Inside the Claim Edit Library · Article 2 of 6
Before the Claim Takes Shape
A charge doesn't always travel directly from an electronic health record into a practice-management system unchanged. In some environments, another layer of software examines the information during that journey, identifies discrepancies, and performs defined actions before the charge enters billing.
This application of business-rule automation gives organizations an opportunity to address certain conditions while information is moving between applications, before the billing team encounters them in a completed claim.
Recognizing a problem and changing the underlying data, however, require different capabilities.
Where Inline Editing Fits
Inline editing refers to checks performed within an active processing workflow, although the term encompasses different functions across software products.
NextGen, for example, describes In-Line Edits within its PM billing environment. Its separately described Charge Review Rules Engine evaluates information moving from an EHR toward the PM system, with capabilities that include supported automated corrections and exception routing.
An edit working inside an encounter or billing workflow serves a different function from a charge-review application positioned between two systems. Both can identify issues before claim submission, but their timing, available data, and authorized actions depend on the technology and its configuration.
When a Business Rule Acts on the Information
Consider a practice where charges regularly arrive with a service location that doesn't match the encounter record.
Billing staff correct the claims individually, but the discrepancy continues appearing.
An upstream review rule could compare the incoming charge information against the documented service location before it reaches the PM system. Depending on the configuration, the system could flag the mismatch, route it for review, or apply an authorized correction when the correct location can be verified.
The scheduled location may differ from where the service was performed, so the rule must rely on a verified service location.
Without a reliable basis for selecting the correct value, an automated rule risks replacing one discrepancy with another.
Validation identifies the condition. Transformation goes further, changing the information according to an established instruction. Although a software platform can support both functions, the second requires greater confidence in the source information and business logic.
Automation Has Limits
Imagine a similar rule identifying a missing modifier.
The system might recognize that a particular combination deserves attention, but adding the modifier requires more than identifying its absence.
Modifiers can communicate circumstances about the service itself. Their use must be supported by documentation and applicable coding or billing requirements.
Automated correction is appropriate only when reliable information supports the change.
Some administrative values can be populated from an authoritative source under an approved rule. Coding-related changes often require additional documentation, review, or more restrictive conditions.
A dependable automation framework separates information the system can establish from decisions requiring human judgment.
The Value of Looking Upstream
Suppose a charge arrives in the PM system with an incorrect location, even though the originating EHR contains the right information.
Correcting the PM record could allow the claim to proceed. The discrepancy between the applications, however, remains unexplained.
Upstream review examines the source record, transmitted information, and receiving system's processing. Comparing these points helps identify whether the problem arose during entry, data mapping, transmission, or downstream interpretation.
When the source information is incorrect, the solution begins with reviewing the originating workflow. If the outgoing data is correct but the received information differs, attention shifts to the interface or receiving application's processing.
Identifying discrepancies earlier provides opportunities to resolve them before additional billing work accumulates. Still, some checks require coding or claim information that becomes available only later.
The most effective placement is the point where a system has enough reliable information to evaluate a condition and respond appropriately.
What Changes for the Billing Team?
Inline checks and upstream rules influence which problems reach billing staff and what information accompanies them.
In some workflows, discrepancies arrive as clearly identified exceptions instead of unexplained claim holds. Approved administrative corrections can take place before import, while issues requiring further evidence are directed to human review.
The underlying service must still be represented accurately. Automated processing doesn't replace correct documentation or qualified judgment.
Knowing where a rule operates helps explain why a charge was delayed, corrected, or redirected before it reached the billing department.
References & Further Learning
- NextGen Healthcare, Practice Management Coding and In-Line Edits
- NextGen Healthcare, Charge Review Rules Engine
About This Resource
Revenue Cycle Uncovered is an independent educational resource. Content is provided for general informational purposes and does not represent the policies, practices, or positions of any employer or organization. Workflows, payer requirements, regulations, and operational practices may vary. Information should be independently verified when applied to specific situations.