I spent more than a decade running my own ASC-specific compliance, coding, and billing company before joining SIS. In that time, the single thing I've watched change most is the margin for error. Payers are more involved, procedures are more complex, and what a coder doesn't know can cost a center real money in both directions: missed reimbursement and compliance exposure. Here's what I think every ASC leader and coder should understand about where things stand right now.
Hospital coders specialize. A cardiology coder knows cardiology; a radiology coder knows radiology. ASC coders are expected to handle whatever comes through their center — and what comes through has been expanding. Cardiology and peripheral vascular procedures, for example, have moved into the ASC setting significantly over the last several years.
Physician practice coders face a related problem when they're asked to handle ASC coding. The two settings operate under different rules, different payer expectations, and different bundling logic. Strong experience in one specialty translates very little to surgery coding. Treating it like a lateral move is one of the more common and costly mistakes I see.
Payer policies drive the coding decision in a way they simply didn't a decade ago. Payers have established their own coverage rules that can diverge significantly from what the AMA or CMS says, and coders who aren't current on those policies will lose ground on both denials and reimbursement.
A practical example: some payers cover certain knee procedures only when the patient sustained a traumatic injury. Knowing that before the case is scheduled shapes the documentation requirements, the prior authorization conversation, and whether the center has a defensible position if the claim goes to appeal. That kind of upfront knowledge prevents the downstream billing problems that are far harder to unwind.
Knowing national payer policies is one layer. Knowing your local Medicare Administrative Contractor's (MAC) coverage determinations is another. And for organizations working with centers across multiple states, that means tracking policy variations from one end of the country to the other. Coders working alone at a single facility are the most exposed here. There's a phrase I use with new coders: you don't know what you don't know — and that's the reality of working without a broader team to lean on.
The most common misconception about coding audits is that they're primarily about catching errors that could create compliance exposure. That's certainly part of it, but audits are equally an opportunity to make sure you're getting paid for everything you're entitled to.
The AMA and CMS don't always agree on what procedures should bundle. Some commercial payers follow AMA guidelines; others follow Medicare guidelines. If your coder defaults to the more conservative interpretation across the board without knowing which payers follow which standard, you're going to be leaving money behind on a regular basis.
HCPCS reporting for drugs and implants is another area worth examining closely. Medicare typically packages most implants into the procedure rate, but many commercial payers will reimburse for implants separately, assuming it's been negotiated into the contract. ASCs that bring in physicians performing implant-heavy procedures need to have those conversations with payers before the first case is scheduled. The center is purchasing that implant based on the physician's expectation that the economics work. Verifying that independently is the ASC's responsibility.
On audit frequency: quarterly is the right cadence for most centers. Annual audits can allow the same error to repeat many times before anyone catches it, and by then timely filing windows with certain payers have closed. Quarterly audits create enough runway to correct course while the cases are still actionable.
A coder effectively handling cases and supporting the billing team on denials can realistically manage 60 to 100 cases per day. If your center isn't generating that volume, you're looking at a part-time role — and part-time coders often lack the ASC-specific depth and resources to keep pace with policy changes and complex cases. In that situation, outsourcing usually makes more sense financially and from a compliance standpoint.
It doesn't have to be all-or-nothing. A hybrid model works well for many centers: an in-house coder handles the routine case volume, and an outside team supports the complex or unfamiliar cases. I've worked with ASCs where a physician brings a procedure the facility has never coded before, and having a relationship with an external coding team for those situations is what keeps everyone compliant, confident, and ultimately gets the ASC paid. Think of it the way you think about legal counsel — you don't need a lawyer every day, but you always want one you can call.
Something worth being clear about: outsourcing coding doesn't transfer the compliance obligation. The ASC's administrator still needs to be watching the numbers, reviewing audit results, and holding the vendor accountable. Medicare requires a designated compliance officer and a compliance plan the facility can speak to. If an auditor walks in and asks who that is, "I'm not sure" is never an acceptable answer.
AI tools are becoming a meaningful part of ASC coding work, and the potential they represent is real. One of the most effective applications right now is research support — pulling together what multiple specialty societies say about bundling rules for a complex procedure, rather than manually working through dozens of sources. For a busy coding team, that kind of efficiency gain is worth paying attention to.
ASCs considering or expanding their use of AI-assisted coding tools should approach the decision carefully. A few principles that apply regardless of which tools you're evaluating:
Work with trusted vendors who understand ASC-specific coding requirements. General medical coding and ASC coding are not the same problem.
Keep experienced coders in the loop. AI works best as a resource for knowledgeable professionals who can evaluate its output, apply judgment the tool cannot, and catch it when it leads in the wrong direction.
Verify against governing body sources. Any AI output should be checked against AMA guidance, CMS policy, or the relevant specialty society before it's acted upon.
Audit AI-assisted work with the same rigor you'd apply to any coder. Tracking accuracy over time tells you where the tool adds value and where it needs closer human review.
The teams best positioned to benefit from AI are those who already have deep ASC coding experience. That foundation is what allows them to use AI productively and to recognize when it's pointing them somewhere they shouldn't go.
SIS offers tech-enabled coding, billing, and transcription solutions purpose-built for ASCs. If you're evaluating your current coding and billing model — whether in-house, outsourced, or hybrid — learn more about how SIS Revenue Cycle Services supports surgery centers.
Most medical coders work within a defined specialty and build deep expertise in that lane. ASC coders are expected to handle whatever their center performs, and the range of procedures moving into the ASC setting keeps expanding. Add to that the ASC-specific bundling rules, payer policy requirements, and HCPCS reporting obligations that don't apply in other settings, and you have a role that demands a genuinely different skill set. Experience in another coding specialty doesn't transfer as directly as many people assume.
Quarterly is the right cadence for most centers. The audit scope should capture a meaningful sample of cases per physician, and findings should feed directly back into coder education and workflow adjustments — that feedback loop is what keeps the same errors from recurring.
The clearest signal is case volume, but it's not the only one. Even centers that hit the volume threshold may find that the complexity of their case mix, gaps in staff expertise, or difficulty keeping pace with payer policy changes tips the decision toward outsourcing or a hybrid model. The staffing math is one input; the compliance and quality picture is the other.
AI works best as a starting point, not a final answer. The more important question is whether the people using it have enough ASC coding experience to evaluate what it produces — because without that baseline, there's no reliable way to catch it when it's wrong. Vendor selection matters too; tools built for general medical coding don't necessarily account for the ASC-specific rules and payer requirements that determine whether a claim holds up.