A new online resource can help identify and overcome health inequities.
Were you aware, for example, Black residents of Cole County were about 1.5 times more likely to be treated for substance disorders than white? Or, they were about 1.5 times more likely to seek treatment for prostate cancer, cardio-pulmonary disease, asthma or anemia?
The Missouri Hospital Association (MHA) launched its Health Equity Dashboards on Monday.
The dashboards provide detailed data showing where there are health inequities. They may be searched down to ZIP code, and draw from 41 million hospital claims during three fiscal years - from 2018-20. Claims came from 5.4 million unique Missourians, or about 88 percent of the state's estimated population of 6.16 million.
The MHA wanted to create a novel approach to presenting health disparity data, said Mat Reidhead, MHA vice president of research and analytics.
There have been pervasive and long-standing problems of health disparities for vulnerable people across the country, Reidhead said.
"Over the past year, the pandemic has recast and magnified inequities for vulnerable Americans. Everyone has a fair and just opportunity to be as healthy as possible," he continued. "All sectors can use this information to close those gaps on health inequity across Missouri and nationally."
The website may walk a viewer through searches along demographic or geographic lines.
Its "Get Started" step (called a quick-start priority guide) lets viewers select between demographic groups for side-by-side comparisons. For example, the viewer might look at the disparity between health care users in Cole County. If viewers wished, they can see how many people of a particular race used services, and how they paid for them.
A comparison of white versus Black patients shows Black patients (29.54 percent) were about 2.9 times more likely to have Medicaid coverage than whites (10.35 percent). They were also about 3.4 times more likely to have adverse social determinants of health.
"We've got huge differences in the rates of diagnoses," Reidhead said.
Looking a little deeper, we went on to step two, "Take a Deeper Dive."
The dashboards default to "asthma" because asthma is a "very, very common health disparity that we see across the state," he said. He pointed out Barnes Jewish Hospital has a mobile asthma unit.
In step two, it is possible to find data by age, sex and race.
Adding Boone, Callaway, Maries, Miller, Moniteau and Osage counties to the selections - those counties that surround Cole - we can look a little more regionally at health.
Data show Blacks (68.73 percent of the time) were more likely than whites (44.81 percent of the time) to use emergency departments in Cole County. In Boone County, Blacks (57.19 percent of the time) were more likely than whites (33.8 percent of the time) to use emergency departments.
Similar differences occurred in Callaway and Maries counties. Among those we pulled up, only in Moniteau County were whites (46.11 percent) more likely than Blacks (35.85 percent) to use emergency departments.
The page also charts data, such as health care payer and ages of patients.
Another click on that page allows the user to drill down to the zip code level.
A third step lets the reader "Evaluate risk-adjusted differences in health outcomes." This dashboard lets the reader compare rates at which demographic groups have to return for procedures for conditions, such as myocardial infarctions (specific kinds of heart attacks). And it provides rates of mortality during specific surgeries, such as a coronary artery bypass graft surgery (CABG).
Data for specific procedures like CABG is limited to counties with hospitals that provide the services.
The fourth (and final) step is intended to help viewers "Understand diversity in your community's composition."
Viewers may dive into data by ZIPcode. They may search by items, such as average household income, average public assistance, ages, college degrees, percentages below poverty level, employment status, disability status, whether they commit to work, age of home and many other factors.
Using asthma as an example, said MHA spokesman Dave Dillon, a child with asthma may live in a community that challenges his or her health.
Hospitals see patients from certain ZIP codes, where asthma appears more prevalent, homes are older and emergency department rates are twice those of other areas, he said.
Someone can look at this data set and see that there are elevated levels of utilization within that community. Rather than simply continuing to provide asthma medication to those individuals from that community, they can use the data to help understand they probably need to go upstream, where those asthma triggers are happening and intervene there.
They can look to community partners, who can help mitigate causes.
"It's the pound of cure when the ounce of prevention is upstream," Dillon continued. "That is really the whole idea behind using this to identify determinants of health."