Where did all the money go? Exploring medical coding and billing errors
Improper healthcare spending can add up quickly when clinical information is lost or distorted across documentation, coding, and reimbursement.
EHRs sit at the center of this process. Physicians capture what is clinically happening, while hospitals and insurers need that information translated into standardized documentation and codes. When these layers do not align, the system compensates with reviews, queries, corrections, and audits, creating more administrative work and financial uncertainty.
EHRs Make Clinical Documentation Part of Reimbursement
EHRs serve two different purposes. For physicians, the medical record captures the patient’s condition, clinical evidence, diagnostic reasoning, treatment, and follow-up. For hospitals, insurers, and regulators, that same record must support coding, billing, quality reporting, compliance, and reimbursement.
This creates tension. Physicians think clinically, but reimbursement systems require clinical decisions to be documented with enough specificity for administrative systems to interpret them.
Health IT can support diagnosis and clinical care, but poor workflow integration and documentation requirements can increase cognitive burden and interfere with clinical reasoning.
Medical Coding Translates Clinical Decisions into Billing Data
Medical coding bridges clinical documentation and reimbursement.
Diagnoses, procedures, treatments, and other aspects of care are converted into standardized codes used for claims, reimbursement, quality measurement, and risk adjustment.
The difficulty is that clinical medicine and coding do not describe patients in exactly the same way. A physician may describe a condition accurately in clinical terms, while coding requires additional specificity about anatomy, severity, laterality, complications, or procedures.
With extensive and continuously updated code sets, physicians cannot reasonably master every coding distinction. Their primary responsibility is determining what is clinically happening.
Accurate coding therefore depends on collaboration. Physicians establish diagnoses and document clinical decisions, while coding professionals translate that documentation into standardized codes. Problems arise when the information needed for that translation is incomplete, inconsistent, or ambiguous.
CDI Correct Gaps After the Clinical Decision
Consider a patient hospitalized after a traffic accident.
At discharge, the physician records “left lower leg crushing injury with necrosis.” Clinically, the description may appear reasonable. But when the diagnosis enters the coding process, it may not contain enough specificity to map confidently to the appropriate code.
The coding team therefore sends a query asking the physician to clarify the documentation. The physician must reopen the case, reconstruct the clinical context, review the evidence again, and update the record while managing other patients.
Queries are an important safeguard, but they also highlight a limitation of traditional clinical documentation improvement (CDI) tools: information gaps are detected downstream, after they have already entered the medical record.
Making queries more efficient improves correction, but it does not prevent the gap from occurring in the first place.
Billing and Payment Errors Create System-Wide Financial Risk
The consequences grow once documentation and coding gaps reach reimbursement.
Some medical billing advocates have estimated that errors may appear in up to 80% of medical bills, although published estimates vary substantially depending on what is classified as an error. Problems can include incorrect codes, duplicate charges, missing information, and other discrepancies that affect payment.
In FY2022, Medicare FFS reported $31.46 billion in improper payments, with $21.2 billion attributable to missing or insufficient documentation, while incorrect coding accounted for another $3.3 billion. Medicare Part C reported $13.94 billion in improper payments, driven primarily by medical-record discrepancies that resulted in both overpayments and underpayments.
Their scale shows how consequential information integrity becomes once clinical information enters reimbursement systems. Patients may receive inaccurate bills, providers may face reimbursement or compliance risk, and payers may act on incomplete information.
What begins as an information gap at the point of care can become a financial and administrative problem downstream.
DxPrime Strengthens Diagnostic Integrity at the Point of Decision
This is the underlying problem that DxPrime aims to resolve.
DxPrime supports that decision by making the evidence easier to evaluate and identifying potential integrity gaps while there is still an opportunity to act. Physicians can confirm, update, resolve, rule out, or follow up on a condition before the diagnosis is translated into medical codes and propagated further through the healthcare system.
A physician-validated diagnosis creates a stronger foundation not only for documentation and coding, but also for clinical care, care continuity, quality measurement, reimbursement, auditability, and downstream use of health data.
The difference is therefore broader than moving coding intervention upstream.
Traditional downstream processes ask:
How do we correct the record after a discrepancy appears?
DxPrime asks:
How do we ensure the patient’s disease status is clinically supported, current, and traceable before that information becomes consequential across care, documentation, coding, and reimbursement?
Medical AI should not simply automate administrative correction. Its role should be to strengthen clinical reasoning where decisions are made, preserve the connection between evidence and physician judgment, and create a more reliable clinical foundation for every process that follows.
| Reference |
1. Medical billing errors growing, says Medical Billing Advocates of America