Identifying and Reducing Health Disparities
Andrews discusses how COVID-19 brought to light dramatic health disparities in the United States. The Health Transformation Alliance (HTA) has used data to determine inequities among the employees in its cooperative companies and implemented strategies to reduce disparate care in high-risk populations.
COVID brought this into stark relief. [It spotlighted] issues we had before COVID, like respiratory and other lung issues, which were much higher among minority groups. Minority children are more likely to be asthmatic, and that creates lifelong problems.
If you look at obesity, Type 2 diabetes, and asthma and look at the demographic profiles of people struggling with those conditions, it is disproportionately minorities, and that has always been true. We saw it in the media during the pandemic. HTA has aggregate data with four million people going back 51 months, and we broke that information down by race or other categories to see what our businesses were experiencing.
What we’ve tried to do is take action to fix it.
We know it is true that people with health coverage have better outcomes than people who don’t. All full-time employees in our member businesses have health coverage. A 5-year-old with asthma whose mom doesn’t have insurance won’t get as much treatment as she should. The same goes for a person with diabetes; if they can’t see a primary care provider to get a metformin prescription, they are going to get sick.
Second, so many chronic diseases tied to worse outcomes with COVID can be managed through good use of medication. Our members all have good pharmacy plans for their employees and families. One of the things we looked at when considering pharmacy plans was their policy on delivery. Some will deliver to affluent areas but not poorer ones. Some have lots of stores all over, and other plans favor more upscale areas. We looked at our partners like CVS that are everywhere. Something like 90% of the U.S. population lives within a few miles of a CVS.
The final thing we looked at is behavioral health. This country has had a significant behavioral health problem for a long time, but it metastasized during the pandemic. The rates of isolation, loneliness, depression and substance abuse multiplied. One of the solutions HTA put together was working with Lyra Health, a network of mental health professionals who are readily available. People often have to wait as much as three months to see a therapist, and by working with this organization, it will offer an expanded network of professionals digitally available to help people. This also ties to disparities because data show that providers who understand patients’ culture are usually more effective than those who don’t. With Lyra a number of their providers are people of color.
This is our third year of implementing these solutions, so it’s early. But we do have some results, both qualitative and quantitative. Employees are telling employers, “We are glad you did this. It helped me get an appointment with a psychologist sooner,” or “This has been good because I can pick up my prescription two blocks from my house.”
Quantitatively, I don’t want to overgeneralize, but it appears that, generally, people who take part in the programs have better health outcomes than those who don’t. We do measure how we stand in the disparity area. If you want to measure things like NICU [neonatal intensive care unit] days for babies, our members tend to have lower NICU rates than the general population, and it has lots to do with maternal health and the care they receive.
There are sensitivities connected to these things and laws requiring people to be treated equally. If this data is used as a weapon, it’s a bad thing. It’s illegal to say, “She might have a problematic pregnancy, so let’s not hire her.” That is a billion percent illegal.
But using data as a tool or a bridge someone can walk across to get better health is something we all want to do. If a 19-year-old employee changing bed linens in a hotel is pregnant, you know she may have a high-risk profile. If the approach is to work with providers, we can offer some ideas that may help with the pregnancy, like seeing the OB more often. The hard part is making sure everyone in the organization adopts the culture of data being an asset and not an intrusion.
We did a neonatal study, and it indicated our members in minority populations weren’t doing as well as they should be. NICU time for our minority employees was higher than for the general population. We tried to figure out why and then look for relationships with the institutions we had to create success with minority moms.
We wanted to see if there was a way to predict the moms that might have health difficulties that could lead to a baby ending up in the NICU. We did a study that indicated there were predictive factors like obesity, diabetes and respiratory problems that were all relevant to the risk for baby and mom. And race was a factor.
There is a cause and effect. A mom with diabetes and respiratory problems can tie back to the fact that she didn’t get good pediatric care as a child, which carries into her adulthood. It’s not literally the color of her skin that causes the problem but the inequities that deprived her of good healthcare.
The practical impact would be to offer her better care early in her pregnancy or before she becomes pregnant. Employers pay for most of the visits at an Ob/Gyn already, but maybe they can authorize more visits through their health plan. Instead of going to see a doctor three or four times, a plan could increase it to seven or eight times.
Getting this data is difficult but doable. I use the analogy of going to an annual checkup; no one likes to, and we hold our breath when the doctor calls with our results. If there is bad news on the other end of the line, it’s hard to hear. I look at these issues the same way. The diagnosis can be painful, but the data is the tool to help you do better.
Access to data and information is the critical difference between success and failure. With access comes two issues: who controls the data—and that should be the patient—and proper safeguards should be put in place to protect the patient’s privacy.
I can’t overemphasize the importance of privacy. No one ever knows the facts of someone’s pregnancy. But if we know someone is a 19-year-old who is obese, has a history of respiratory problems, is a single parent making lower income, and speaks English as a second language, then we can pay more attention to her with her permission. We can empower the doctors with that information, and they can give her better care. The more you know, the more you can do, and healthcare data is the key that unlocks all of that.
It helps the bottom line if employees are healthier. A person with Type 2 diabetes costs four to five times more to care for than someone who doesn’t have it. Someone who has colon cancer and gets screened and stopped early in the process is less expensive to treat. There is an economic aspect, but people are also the most important asset a company has. Whether it’s the person behind the counter at a Marriott, a code writer at IBM, or an analyst at JP Morgan, if they are healthier and happier, they are more productive.
Also, when you ask employers today what their major challenge is, almost all will say recruiting and retaining employees. All skill levels are relevant to this discussion, and almost all employers are struggling with vacancies. A person is much more likely to work for an employer and stay there if, when her daughter developed asthma, she was able to see the best doctor available. It is a relatively small number of employees who are going to have a health crisis, but when they do, it is front and center in their lives. An employer who understands that engenders loyalty.
If you want to say you really care about your employees, how can you not look at these things. What is hard is being careful and nuanced and methodical about collecting data, protecting privacy, not reinforcing stereotypes, and using data for positive purposes.