Collecting Health Data and Reducing Health Disparities: A Winning Combo? | Healthcare Informatics Magazine | Health IT | Information Technology Skip to content Skip to navigation

Collecting Health Data and Reducing Health Disparities: A Winning Combo?

July 31, 2014
by Gabriel Perna
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The cost of health disparities in America was in excess of $60 billion in 2009, according to a figure cited in a recent Robert Wood Johnson Foundation (RWJF) brief.

Marshall Chin, M.D., an internist at the University of Chicago Medicine, is a renowned researcher in the field of health disparities. He serves as director of the RWJF Finding Answers: Disparities Research for Change National Program Office. According to Dr. Chin, in Chicago, an African-American with breast cancer is three times more likely to die than a white person. This is just one example, he cites, that shows the tough situation minorities often face when it comes to their care.

“One of the challenges is there is no one single cause and no one single silver bullet that can fix the solution,” Chin says. “For example, part of it is access to care. If you have health insurance, you do better than when you don’t have it. But that’s just a foot in the door. Even when people have insurance, there are these racial differences in how people do. As a whole, we aren’t tailoring the care we provide to the specific needs of these individual people.”

Across the country, healthcare organizations are recognizing the issue of health disparities and taking action. An initiative that’s gained some recognition, from RWJF and elsewhere, is the collection of race, ethnicity, and language (REL) data. Collecting this kind of data, Chin says, helps provider organizations identify where they have disparities in care, leads to buy-in, and creates accountability. The best method to collection, he adds, is self-reporting.

“Directly asking the patient is the best way to avoid assumptions,” Chin says. Once the data is collected, it can be used in conjunction with clinical information sets—such as readmission rates— to help identify disparities and look into the root cause analysis of those problems.

Marshall Chin, M.D.

REL Data in Cincinnati

Identifying disparities was a significant reason for the Health Collaborative, a nonprofit organization that is made up multiple hospitals and health systems in Cincinnati, to begin collecting REL data as part of a citywide project that began three years ago. Nancy Strassel, senior vice president for the Greater Cincinnati Health Council, was a leader in the project. She says the collaborative was aware of the disparities, receiving data as a member of RWJF’s Aligning Forces for Quality (A4FQ) communities, and wanted to get a better grip on the reality of the situation.

“We saw some disparities data that spoke to the number of amputations that might be diabetes related. We know this is documented nationally but when we saw the regional numbers, we thought we had to do something to improve and determine what other disparities exist. Without having this data, you really don’t know,” Strassel says.

One of the first steps was to determine how hospitals and healthcare settings were collecting this data. What they found was a huge variation in the way hospitals and health systems were collecting REL data. They found that many were not even having patients self-report the data and often data collection categories were not standardized.

The organization focused on standardizing REL data collection through registration. According to Strassel, that required a lot of health IT department involvement to ensure coding and categories were aligned throughout the region. Because many hospitals were in the process of implementing an EHR, this coordination with the IT departments proved to be a challenge.

Nancy Strassel

“If a hospital was putting in an EHR [electronic health record], this wasn’t the highest priority. We had to work with many different hospital departments to make this happen. It was an opportunity because these systems were going in but it was a time when hospitals were quite busy with their change of process,” Strassel says. Furthermore, she notes, many health systems and hospitals wanted to dig deeper in the EHR and collect more granular data. “We had to meet each hospital where they were.”

According to RWJF’s Chin, REL data should be built into EHR systems automatically so it can be collected at intake and stratified for clinical results. This isn’t happening yet, but he expects it to occur in the coming years when there are reimbursement incentives for reducing disparities. “All providers are collecting performance data, it would be a simple programming step to stratify it through (REL) data,” he says.

Discovering Disparities

Once the collection methods were aligned and registration workers were trained on them, Cincinnati Health Collaborative began a public-facing campaign to let people know the rationale behind the reporting. This helped REL data collection become “second nature” for many people, a Health Collaborative consultant, Lisa Sloane said in a RWJF data brief.

Since many hospitals and health systems were undergoing multiple quality improvement initiatives, the Collaborative had to ensure this project was “part in parcel” with what they were doing. For example, Strassel says, a few of the hospitals in the collaborative were working to reduce readmission rates for congestive heart failure patients. So they used the REL data to see if there were health disparities in that area.

“Initially, we didn’t see a lot of variation. When we started breaking the data down by hospital, by system, by some of the various REL categories, and by condition, we started (seeing) small numbers (of disparities,” Strassel says. “Those are things we have to continually talk about as a community.” Thanks to the granular data within the EHR, she adds that hospitals are analyzing their own data at a deeper level. Further, the Health Collaborative will continue to collect and analyze data on their own, specifically at a communitywide level and the group expects more results to be published in the future.

With the numerous competing priorities overwhelming healthcare provider organizations on a daily basis, Strassel says it was a challenge to keep REL data collection on the radar screen. Credits was the meaningful use requirements for helping give providers perspective, in this regard.

“As physicians have motivation to provide the best care possible, they can use the REL data to provide the best care possible. If you know who your patients are, you can tailor to their needs of that patient and provide better care.  That helps providers meet quality standards,” Strassel says.

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