EHR Billing Fraud: When the Clinical Note Manufactures Support for a Claim

EHR billing fraud occurs when someone knowingly uses false clinical documentation or coding in electronic health records to support a claim for payment that the care provided does not justify. A copied examination, an auto-populated finding or a suggested code can travel from the chart into the bill. If you are the clinician who knows what happened, the coder who sees the mismatch or the compliance employee whose questions keep coming back unanswered, the important connection is between the care, the note, the code and the claim.

The software sits in the middle of that connection. Clinical and billing modules are commonly sold together, and the note supplies information for the charge. The Centers for Medicare & Medicaid Services describes a billing specialist or another reviewer helping choose codes before the claim goes out. The person documenting the encounter and the person submitting the bill may therefore see different parts of the same transaction.

What Constitutes Falsifying Medical Records?

Falsifying medical records includes entering findings or services that did not occur, or retaining copied information that falsely describes the encounter. In its report on hospital EHR fraud safeguards, the Department of Health and Human Services’ Office of Inspector General described how copied information and unedited template output could create inaccurate records and support inappropriate charges. The financial question is what someone did with that false account of the care.

For a clinician, the discrepancy may be between an examination performed and the examination described. For a coder, it may be between the service documented and the level selected. For a billing employee, it may be the claim that leaves the organization after those earlier decisions. We work through those connections with the person who knows the workflow.

The False Claims Act reaches people who knowingly send false bills to the government or cause someone else to send them. Who identified the inaccurate finding? Who received the correction? What happened to the claim afterward?

What Are the Risks of EHR Cut and Paste?

EHR cut and paste can carry inaccurate information into a later encounter and support charges for care the patient did not receive. The Inspector General calls the practice copy-pasting or cloning: information from one location is reproduced in another. Its concern is the material that goes forward without being updated or checked for accuracy.

Copy-forward can make an old account look current. An examination finding carried into the later record may look newly documented to someone reviewing that record on its own. The connection to billing comes when that finding helps support the claim for the later service.

The Inspector General’s contractor report explains why reviewing one claim at a time can miss the pattern. A reviewer may need to compare multiple claims from the same patient or provider to recognize copied language. The recurring text becomes meaningful when it is compared with the encounters it purports to describe.

That is where an insider’s account adds something the finished chart cannot. You may know which parts of a note came from the prior visit and which were actually reviewed during the current one. We connect that knowledge to the service billed and the organization’s handling of the discrepancy.

Templates Can Turn One Click Into an Examination

EHR templates can populate fields and generate extensive prose from a checkbox. The Inspector General described overdocumentation as false or irrelevant documentation that creates apparent support for a higher level of service. Its report identified the danger of generated text suggesting that the practitioner performed a more comprehensive service than actually occurred.

The mechanism matters because the text can arrive already written. A normal-finding macro or a checked box may supply the words that later appear to justify a charge. We want to understand what the user selected, what the system inserted and what the provider retained in the completed note. The amount of prose is much less informative than how it got there.

A 2022 Vassar College thesis, A Panacea or a Problem? Electronic Health Records and the Complicated Politics of Its Stakeholder Network, examines why records accumulate material useful to billing but less useful to care. It argues:

That analysis helps explain the design incentive. We find the tradeoff absurd: a record meant to inform the next clinician becomes harder to use because it is busy serving the bill. The checkbox can supply the prose in an instant.

EHR Upcoding After the Evaluation and Management Changes

EHR upcoding has to be examined against the payment rule for the service and date involved. The older evaluation and management framework rewarded documentation of examination elements across body areas and organ systems. Templates and normal-finding macros made that documentation faster to produce.

The Centers for Medicare & Medicaid Services changed office and outpatient visit selection effective January 1, 2021. Its Physician Fee Schedule rule explained that history and examination would stop determining those code levels. For the covered visit levels, selection would instead depend on medical decision making or the practitioner’s total time on the day of the visit.

The agency’s May 2026 evaluation and management guidance describes the change for most other evaluation and management visit families from January 1, 2023. It directs providers to choose the level using medical decision making or time and says documentation volume does not decide the service level billed.

That changes the comparison an insider brings us. A note full of examination findings, a claim based on time and a claim based on medical decision making each call for a different explanation of the service. We match the stated basis for the code to the work performed and the rule that applied then. The older incentive to fill the chart helps explain the software’s design. The applicable payment rule tells us what the claim actually relied on.

When a Code Suggestion Reaches the Billing Queue

A code suggestion becomes consequential when someone accepts it or software sends the resulting claim to billing. The useful account explains where a person reviewed the suggestion and where the process continued automatically.

The Health Care Compliance Association’s 2024 report on AI and compliance describes computer-assisted coding that lets a human accept, reject or modify suggested codes. It contrasts that with autonomous coding that reduces or removes human coding work and can send claims directly to billing.

The report also raises questions about how organizations handle a coder’s departure from a recommendation and how software responds to changing coding standards. Those are useful questions for a billing-fraud inquiry. If a coder challenged a suggested level, we want to understand the reason, the response and the code that ultimately reached the payer.

For someone working in revenue cycle, the important handoff may therefore occur after the clinician finishes the note. The clinician’s account, the coding review and the claim can show where an inaccurate description became a request for money. A system’s ability to repeat that path makes the configuration and the review process worth examining alongside individual encounters.

What Are Some Examples of Upcoding?

Billing a physician visit when the service should have been billed as a nurse visit is a concrete example. In an October 2021 enforcement notice, the Inspector General said RMS Lifeline and Vascular Surgery Associates of Richmond agreed to pay $79,668 to resolve allegations involving that discrepancy and false meaningful-use certifications.

The Inspector General alleged that the companies submitted physician-visit claims using CPT code 99212 that should have been nurse-visit claims using CPT code 99211. The other allegation concerned certifications that physicians qualified for EHR incentive payments when they were ineligible.

The visit allegation gives a clinician or coder a specific comparison: who provided the service and which service the claim represented. The incentive allegation concerns a different representation, whether the provider qualified for the program payment.

What Is an EHR Audit Log?

An EHR audit log records activity within the system, including when users access or change a record. It can connect the finished clinical text to the history of its creation. The Inspector General described date, time and user stamps as useful in identifying inconsistencies.

In its January 2014 contractor report, the Inspector General found that only three of 18 Medicare contractors reported using audit-log data in reviews or investigations. One used it to check whether the provider changed the record after the date of care. Another used it to assess the authenticity of entries.

The companion hospital report found another revealing split. All eight hospitals OIG visited described using their logs to monitor privacy, such as unauthorized chart viewing, rather than to detect inflated billing or fraudulent claims. Watching chart access. Overlooking the bill.

The hospital report also found uneven capture of billing-release events, entry methods and the original authorship of copied material. For an actual case, we examine the log’s fields and the product version: chart access, editing, signing, source-text information and release for billing each explain a different part of the sequence.

eClinicalWorks and certain employees agreed to pay a total of $155 million to resolve allegations about software capabilities and kickbacks. The Justice Department’s 2017 settlement announcement included an allegation that the software failed to record user actions accurately in an audit log. The history meant to expose changes allegedly failed to capture them accurately.

What Evidence Is Needed to Report Fraud?

We build an EHR billing fraud case with you by connecting the service, the clinical record, the selected code, the submitted claim and the people who understood the difference. In an EHR matter, the product version and the way the note was generated can explain how the same discrepancy appeared across encounters.

We examine the original and later notes alongside available creation history, coding decisions and claims. A template’s output explains what the system supplied. An edit explains what someone changed. A coder’s review explains the selected service level. The submitted claim identifies what the organization asked the payer to fund.

The organization’s response matters too. For a billing concern, we work with you to establish who understood the discrepancy, what they were told and what continued to reach the payer.

Can a Whistleblower Report EHR Fraud?

Yes. Health care professionals at a facility using NextGen’s software brought the whistleblower case resolved in its civil settlement. The people who used the product could see a problem from the customer side. Clinicians, coders, billing staff and software employees each bring a different view of the path from documentation to payment.

A whistleblower case under the False Claims Act can pay 15% to 30% of what the government recovers. We assess the payment connection and the evidence with you, and bring in whistleblower lawyers who understand EHR billing and the clinical work behind the codes.

When the Chart Supports a False Bill

If you know the chart supported bills for care the patient never received, speak with our whistleblower experts about the claims it supported. We build the case with you around the clinical facts, the software’s role and the decisions that put the bill in motion. Our team stays with you through the case and selects health care fraud whistleblower lawyers for the billing issues your evidence exposes.