RTI Health Advance uses cookies to offer you the best experience online. By clicking "accept" on this website, you opt in and you agree to the use of cookies. If you would like to know more about how RTI Health Advance uses cookies and how to manage them please view our Privacy Policy here. Click "accept" to agree.

It’s Time For A Health Equity Data Reset

It’s Time For A Health Equity Data Reset

Taking a tailored approach to health equity data 

There is no lack of health-related data available today. For example, Healthy People 2030 uses more than 80 data systems to monitor progress toward 355 core measures to improve health and well-being in the U.S. The Centers for Disease Control and Prevention (CDC) lists nine data sources on social determinants of health (SDOH) data alone. There are numerous federal research grants, public-private commissions, and initiatives, as well as a host of commercial entities offering de-identified patient datasets and data integrators. Hospitals and health systems collect their own equity-related REaL/REaLS data (race, ethnicity and language, sex). In 2003, a survey of ~20% of U.S. hospitals reported that 79% of hospitals were collecting racial and ethnic data about patients. 

Federal regulations require reporting more complex patient data (we discuss using individual data and neighborhood-level data for SDoH here). Challenges with data persist for healthcare organizations of all types, from federal and state-based to national health plans, regional health systems, and community-based health organizations and non-profits. AI technology like RTI Rarity™, which creates an omnibus Local Social Inequity (LSI) index drawing on over 150 measures from multiple data sources, can be beneficial for accounting for social risk in value-based payment models, and identifying targeted interventions.

But, just like health equity strives to value everyone equally, as individuals, so should an entity’s approach to their health equity data strategy. Focusing on the unique needs of a healthcare organization’s patient populations, mission and vision, as well as budgetary, technical, and workforce constraints is paramount to ensuring measurable progress to improve health equity at the community level. 

Health equity data challenges during the COVID-19 pandemic

The CDC receives and reports race and ethnicity data for people vaccinated for COVID-19; however, that data has been missing for nearly 40% of people, and it is not reported at the state level. 

In June 2021, three state and national organizations hosted a data and health equity summit. Leaders from 20 states summarized four challenges related to COVID-19 data. Even though their focus was on public health data and systems, these challenges reflect the barriers to health equity data on the whole:

  1. Incomplete and inconsistent collection and reporting of data
  2. Public distrust in sharing data
  3. Limitations with current standards
  4. Challenges with data sharing

In light of these health equity data challenges, healthcare organizations have an opportunity to use the flaws revealed by the pandemic as a time for a reset. 

Health equity data reset review

Here are some reflection questions to provide fresh perspective and reorient health equity data goals and programs. These are most effective when shared with a cross-functional mix of stakeholders, inviting them to answer individually and bringing input to a group session or strategy workshop including discussion surrounding value-based care.

Health equity data questions for stakeholders

  1. Has your organization adopted health equity as a fundamental of high-quality care, as well as expressed it as a value in your mission and vision?
  2. Does your organizational structure support your mission related to health equity? 
  3. Which leaders have you hired or plan to hire, including a Chief Equity Officer, Medical Director of Equity, or Nursing Director of Equity?
  4. Is there consensus across your leadership that objective data can facilitate the discovery of inequity and reveal opportunities for analysis that can be used to implement strategies and programs to achieve health equity goals?
  5. How are you currently discovering, analyzing, and creating approaches to reduce health inequities? Are race and ethnicity an integrated variable?
  6. What key performance indicators do you report on related to disaggregated race, ethnicity, sex, language, or related equity data?
  7. What types of health equity data are displayed in existing clinical or population health dashboards? What is working and not working with reporting and analytics dissemination across stakeholders?
  8. Can you point to one or two examples where health equity data was useful in programmatic or organizational changes that yielded positive outcomes? How could you scale that success to other parts of your data strategy?
  9. How are you dealing with data overwhelm?
  10. What tools or techniques – like machine-learning algorithms – are you using to create focused, actionable insights?
  11. How accurate and complete is your health equity data?
  12. Are you using a multicultural patient group and clinician/staff group to provide input and feedback on your data strategy and approach?
  13. What types of publicly- or commercially-reported data could complement your internal and patient data aligned to your focused goals?

Interestingly, we’ve not asked questions about datasets, interoperability, or technology. Those items reveal themselves as these strategic and tactical questions are answered. Prioritize the questions that resonate with where your organization currently is in your health equity data journey but be sure to take time to answer those that you feel you’ve mastered. Do others agree?

Conduct a health equity data analysis (HEDA)

As an alternative or supplement to the reset questions above, consider conducting a health equity data analysis (HEDA). A health equity data analysis guides how your organization might think about, collect, and analyze data related to health equity. Typically conducted by county- and state-based health departments, using HEDA offers a community-centric approach to gathering information and providing recommendations. The resulting report will capture and address many of the questions asked above, revealing opportunities for improvements to equity data accuracy, timeliness, and quality. The Minnesota Department of Health provides a robust example of HEDA.

Bringing the best of health equity research, strategy, and data analytics together

Our team provides expertise across the health equity continuum, from data and research strategies to healthcare data analytics tools and services to programmatic design and quality improvement. Our proprietary tool forms a composite index for evaluating many data sources at a granular level. We can also create a tailored approach that supports your health equity mission through practical solutions.

Discover health equity data strategy expertise

Can your organization fully utilize its data assets to inform business decisions impacting patients and members? Contact RTI Health Advance today for valuable guidance and insight.

Subscribe Now

Stay up-to-date on our latest thinking. Subscribe to receive blog updates via email.

By submitting this form, I consent to use of my personal information in accordance with the Privacy Policy.

Stay informed on your favorite topics