What Are the Effects of Not Scrubbing Claims?

Claim scrubbing is an important process in the financial and medical claims submission landscape. It involves reviewing claims for errors and inconsistencies before they are sent to payers. It identifies issues like incorrect coding, missing information, or non-compliance with regulatory guidelines, allowing corrections before submission. Accurate and complete claims facilitate efficient operations and timely reimbursement.

Impact on Reimbursement and Revenue

Failing to scrub claims impacts an organization’s financial health by disrupting reimbursement and revenue streams. Unscrubbed claims often result in rejections or denials from payers, causing delays in payment. For instance, a claim with incorrect coding or incomplete patient information is often denied, requiring a resubmission. This cycle extends the accounts receivable period, disrupting cash flow and hindering an organization’s ability to cover expenses or invest in growth.

Unscrubbed claims also lead to direct revenue loss. Many denied claims are never reworked, resulting in lost income for services rendered. Industry estimates indicate that denial rates can range from 5% to 15% of total claims submitted, representing billions of dollars in lost revenue annually across the healthcare sector. Reprocessing denied claims further erodes profitability. Reworking a single denied claim can cost an organization between $25 and $118, which quickly accumulates and impacts the bottom line.

Unscrubbed claims can lead to overpayments, prompting insurance companies or government agencies to initiate recoupment. They reclaim excess funds, often by deducting from future reimbursements. These recoupments, from errors like duplicate billing, impact cash flow and strain payer relationships.

Increased Administrative Workload

Lack of thorough claim scrubbing increases administrative burdens. Rejected or denied claims require staff to dedicate time and resources to investigate. This involves reviewing patient records, verifying coding, and correcting information. Correcting and resubmitting claims, plus follow-up, diverts personnel from other responsibilities.

Addressing problematic claims manually consumes staff time that could be spent on patient care or financial management. This includes phone calls to payers to understand denial reasons or appeal decisions. Extensive record-keeping is required for each rejected claim, documenting the denial reason, corrections, and resubmission details. This repeated processing decreases productivity and contributes to staff burnout due to its repetitive nature.

Compliance and Audit Implications

Unscrubbed or erroneous claims carry regulatory and legal risks. Repeated billing errors can trigger audits from regulatory bodies like the Centers for Medicare & Medicaid Services (CMS) or private payers. Audits lead to scrutiny of billing practices, consuming time and resources. Non-compliance, even unintentional, can result in penalties, fines, or recoupments.

Federal laws, such as the False Claims Act (FCA), impose penalties for submitting false claims to government programs like Medicare and Medicaid. Penalties under the FCA can include fines of up to three times the amount of damages sustained by the government, plus additional civil penalties ranging from $12,000 to $24,000 per false claim. Even “honest mistakes” can lead to liability under the FCA if there was deliberate ignorance or reckless disregard for the truth. Violations of the Health Insurance Portability and Accountability Act (HIPAA) due to improper handling of protected health information in billing result in fines ranging from $100 to $50,000 per violation, with an annual maximum of $1.5 million for identical violations.

A poor claims history can damage an organization’s reputation with payers and regulatory agencies. This can lead to a loss of trust, affecting future contracts or relationships with insurers and patients. In severe cases, non-compliance can result in exclusion from federal healthcare programs or criminal charges, especially when fraud is identified.