact on individual health outcomes. For example:  

• Racial and ethnic minority groups have higher rates of illness and death related to diabetes, hypertension, obesity, asthma and heart disease when compared to their White counterparts.¹ 
• Hispanic people have 33% more cases of COVID-19 than expected, and when adjusted for age, Hispanic, Black, and American Indian and Alaska Native (AIAN) people are twice as likely to die from COVID-19 as their White counterparts.²
• Black people are 8 times as likely as White people to have new HIV cases and 7 times more likely to die from HIV. ³
• Black women are 3 times more likely to die during and immediately following pregnancy than White women. ⁴ 

It’s crucial then, to effectively measure your population in order to understand its needs and the health disparities that exist today.  

Exploring Racial and Geographical Health Disparities 

In order for health care providers and organizations to understand the impact of these disparities, they have to know where they exist. The ACG System’s world-renowned functionality allows users to input their own data points to create profiles that represent a specific geographical area. Disease prevalence, access to care, medication adherence, care coordination and other health indicators can then be reviewed to see how they are impacted by race and ethnicity. 

Why is it Important to Track This Data? 

Understanding and reducing disparities in health care is a growing focus among government and private payors. The ability to gather more data about race and ethnicity allows providers and heath care organizations to treat patients more effectively. Not only will this potentially reduce health care costs, but it can also increase overall population wellness and work toward the overarching goal of health equity. 

How Can the ACG System Help? 

The ACG System offers users individualized and targeted glimpses into the health of your population. The System variables work together to define patient groups, identify their greatest needs and create plans to meet their necessities. Having this information at your disposal will help you create a more meaningful and effective population health management strategy, and ultimately, implement interventions to achieve health equity within your population.  

Stay tuned for more details on how to use ACG System to measure racial disparities in health and implement solutions to achieve better health outcomes. 

NOTES:

¹Racism and Health. Centers for Disease Control. (2021)  https://www.cdc.gov/healthequity/racism-disparities/index.html

²Hill, L. & Artiga, S. (2022). COVID-19 Cases and Deaths by Race/Ethnicity:  Current Data and Changes Over Time.  Kaiser Family Foundation. https://www.kff.org/coronavirus-covid-19/issue-brief/covid-19-cases-and-deaths-by-race-ethnicity-current-data-and-changes-over-time/

³2021 National Healthcare Quality and Disparities Report. Rockville, MD: Agency for Healthcare Research and Quality; December 2021. AHRQ Pub. No. 21(22)-0054-EF. https://www.ahrq.gov/research/findings/nhqrdr/nhqdr21/index.html

⁴ Petersen EE, Davis NL, Goodman D, Cox S, Mayes N, Johnston Eet al. Vital signs: pregnancy-related deaths, United States, 2011–2015, and strategies for prevention, 13 states, 2013–2017. MMWR Morb Mortal Wkly Rep. 2019;68(18):423–9. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6542194/