Before Claims Leave: A Scrubbing Playbook for Dermatology Teams

# Before Claims Leave: A Scrubbing Playbook for Dermatology Teams A dermatology claim can look complete and still contain a preventable problem: a procedure linked to the wrong diagnosis, an unsupported modifier, or a lesion count that does not match the note. Finding that problem before submission is usually easier than correcting it after a rejection or denial. Claim scrubbing is the structured review of claim data against billing requirements before submission. Done well, it checks more than empty fields. It connects the claim to the documented service, applicable coding rules, and payer requirements. The goal is not simply to make claims pass an automated test. It is to submit accurate, defensible claims—and learn why errors keep entering the workflow. ## Define “Clean” Before Measuring Improvement Clean claim rate is not calculated consistently across organizations. One dashboard may count claims accepted by a clearinghouse; another may count claims processed without correction. Those measures answer different questions. For an internal improvement program, define your operational clean claim rate explicitly. One useful definition is: **Clean claim rate = claims processed without a rejection, denial, or post-submission correction ÷ claims with a known processing outcome in the same submission cohort × 100.** Group claims by original submission date, allow time for outcomes to arrive, and disclose how many remain pending. Do not count resubmissions as new claims. A recent cohort with many unresolved claims is not directly comparable to a mature one. Track these companion measures separately: - **First-pass acceptance:** Original submissions accepted at the clearinghouse or payer intake stage. Identify which checkpoint you mean. - **Pre-submission edit rate:** Claims flagged before their initial release. - **Denial rate:** Claims denied during adjudication, using a consistent claim-level or line-level definition. - **Time to release:** Time between a claim becoming ready for billing and its submission. A claim can pass intake and still be denied. Likewise, a claim corrected internally before submission can ultimately be clean, while still revealing an upstream workflow problem. Your operational definition also may differ from a payer’s contractual or regulatory definition of a clean claim. ## Build Three Layers of Claim Review ### 1. Administrative and transaction checks Start with information that determines whether a claim can enter processing correctly: - Patient name, date of birth, and subscriber relationship. - Member identifier and appropriate payer routing. - Billing and rendering provider identifiers. - Service date and place of service. - Required referring provider or authorization information, when applicable. - Valid, current codes and required claim fields. Eligibility checks belong upstream, but claim scrubbing should catch unresolved discrepancies. An eligibility response is not a guarantee of payment, and an authorization does not automatically establish coverage for every billed service. ### 2. Coding and payer-rule checks Next, evaluate relationships among codes, units, diagnoses, modifiers, and service dates. Use current coding references, applicable National Correct Coding Initiative edits, and payer policies rather than relying solely on historical payment patterns. Review: - Procedure combinations that may be bundled. - Add-on codes without an appropriate primary service. - Units inconsistent with the documented services. - Diagnosis pointers connecting each procedure to its supporting diagnosis. - Modifier requirements and supporting documentation. - Potential duplicate services or global-period conflicts. A rule should explain why a claim is flagged. “Invalid combination” is less useful than an edit identifying the affected lines, applicable rule, and required review. ### 3. Documentation support Some errors cannot be resolved from claim fields alone. The record may need to establish lesion location, technique, measurements, medical necessity, or whether a separate evaluation occurred. When documentation is insufficient, route a specific question to the clinician. Do not select a more convenient diagnosis or add a modifier just to bypass an edit. Any clarification should follow the practice’s documentation amendment policy and preserve the audit trail. ## Use Dermatology Scenarios to Test Your Rules The following examples are hypothetical. Coding decisions depend on the complete record, current guidance, and payer requirements. ### Same-day evaluation and procedure A patient receives treatment for a lesion and also has an evaluation of an unrelated rash. The claim includes an office visit and a procedure. The scrubber should prompt review of whether the evaluation and management service was significant and separately identifiable beyond the work ordinarily associated with the procedure. Modifier 25, when appropriate, belongs on the evaluation and management service. A different diagnosis alone does not establish that a separate visit is billable. Nor is a different diagnosis always required. The documentation must support the separate service. ### Several lesions, different services A clinician biopsies one lesion and destroys other lesions during the same encounter. A generic procedure list may obscure which diagnosis, site, and technique belong together. The review should reconcile each billed service with the documented lesion or lesion group. Distinct sites may matter when assessing an edit, but they do not automatically justify an override. Confirm whether the applicable edit permits a modifier and whether the circumstances support its use. ### Excision measurements and claim release An excision code may depend on anatomic location and excised diameter, including margins, as defined by the applicable coding guidance. A note containing only the visible lesion measurement may not supply everything needed. Route missing measurements for clarification rather than estimating them from a photograph or pathology specimen. Establish when pathology must be reviewed before final coding, without unnecessarily holding every dermatology procedure claim for a result. ## Make Every Edit Actionable A scrubber that flags everything eventually gets ignored. Separate findings into three operational categories: | Category | Appropriate use | Next action | | --- | --- | --- | | Hard stop | Missing required data or a clearly invalid submission element | Correct before release | | Review required | A coding or coverage issue needs judgment | Route to the designated reviewer | | Advisory | A potential issue warrants attention but is not automatically blocking | Review under a documented policy | For each recurring edit, document its owner, supporting reference, correction steps, and escalation path. Require an explanation for overrides and periodically audit them. Avoid a single shared queue with no accountability. Registration should resolve demographic discrepancies; billing should handle claim construction; qualified coding staff should review coding conflicts; clinicians should clarify clinical documentation. Measure queue age as well as volume. An apparently excellent clean claim rate is not a success if difficult claims sit unsubmitted until timely filing becomes a risk. ## Connect the Workflow Without Automating Judgment IKON EMR’s AI-powered EMR/EHR environment brings relevant functions into this discussion: AI scribe, telemedicine, billing, and patient portal tools. Their value depends on how the practice connects documentation, patient information, and billing review—not on treating automation as a substitute for oversight. An AI scribe can assist with drafting the visit narrative, but the clinician must verify lesion details, measurements, and services performed. Patient portal workflows can help collect updated patient information; staff still need to validate billing-critical changes. Telemedicine encounters require their own review of current payer rules, including applicable place-of-service and modifier requirements. When evaluating IKON EMR’s billing workflow, ask to see how edits are surfaced, assigned, corrected, and traced. Confirm which checks are native, which depend on a clearinghouse, and which require human review. HIPAA compliance also belongs in the design: use appropriate access controls and approved communication channels, and avoid moving patient information into unsecured spreadsheets or messages to resolve billing questions. ## Turn Repeated Errors Into Upstream Fixes Review a manageable sample of recent edits, rejections, and denials each week. Group findings by root cause rather than only by payer response code. Use this checklist: - [ ] Identify the most frequent preventable error categories. - [ ] Find where each error first entered the workflow. - [ ] Assign one owner to change that step. - [ ] Test the change against representative claims. - [ ] Check for unnecessary holds or false-positive edits. - [ ] Compare outcomes using consistent, sufficiently mature cohorts. For example, repeated missing excision measurements may call for a better procedure template, not another billing reminder. Repeated diagnosis-pointer errors may call for changing how charges are assembled. ## FAQ ### Does claim scrubbing prevent every denial? No. It reduces detectable errors before submission. Coverage decisions, benefit limitations, payer processing issues, and other circumstances can still produce denials. ### What is a good clean claim rate? Start with a reliable baseline and a clearly documented definition. Comparisons are useful only when measurement methods, outcome windows, and claim populations are comparable. ### Should every flagged claim be held? No. Hard stops and judgment-based reviews need different handling. Document release criteria, escalation responsibilities, and override reasons. ### How often should scrubbing rules change? Review them when coding guidance, payer policies, or workflows change, and when denial patterns reveal gaps. Assign an owner to validate updates before broad deployment. The most useful scrubber is not the one that generates the most warnings. It is the one that catches meaningful problems, directs them to the right person, and helps the practice stop creating them.