Laboratory Information Systems (LIS): What You Need To Know To Get Paid

By Sean McSweeney  bio

Today, laboratory billing claims require more and more data to successfully get paid.

One of the biggest reasons your claims may be getting denied is because you’re not using your Laboratory Information System (LIS) properly. Sometimes referred to as a Laboratory Information Management System (LIMS), an LIS is implemented in a laboratory to coordinate various aspects of data in your lab.

Regardless of specialty, labs across the U.S. who want to operate optimally will use an LIS to track their sample receipt, specimen processing, result entry, and patient demographics. A major trend across the US is that labs are using their LIS to track less and less of their data because billing process needs are shifting. But be wary of this. You need your LIS to help avoid denials.

Let’s dive into how to appropriately use the LIS to adapt to the new laboratory environment.
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LIS Limitations

There are a few areas of growing information that LIS often haven’t tracked due to their perceived role, and recency and complexity of the market change.

1. Information about the patient
2. Information about partner requirements
3. Information about lab requirements
4. Information about payer policies

With these areas becoming more of a headache to navigate with an LIS, some labs are making poor decisions about how to track this information (e.g., not in the LIS, or worse yet, not tracking this information at all.

But tracking these pieces of information is not a waste of resources. Tracking these pieces of information is increasingly critical to successfully getting paid. Your lab will benefit from tracking these new pieces of information in or close to the LIS; you just have to compensate for the complexity.

How to Compensate

Successful billing solutions and teams will compensate for LIS/LIMS deficiencies by building processes around it to get the information necessary for processing as early as possible.

Collect Data Up-Front

One thing successful labs do to utilize their LIS to help process claims better is to adamantly pursue up-front data collection. This means anything from patient information, scanning driver’s licenses, scans of insurance cards, following up on information changes, and any other relevant patient data is collected to aid the billing cycle.

As the market requires more and more information like ICD10 codes, CPT Codes, and Z Codes, the strong billing solutions incorporate these items explicitly into their process like explicitly planning panels and include gene descriptions and z-codes into custom fields or at the end of descriptions.

Click here to learn how pesky Z Codes affect processing.

Next, fill out medical necessity questions early on in your lab’s order process. Denials for “lack of pt medical necessity” are a key example of making a process moderately easier up front only to make it significantly more challenging later. Just imagine trying to arrange a phone call with a patient, AFTER a test has been done, to about family history. Contrast that with having the conversation prior to the test with the patient sitting in front of their trusted physician. Implementing processes to collect this early on protecting against denials or worse, an inability to bill successfully—think lost revenue.

Successful labs create a checklist of key questions to ask to send with the requisition to ensure all necessary information is acquired before the claim is sent off. Others alter the requisition itself (and this is a best practice). And making this question list standard for all of your requisitions rather than unique to one makes it easier for busy medical professionals—remembering one script rather than a different one for each requisition. These practices play more to the “rather have it and not need it than need it and not have it” thought process. Often, every piece of data isn’t needed; however, when there are denials for lack of patient data, the entire revenue cycle is thrown off.

Simply collecting all relevant information helps ensure a more seamless billing process, but sharing that information is how this data collection improves billing. And to improve billing, you need to share that with your billing team. If your billing team is outside your company, you’ll need to transfer information to them. The most common ways these transfers occur are via:

1. Manual extraction
2. HL7 or CSV Interface

Manual Extraction

This is the most common method for sharing data with an external billing company. The keys to the LIS are to allow remote access to all of the information needed to bill. Ideally, visibility into what’s coming so workflow planning can occur. There are 2 common ways remote access is offered to LIS: Web and Desktop / Application Sharing.

Web – If you access your LIS from a remote web site, then there’s a good chance you can configure something to allow your billing team to do so as well. This is often the easiest way to permit that and if its available for your LIS, you should consider implementing it.

Desktop/Application Sharing – when the application is not a web application, but rather a desktop application, technologies like Terminal Services for Windows, TeamViewer and LogMeIn are used.

The key frame of mind to adopt when setting up access like this is “what could the billing team benefit from seeing?” Think the number of accounts that they get, think about which reports and screens. And remember if they can’t see the data that was collected with the best practices above, it won’t affect their billing efforts.

HL7 or CSV Interface

This is the more involved of the two strategies but can yield tremendous benefits if done correctly. These two interface descriptions are about computers sharing information.

Now computers can share any kind of information they like, but in order to ensure the team receiving that information can use it, there’s a context of understanding that needs to be built.

For example, these files often send patient names with patient IDs. This might seem meaningless until you receive the 10th John Smith and then you need something more to identify the right one.

The second assumption that’s frequently overlooked is process assumptions. In labs, imagine saying “give me a file of all of your samples”… seemingly a reasonable request. However, for billing, the team probably doesn’t want all of them, just those that need to be billed.

That probably means eliminating the ones that have already been billed and those that aren’t ready to be billed. But if the LIS doesn’t have a status called “ready to be billed” what do you map it to? “Resulted”? Walking through these detailed questions is critical to building an interface that works.

The best labs often offer both manual access and an HL7 interface to their billing team. The HL7 to reduce work and make reconciliation explicit, and the manual interface to be able to work through nuances.

The best billing teams offer interfaces back into the LIS—to reduce the number of places your lab and admin teams need to look to get their work done. This is often done by a custom interface—sharing accession statuses, payments or even follow-up work needs. Getting data into the LIS helps everyone be more productive.

Don’t feel intimidated or behind if you’ve never heard of these. These interfaces are for your LIS but are handled by your IT specialist or tech team. But remember that they’ll need your support to answer business questions like what is “ready for billing”?

The point is that good labs leverage open communication in any way possible between the lab and the billing team or provider to ensure all data needed to process a claim is received.

Overall Takeaway

With the growing complexity of various billing cycle tasks, the LIS is needed to ensure proper information is collected and shared effectively with the billing team to have claims paid.

Collecting relevant, needed data is critical to ensuring minimal denials are received.

Utilize electronic and manual interfaces within your LIS to optimize functions with your billing team.

When handling your LIS, think about getting data in, not just out of your system.