Tech & Innovation in Healthcare

Take advantage of collaboration to identify disparities.

Since the start of the COVID-19 public health emergency (PHE), one thing that came into the public eye has been known by healthcare professionals for years — there is significant inequity in healthcare access, cost, and quality for patients of different races, ethnicities, genders and gender identities, ages, and other factors.

The good news is that health systems can use technology to examine data to reduce health disparities — here’s how.

Know What Types of Data Need Analysis

“Equity is being able to pull back and say not just that I gave everyone the same thing, but that I’m giving everyone something they can utilize and use in their particular space and time and situation,” said L. Renee Bradley, EdD, MBA, CPC, CPC-P, Rhodes State College in Lima, Ohio during her “Diversity, Equity and Inclusion Awareness in the Medical Field” session at AAPC’s HEALTHCON Regional 2022 conference in Denver, Colorado.

Healthcare providers can work with other stakeholders to understand the complete picture of health equity in their patient population. “Hospital electronic health records (EHRs) possess much of the clinical data, which should be layered with community health needs assessments, other providers’ data, and data on patient experience, outcomes, screenings, and social needs. All of this together will give us a better assessment of disparities and help point to a solution,” says Edward S. Kim, MD, MBA, physician-in-chief and senior vice president, City of Hope Orange County, and vice physician-in-chief and professor, City of Hope National Medical Center in Irvine, California.

According to an American Hospital Association (AHA) Center for Health Innovation market insight, additional data sets that healthcare systems should use to identify health disparities include, but are not limited to:

• Race, ethnicity, and language (REaL) data
• Medical claims data from payers
• Drug claims data from payers
• Patient-generated health data from wearable devices, smartphones, mobile applications, and remote monitoring

Certain specialties may require more data to ensure equitable care. For example, Dr. Kim’s focus is on cancer care, which has its own equity challenges. For optimal oncological care, specialists want to provide an equal opportunity to prevent cancer, allow early detection, deliver the right treatment, and provide follow-up care. “Critical data includes incidence rates, mortality rates for ethnic populations, five-year survival rates, and screening prevalence. We have made tremendous progress in cancer research and treatment, but, unfortunately, these advances have not benefited patients equitably,” Dr. Kim says.

Analyze Data to Improve Healthcare Equity

Predictive models harness data mining, statistics, and machine learning to identify patterns and calculate the chance of certain outcomes occurring. Healthcare professionals can use predictive models to help improve healthcare equity, but those models should also be enriched to “improve our ability to identify and prioritize patients at increased risk for serious illnesses, such as cancer,” Dr. Kim says.

By knowing which individuals could be at risk for developing severe infections or chronic diseases, providers can deliver the support and resources the patients need. “Or, we can work with providers in the primary care setting to ensure screening and, if needed, lifestyle education,” Dr. Kim adds.

At the same time, collaboration between healthcare professionals and organizations is another key to improving healthcare equity. Filling servers with essential data is great, but if that information continues to be siloed, then equity won’t be understood or achieved. The AHA encourages “hospitals and health systems [to] build relationships with other stakeholders who share the same vision of eliminating health disparities for the benefit of the entire community.”

Establishing solid partnerships to share and evaluate health data will help improve outcomes. “To get the big picture of how we’re lacking in care, we must share data across regions, healthcare facilities, insurance companies, public health, and providers at both the primary care and specialist levels,” Dr. Kim says.

Improving collaboration and predictive models can start simply by examining the technology available.

Use Technology to Explore Healthcare Equity Disparities

Interoperability is essential to effectively and securely sharing clinical and critical health data. If your healthcare organization establishes a partnership with an interested stakeholder, how effective will that partnership be to improving healthcare equity if the data cannot be shared and analyzed? By implementing technology that can create a bridge between organizations, social, clinical, and financial data from different systems (EHRs, billing, coding) can be used by several different groups and organizations, such as:

• Providers
• Payers
• Pharmacies
• Public health agencies
• Social and community groups
• Government agencies

Many health organizations are a part of one or multiple health information exchanges (HIEs), which help standardize data sharing between organizations. Once the information is standardized, it can be integrated into practice’s EHR, so the providers can use the information in their medical decision making.

Using an HIE also simplifies the data collection to facilitate collaboration. Clinicians and health systems will be able to identify any health disparities in the data sets and determine how demographics and geography play into processes and outcomes.

Once health organizations can identify disparities in their patient population, they can use the data to address the issues. Regardless of whether the issues facing the community are hazardous materials in living environments, lack of access to health foods, or conscious/unconscious bias, telling a story to clinicians with the data gathered is an effective method to improving health equity.