The U.S. health insurance system is increasingly complex, affecting providers’ ability to offer coordinated care and cost transparency. Patient-centered lab stewardship tackles this complexity through targeted efforts to improve access to medically necessary testing, as well as improving coverage for those tests. In an influential New York Times op-ed, Elizabeth Rosenthal, MD, proposed a patient financial bill of rights, noting that “twenty percent of people with insurance say they have trouble paying their medical bills, a figure that rises to above 50% for the uninsured” (1). Even for patients with insurance, and for whom testing is considered a “covered benefit,” the actual cost to the patient is not transparent because of copays, coinsurance, and unmet deductibles (2).
As clinical laboratory professionals who prioritize patent care, we believe patients deserve to understand how much a service will cost, whether insurance will cover the cost, and whether they will be financially liable. Tools to support pricing transparency for lab testing align with these stewardship principles.
So, how can we find out what a test will cost? We invited Heather Agostinelli, vice president of strategic revenue operations at XIFIN, to share her expertise.
In your own words, what does a thorough benefits investigation for a laboratory test entail?
A good benefits investigation (BI) entails understanding the cost of the test and the expected reimbursement of that test at that specific point in time. What type of deductibles are involved? Is there a separate deductible, perhaps for genetic testing? Are there applicable co-pays? What is the co-insurance that will be applied to this test? Those things are all very important to a thorough BI. Most smaller labs are making phone calls to payers for BI and may be on that call for 30 to 60 minutes to do that. In addition, they usually make multiple calls back to see if they get the same story from that payer because there is so much misunderstanding, and often speaking to two different people yields two different answers.
We’re very fortunate, because we have an estimator tool that is a big help. However, it is also predicated on the insurance returning all the necessary information. In the instance of an out of network lab, it can be inaccurate if we do not have access to an expected amount for that payer and that test. We do, however, have an analytics program that can determine what that insurance typically allows for that test, helping eliminate the error in BI for out of network labs. This tool is key, as many labs are out of network and do not have expected pricing as there are no contracts in place with payers.
When we provide an estimate back to a patient, we explain that this is the estimate at that exact time, because claims will come in and be processed within hours sometimes and that can affect the estimate. In many instances, it changes it for the better in the sense that more of the deductible has been met, but I’ve seen where we’ve had a reverse effect.
Could you share an example of why this issue is important?
There is a patient that comes to mind—a young mother who had a child born with Down syndrome. She became pregnant again and was interested in testing to see if this baby would have Down syndrome. A BI wasn’t really in play at that time, so patients just had the test and hoped for the best. She ended up with a large bill, and when I met her, she was seriously upset and confused about her insurance benefits. She told me that she would not have had some of the tests had she known what they were going to cost, and she assumed they were all covered by insurance.
Her story still resonates with me, especially since her testing was covered, but not through the out-of-network laboratory where she had the test. That’s why I think BI is so important and is increasingly relevant.
What are the barriers to answering this clearly for each patient encounter?
Some of the complexity comes from dealing with out-of-network plans. Dealing with specific plans can be difficult because you submit to the state plan, but they forward to the home plan, and they might have discrepant policies. In addition, when calling the plan directly, the discrepancies in information could be the result of inadequate training.
This issue of inaccurate information recently caused a problem with our tool. The insurance carrier provided all the appropriate information to the vendor, who in this case was the intermediary between the payer and XIFIN. The vendor filtered out some of the pertinent information that was returned to XIFIN, thus causing an inaccurate BI. In this instance the coinsurance responsibility was filtered out. This example highlights the importance of validating the accuracy of the information, whether you do it manually, through a phone call, or with an automated tool. When we identify inconsistencies in our investigation, we usually work through the payer relations team to investigate the root cause.
In a perfect world, what would labs implement to support a patient-centered approach to billing transparency for laboratory testing?
Many labs manage their own BI process, but I do have several large labs where we manage their BI as well as prior authorization. When you are dealing with a patient who has no out-of-network benefits, most laboratories offer a self-pay rate that is less expensive than if they had gone through their insurance. Pursuing a self-pay option must be determined prior to billing insurance. Once insurance is billed from a compliance standpoint, you really can’t touch that bill.
In a perfect world, automation is key. Taking out the human element can be beneficial—with a machine at our end hooked up to the machine at the payer’s end that knows how much of a deductible this patient has, how much of their deductible was met this year, this is the coinsurance percent, and this is their copay. We’re not necessarily having the conversation with the patient, but at least it’s machine to machine, and you're not talking to a person who may understand what is covered by insurance today but a colleague may not the next day.
The ability to do a BI from a system standpoint, and using what we call our estimator tool, is a trend well-received among our stakeholders. In the example I shared with the estimator tool filtering issue, I was pleasantly surprised to find that the insurance provider was very willing to help us figure out what happened. They wanted to make sure that we had received the right information so that we were giving the patient the appropriate information for the BI.
How do you push the field towards tools that really are as effective as possible, including standards that consumers should expect?
Accessibility and usability are key. You want to make sure that it is for somebody who doesn’t live and breathe benefit investigations. I always think of my dad who is brilliant and gets frustrated whenever he must deal with Medicare. The tools should be user-friendly and easy to find. Ultimately, if you have a good tool and it is accessible and easy to get to, it really does cut down on all those phone calls. Automation is key for error-prone elements, but human interaction to educate the consumer is still necessary. Overall, consumer expectations, including price shopping and user experience, will drive the field to improve.
Jessie Conta, MS, LGC, is a licensed genetic counselor in the department of laboratories at Seattle Children’s Hospital. + EMAIL: [email protected]
Jane Dickerson, PhD, DABCC, is a clinical professor at the University of Washington and co-director for clinical chemistry and reference lab services at Seattle Children’s Hospital. +EMAIL: [email protected]
Heather Agostinelli is AVP of Strategic Revenue Operations at XIFIN in San Diego, CA. +EMAIL: [email protected]
1. Rosenthal E. Nine rights every patient should demand. The New York Times. 2018, SR p. 2.
2. Dickerson JA, Conta JH. Billing demystification and the impact on uninsured and underinsured individuals seeking lab testing. J Appl Lab Med 2021;6(1):327–329.