Denver Health integrates meaningful race, ethnicity and language data in its Epic EHR
Racial and ethnic minorities have unequal access to health care and are at greater risk for health disparities. Collecting accurate and meaningful race, ethnicity, and language (REAL) information is an ongoing challenge in healthcare – one that is critical to improving access to care.
This is a particularly timely topic as Healthcare IT News parent company HIMSS celebrates its annual meeting Global Health Stocks Week from October 23-27.
THE PROBLEM
For healthcare system Denver Health, the first hurdle was understanding the pre-intervention landscape when it comes to REaL data at its own facility.
“We knew we had issues collecting this data, but we first had to define the process for evaluating the quality of this data,” said Dr. Cory K. Hussain, associate chief medical information officer for health equity and clinical effectiveness near Denver. Health. “Defining those metrics was challenging. Once we got past that barrier, we discovered we had some real issues with our REaL data.
“Our next step to determine the root causes that caused these data quality issues was equally, if not more, challenging,” he continued. “It studies system-level processes, especially those that can involve a lot of variation that can be burdensome.”
Before implementing a REaL intervention in the EHR, Denver Health’s system-level settings required it to change some of its workflows.
“This was a difficult task as it required both buy-in from our frontline employees and then training them in this new method,” Hussain said. “This was only possible because of the dedication of the REaL team who were always embedded within the registration staff who did all the heavy lifting to make this program a success.”
PROPOSAL
Healthcare disparities continue to plague Colorado’s healthcare system. Many are systemic in nature, and the only way to alleviate these is to understand the patients affected and the systems in place that maintain them.
“You can’t change something you don’t have reliable data on,” Hussain explained. “Knowing who our patients are is an essential first step in the right direction. However, many organizations, including ours, struggle with missing data and quality issues. If we can’t trust our data, we can’t come up with interventions in the right population that would have done that.” the maximum intended impact with the limited resources available.
“Create training that addresses both how to ask these questions and how to respond to concerns when these questions are asked.”
Dr. Cory K. Hussain, Denver Health
“REAL was the necessary first step to do this work,” he continued. “Once we have reliable data, we can see which subsets of our population are affected here at Denver Health. This would help us evaluate the delivery of our health care system to these populations and make any adjustments that could reduce health care gaps in these vulnerable subgroups of the population. “
MEETING THE CHALLENGE
Today, Denver Health uses this information to understand health disparities in its patient cohorts when it comes to cancer screening or diabetes/hypertension control.
“Clinical champions and key stakeholders involved in health equity are using this data to identify gaps in our metrics and system processes that can improve them,” Hussain said. “They use this data as a filter and view all health outcomes using this data under the ‘lens of health equity.’
“At this stage, our ethnicity demographics are limited to the Denver Health systems,” he continued. “Epic has a module to exchange information with all other Epic hospitals using a functionality called Care Everywhere. However, this data field is currently not mapped to exchange this information.”
There are future plans from the Management and Budget Office to transition to more detailed ethnic backgrounds being collected and to additional racial categories.
“We are already leading the way by currently collecting this data,” Hussain noted. “At this time, we have not integrated this data or are not sharing it with any vendor because there are no federal reporting requirements for ethnic backgrounds. However, we see this changing and with the ability to exchange social determinants of health data, we likely will. see the liberalization of this data use in the United States.”
RESULTS
Race and ethnicity data were missing for more than 13% of Denver Health patients. The new methodology has reduced this to less than 1%.
“We now have ethnic background data on more than 700,000 of our patients, which allows us to see the wealth of our population beyond broad race and ethnicity categories and allows us to identify subpopulations within certain racial categories that may still be continue to have gaps in healthcare. Hussein reported.
ADVICE FOR OTHERS
“Evaluate your current data status and what process controls are in place or missing that are leading to the data gaps,” Hussain advised. “We weren’t successful until we discovered there were significant gaps and barriers in the way this data was collected.
“Using the quality improvement methodology allowed us to support our processes to specifically address pain points within our organization that would deliver the highest return on investment,” he continued. “This allowed us to achieve the best results we could have imagined. Every organization may have similar or nuanced processes that need improvement.
Also consider engaging the communities served by asking how they can better collect such information, he added.
“Design patient-centered and patient-friendly technologies that account for race, ethnicity, and ethnic backgrounds,” Hussain advised. “Create training that addresses how to ask these questions and how to respond to concerns when these questions are asked.
“But above all, create a burning platform for such a project that gets the attention and buy-in of all stakeholders in your organization, from the C-suite to the registration staff doing the work,” he says. concluded.
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