Latest Lab Billing Trends Are AI, More Transparency

Lab coding, billing, and collection companies are incorporating AI into their service offerings

CEO SUMMARY: From predictive analytics to data curation to improved online payment options, the newest trends in billing allow clinical laboratories and anatomic pathology groups to boost their financial bottom lines without putting more pressure on patients. Technology is at the core of these developments, particularly software that analyzes and curates clinical and patient data. One might even say that a revolution in lab revenue cycle management (RCM) is underway.

MORE LABORATORY BILLING FIRMS are embracing artificial intelligence (AI) to help maximize their accounts receivable process. Among the benefits are increased transparency into problematic claims and predictive analytics to identify actual dollars that could be collected. 

Incorporating AI-powered solutions into the coding, billing, and collections functions is a major trend with both clinical laboratories and anatomic pathology groups. AI automates many manual processes while simultaneously improving the accuracy of these processes. This, in turn, leads to a larger proportion of clean claims at first submission, generating more revenue to the lab. 

These developments are coming at a time when federal regulatory changes are putting increased pressure on billing companies to keep up with the ever-evolving world of lab billing and coding. AI is helping clinical laboratories increase revenues through a reduction in accounts receivable and front-end denials, as well as faster turnaround in resubmission of denied claims.

For clinical laboratories and pathology groups, a sound knowledge of current trends in revenue management is a must. It can make negotiations with vendors more fruitful—whether it is to determine a renewal of a prior agreement or evaluate a new service. Consider it a positive when a service provider is familiar with one or more of the advancements below.

Predictive Analytics

For example, one big change in laboratory revenue cycle management (RCM) in recent years is the use of predictive analytics to identify which claims are most likely to be paid. This allows billing companies to focus their resources on the claims for which they presumably will collect payment. 

Problematic claim submissions make up a significant portion of revenue loss for clinical laboratories and pathology groups, observed Mick Raich, founder of Vachette Pathology in Toledo, Ohio. The most common reasons for claim rejections include missing or inaccurate patient information, lack of proper authorization indicated on the claim, and incorrect ICD-10 codes.

Predictive analytics uses AI to allow billers to analyze large volumes of data and predict outcomes. For example, AI can identify which types of claims are most likely to be paid on first submission and which claims may be denied, Raich explained.

“AI allows billers to say, ‘Here are our top 25 denial codes, and if we clean up these three denial codes, that equals $26,000,’” he said. “It allows billers to work the right claims at the right time.”

Predictive Analytics Tool

Advanced Data Systems (ADS) in Paramus, N.J., provides billing and outsourced RCM services for laboratories and healthcare providers. It uses its MedicsPremier platform, a predictive analytics tool, to determine true accounts receivable, allowing laboratories and RCM firms to focus their resources better, explained Jim O’Neill, Laboratory Services Business Development Manager at ADS.

“When we know the actual dollar amount that stands to be collected, we can allocate the appropriate staff to gather the missing information,” O’Neill explained. “By putting an actual dollar figure on the claims, it gives incentives for the RCM company and the laboratory to fix those claims as soon as possible.”

In addition to identifying which types of claims are most likely to be paid, predictive analytics also highlights problems in denied claims, enabling clinical laboratories to improve their submissions from the start, Raich said.

Analyzing Denial Codes

“Once you analyze your denial codes, you can see what you’re doing wrong,” he added. “This way, you can make those fixes up front to improve the likelihood that those claims will get paid.”

Increased transparency into what is happening with claims is another technique allowing RCM firms to improve collections on behalf of their clinical laboratory clients.

Billers have long used dashboards to give their clients information on accounts receivable, but too often those dashboards simply offer a snapshot in time and do not give full transparency into what is happening with the claims. RCM vendors now are improving the usefulness of these dashboards by giving clients more insight into the claims process.

ADS, for example, recently introduced a new tool that gives 100% transparency between laboratory staff and the ADS response team, O’Neill explained. Laboratory customers now have on-demand access to all data used by a given revenue management company. As soon as the billing system identifies a problem with a claim, it is assigned to an ADS team member, who works closely with the lab staff to resolve the issues.

Replacing Cumbersome Tools 

“Previously more cumbersome tools handled this process,” O’Neill said. “Labs and RCMs were passing data back and forth through Excel, which can be time consuming and even result in lost data.”

The ability of an RCM company to resolve problematic claims in collaboration with the clinical laboratory can result in faster turnaround on collections. For ADS customers, increased transparency has led to a seven-to-10-day improvement in customers getting claims filed and rejected claims resubmitted, O’Neill noted.

“This results in fewer denials, faster turnaround on collections, and less time spent by lab staff on billing issues,” he said, adding that the improvements in lab billing have helped ADS lab customers increase revenue by an average of 20% in a year.

One challenge that all clinical laboratories and RCM firms face is locating important information that is absent from claims. Missing or bad data is a significant pain point in the billing cycle, Raich noted, who added that from 10% to 18% of data in lab billing claims is bad. Such flawed information can be a result of many factors, ranging from a patient moving to a new address to that person switching health insurers.

Automating Data Curation

Typically, to locate missing information, RCM staff need to make phone calls or send e-mails to providers, a task that is time consuming and costly. In response, many revenue cycle management firms are turning to data curation to fill those holes and save themselves back-and-forth communication with providers. Essentially, curated data is a collection of datasets selected and managed to meet the needs of a specific group of clients. 

Several companies specialize in gathering and curating data specifically related to healthcare claims. ADS, for example, partners with Wave HDC in Philadelphia to gather missing claims information without needing to engage with the physician or the patient. Wave uses multiple methods to find, verify, and correct data attributes, such as patient demographics, medical insurance information, and medical beneficiary identifiers.

Adding Missing Data to Claims

“We can add missing data to claims—such as insurance information—then resubmit those claims,” O’Neill said. “This has helped us recoup hundreds of thousands to millions of dollars for our laboratory clients.”

As clinical laboratories face increasing challenges in obtaining payment for their services, advancements in revenue cycle management can help labs improve their collections, often without inconveniencing patients. What may be most striking to observant laboratory directors and pathologists is how vendors who provide clinical lab services are themselves incorporating other companies’ systems and products into their own service menu. The resulting service or product delivers more value to the lab client. This arrangement is not limited to the clinical laboratory industry, but is true throughout the business-to-business software world. 

When lab managers are researching RCM companies, it is worth asking vendors how they incorporate the products of partners into their lab services. This fuller picture can better illustrate the RCM capabilities for which a clinical lab or pathology group will pay. A vendor may not outwardly advertise predictive analytics, for example, but that doesn’t mean such a function isn’t at work behind the scenes.

Contact Mick Raich at or 517-403-0763; Jim O’Neill at or 609-517-6242.

Online Features Ease Payment for Lab Tests

ANOTHER WAY OF INCREASING LAB CLAIMS COLLECTIONS is simply to make it easier for patients to pay their bills. Revenue cycle management (RCM) firms can help in this regard. 

“Insurance companies now put more of the responsibility on patients, so labs and RCMs must be responsive to this development,” said Jim O’Neill, Laboratory Services Business Development Manager at Advanced Data Systems (ADS) in Paramus, N.J. “More companies now use online tools for bill paying, but the tools are only effective if the online invoice matches the invoice the patient has in hand.”

For example, ADS allows clinical laboratories and RCM companies to collect payment from patients through their mobile phones or on their computers. As patients use the online system to schedule their next appointments, they can view outstanding balances and receive a prompt to make a payment. The system also sends automated alerts if patients miss their payments.



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