Analytics
Avoiding ER Billing Mistakes: Data Insights From Empathia AI

Avoiding ER Billing Mistakes: Data Insights From Empathia AI

8 min read ·

Executive Summary

If you work in emergency medicine, you already know the drill: high acuity, unpredictable volume, and pretty much zero room for error. You’re juggling crashing patients, hallway beds, and a waiting room that never stops refilling—and somehow you’re supposed to produce pristine, audit-ready documentation on every visit.

No surprise that ER billing mistakes still slip through. But here’s the twist: most of those mistakes are totally preventable. And they’re quietly fueling:

  • Denied or delayed claims
  • Compliance headaches
  • Uncompensated care
  • And, yes, more physician burnout

Drawing on real-world patterns from thousands of emergency encounters supported by Empathia AI—an AI clinical assistant used by 10,000+ clinicians—this article unpacks:

  • The most common ER billing mistakes (and why they happen even to great clinicians)
  • How your documentation workflows directly shape billing accuracy and revenue
  • Where AI-powered charting actually reduces risk instead of adding it
  • Practical steps ER leaders can take in the next 30–60 days to clean up billing integrity

Introduction: The $0 Visit That Was Worth $1,200

A medical director at a busy community ED recently shared a story you might recognize all too well.

It was one of those long holiday weekends—the kind where the board is full and the waiting room feels like an airport. A physician picks up a chest pain case that’s clearly not simple. Over several hours, they order serial troponins, arrange a cardiology consult, keep the patient in observation, and spend serious time explaining risks, options, and next steps.

The care? Excellent.
The documentation? Not so much.

No serial reassessments. Bare-bones MDM. Almost no clue, on paper, how much thought and work went into keeping that patient safe.

The outcome:

  • Coded and billed as a low-level visit
  • Downcoded further by the payer
  • Hundreds of dollars in legitimate revenue gone—on a case that was absolutely not “simple”

The problem wasn’t the medicine. It was the story on the page.

Now zoom out. Imagine that same gap in documentation happening a few dozen times per week. Suddenly your ED is quietly losing six to seven figures a year—not because patients are less sick, but because the notes don’t show the true intensity of care.

In the chaos of the ER, billing and documentation errors aren’t just tedious paperwork issues. They’re operational, financial, and compliance risks rolled into one.

The upside? Once you understand why these errors keep happening, they’re incredibly fixable.

Market Insights: What the Data Reveals About ER Billing Errors

When you zoom out across thousands of emergency encounters supported by Empathia AI in North America, some patterns show up so consistently they’re almost predictable.

1. Under-documentation is more common than overbilling

We tend to hear a lot about upcoding, audits, and overbilling. But in most EDs, the real revenue killer is the opposite: quiet, chronic under-coding.

It usually traces back to things like:

  • Rushed or incomplete HPI and ROS
  • Reassessments that happen but never make it into the chart
  • Thin documentation of differential diagnoses and risk
  • Little or no mention of social determinants that add complexity

Think of it this way: you’re doing the work of a full novel, but what ends up documented is more like a short synopsis.

When ER teams start using AI tools like Empathia, a few things shift:

  • High-acuity cases end up with richer, fuller notes—without asking clinicians to type more
  • The medical decision-making (MDM) reads like the actual thought process, not a generic template
  • Those “copy-paste” notes that never justify higher-level billing start to fade out

As documentation gets more complete and precise, billing levels naturally rise to match the real intensity of care. Not inflated—just accurate.

2. Critical care time is frequently missed or undercounted

Critical care is one of the most common areas where EDs leave money on the table. In chart after chart, you see:

  • No clear documentation of total critical care time
  • No explicit link between that time and managing a critical illness
  • Procedure time not properly separated out when required

The data from AI-assisted charting paints a clear picture:

  • Clinicians are providing critical care far more often than they’re documenting it.
  • When AI prompts them to confirm time, criteria, and interventions, legitimate critical care codes show up much more reliably—and compliantly.

Imagine having a quiet, always-on scribe that reminds you, “Hey, this was a critical care situation—do you want to capture that formally?” That’s essentially what’s happening.

3. Procedural documentation is inconsistent

Laceration repairs, procedural sedation, joint reductions, central lines—the usual suspects. The care gets done, the patient improves, but in the chart you’ll often find:

  • Missing details like size, location, complexity, or time
  • No explicit consent documented
  • No note of complications—or that there weren’t any
  • Procedures lumped into the general visit note with no discrete entry

In Empathia’s emergency medicine workflows, procedures are captured using structured, ER-specific templates. The effect?

  • Billing capture improves because procedures aren’t “invisible” anymore
  • Note defensibility improves if a payer or auditor ever comes knocking

It’s like switching from scribbled napkin notes to a clean, organized logbook.

4. Multisystem and social complexity are chronically underrepresented

Every ER clinician thinks in complexity. On any given shift, you’re weighing:

  • Homelessness or unstable housing
  • Substance use and withdrawal risk
  • Non-adherence to meds or follow-up
  • Language barriers and health literacy
  • Polypharmacy and drug interactions
  • Unsafe or unsupported discharge environments

But that nuance often doesn’t make it into the chart in a way that supports billing. Real-world note analysis keeps showing:

  • High-complexity thinking squeezed into low-complexity documentation
  • Social and behavioral risk factors rarely tied directly to MDM
  • Legitimate opportunities for higher E/M levels getting lost

When AI note-generation is context aware and trained on emergency medicine, it can pull out that real-world complexity—simply from how clinicians naturally talk during the encounter. The end result: the chart sounds less like a checkbox list and more like the case you actually managed.

Why ER Billing Errors Happen: It’s the Workflow, Not the Will

Most ER clinicians don’t need another lecture on what “should” be documented. You already know. The problem isn’t knowledge—it’s the environment you’re operating in.

1. Time pressure and cognitive overload

On a typical shift, emergency physicians and PAs/NPs are:

  • Managing multiple active patients
  • Handling constant interruptions
  • Making high-stakes calls with incomplete information

In that setting, documentation and billing accuracy naturally get pushed to the back burner. Notes are often finished:

  • Between patients
  • At the very end of the shift
  • Or at home, when you’re already exhausted

That’s exactly when crucial details—reassessments, critical care time, MDM justification—slip through the cracks or get documented in vague, non-billable ways.

2. Fragmented tools and EMR friction

Even with “modern” EMRs, ER documentation can feel like:

  • Clicking through what feels like 47 tiny boxes
  • Typing narrative text into fields that don’t fit how you think
  • Copy-pasting from old notes just to keep up

In that kind of friction, shortcuts become survival strategies:

  • Reusing old templates that don’t quite fit
  • Skimming over MDM details because there’s no time
  • Skipping discrete procedure documentation altogether

The result? Clean, defensible, billing-friendly documentation becomes the exception instead of the norm.

3. Misalignment between documentation habits and billing frameworks

E/M guidelines, critical care rules, payer-specific quirks—they’re complex and constantly shifting.

ER clinicians, meanwhile, think in very practical terms:

  • “Is this patient sick, or sick-sick?”
  • “Can I safely send them home, or do they need a bed?”
  • “What can kill this patient, and did I rule it out?”

Unless there’s a translation layer that turns that real clinical reasoning into billing-ready documentation, mistakes and under-coding are basically built into the system.

It’s not that clinicians don’t care about billing—it’s that they’re already at full cognitive capacity taking care of the patient.

Product Relevance: How Empathia AI Helps ER Teams Avoid Billing Mistakes

This is where Empathia AI comes in. It’s an AI clinical assistant built to reduce charting time by up to 80% in emergency medicine while making documentation more complete and consistent.

It plugs into major EMRs like Epic, Cerner, Athena, MedAccess, Accuro, OSCAR, eClinicalWorks, NextGen, and others—so you’re not rebuilding your tech stack from scratch.

Here’s how that actually translates into fewer ER billing errors at the bedside.

1. Real-time capture of the full clinical story

Empathia can:

  • Record in-person, phone, or video visits in the ED
  • Turn those interactions into structured, ED-specific notes
  • Draft MDM, procedures, reassessments, discharge summaries, and billing codes

Instead of relying on end-of-shift memory, the AI listens as you go. That means:

  • Those serial exams you meant to document? They’re captured in real time.
  • Risk discussions and shared decision-making don’t get reduced to “patient informed.”
  • You’re not staring at a blank MDM, trying to reconstruct three hours of care from memory.

The result: the note actually tells the story you lived through with that patient—and supports the level of billing that story deserves.

2. Emergency-medicine–specific templates and language

Generic AI tools can generate words, but they often miss the nuances that matter in the ED:

  • Time-based critical care requirements
  • Common ED procedures and what needs to be documented
  • Visits with multiple problems and complex triage narratives

Empathia’s emergency medicine workflows are tuned to how ER clinicians think and talk, so the draft notes naturally include:

  • Differential diagnoses and risk stratification
  • Clinical reasoning for imaging, labs, and admission
  • Procedure details in a structured way that billing teams can use without guesswork

In other words, you keep practicing the way you always have; the AI just helps you put that thought process on paper in a billing-ready format.

3. Draft billing codes with clinician control

Empathia doesn’t just generate text—it can also suggest billing codes (E/M levels and procedures) based on what’s been documented, while keeping you 100% in control.

This acts like a built-in safety net:

  • Flags possible under-coding when the documented complexity is higher
  • Reduces “lost” procedures that happened but never made it to the claim
  • Creates more consistent capture of high-acuity visits across providers

Nothing gets submitted automatically. You can review, edit, and confirm everything. The goal isn’t to push billing higher at all costs—it’s to keep it accurate and compliant, without putting all the burden on your memory.

4. Works across settings and systems

Emergency care isn’t just the main ED bay anymore. It’s:

  • Main ED
  • Fast track / split-flow
  • Observation units
  • Tele-triage and virtual urgent care

Empathia is built to follow you wherever you’re seeing patients—clinic, hospital, telehealth, home visit, even offline—and then drop the finalized note into your existing EMR.

That means your documentation quality doesn’t depend on where the patient happened to be sitting.

Actionable Tips: How to Reduce ER Billing Errors in the Next 60 Days

Even if you’re not ready to roll out an AI assistant tomorrow, you can start tightening up ER billing accuracy right now. Then, if you decide to adopt AI later, these habits will plug in seamlessly.

1. Standardize your “non-negotiables” for every ED note

Work with your coding and compliance team to create a short, practical checklist. For E/M visits, every ED note should clearly show:

  • Chief complaint in the patient’s own words
  • HPI with onset, progression, and key context
  • Pertinent positives and negatives that actually support your differential
  • Relevant comorbidities and risk factors
  • Differential diagnoses and how you ruled out the dangerous ones
  • Why you ordered (or didn’t order) imaging, labs, or consults
  • Disposition and counseling, especially return precautions

Then make it easy to use:

  • Turn it into a quick-reference card at every workstation
  • Build it into a smart phrase
  • Or embed it into your EMR or AI tool as a template

The goal isn’t longer notes—it’s smarter notes that clearly show the thinking you already do.

2. Make critical care documentation explicit

Critical care is too valuable—clinically and financially—to leave vague. Standardize wording like:

  • “I provided a total of XX minutes of critical care time, excluding separately billable procedures, managing [specific life-threatening diagnosis or high-risk condition].”
  • List key interventions: titrating vasoactive meds, managing respiratory failure, acute stroke care, sepsis bundle coordination, etc.
  • Document serial reassessments and changes in status

If you’re using Empathia, you can fold this into:

  • Specialty-tuned critical care templates
  • Phrases you naturally say aloud, which the AI then turns into compliant text

That way, documenting critical care becomes routine rather than an afterthought.

3. Treat procedures as discrete, billable events—every time

For common ED procedures like laceration repair, LP, procedural sedation, central line placement, or fracture reduction, decide on your “required elements” up front:

  • Indication
  • Site, size, and complexity
  • Anesthesia or sedation details
  • Technique
  • Any complications—or that none occurred
  • Outcome and patient tolerance

Then configure your EMR or AI assistant so that when you say something like, “We performed a layered closure on a forearm laceration under local anesthesia,” it automatically expands into a complete procedure note with all the right elements.

You’re already doing the procedure—this just makes sure the chart doesn’t act like you didn’t.

4. Close the loop with billing and coding teams monthly

Instead of only hearing from coders when something goes wrong, turn them into partners. Once a month:

  • Review a small sample of recent ED charts together
  • Ask coders:
    • Where did we under-code because documentation was too thin?
    • Where did we create risk by over-coding without strong support?
  • Turn what you learn into:
    • Bite-sized teaching points (“Here’s one sentence that would’ve justified this level”)
    • Template tweaks or updated AI prompts

Many ER groups using Empathia build this directly into their workflow: coders share patterns, and Empathia’s clinician success team helps tune the AI templates so the same errors don’t keep happening.

5. Give clinicians tools that reduce documentation time—not add to it

If a solution slows clinicians down, it doesn’t matter how clever it is; it won’t survive more than a few shifts. When you evaluate documentation tools, look for ones that:

  • Cut charting time by at least half (50–75% is a good benchmark)
  • Integrate with your existing EMR (Epic, Cerner, Athena, MedAccess, Accuro, OSCAR, NextGen, etc.)
  • Require minimal IT support and work on the devices you already use
  • Are clearly tuned for emergency medicine rather than generic outpatient workflows

Empathia was designed with exactly this reality in mind. In ER-specific workflows, teams have seen up to 80% time reduction in documentation.

That reclaimed time isn’t just about going home earlier (though that’s nice). It’s what makes consistent, high-quality documentation actually sustainable on every shift.

Conclusion: Better Notes, Better Billing, Better Nights

Most ER billing mistakes aren’t about bad actors or shady coding. They’re the predictable result of smart, caring clinicians working in a system that asks them to document too much, too fast, in tools that were never really built for emergency medicine.

When you:

  • Capture the true complexity of your patients and their situations
  • Make critical care and procedures crystal clear in the note
  • Standardize a few non-negotiable elements in every chart
  • And give clinicians AI support that fits seamlessly into their workflow

…billing accuracy starts to improve almost automatically. Revenue rises to meet the actual acuity you’re already handling. Compliance risk shrinks. And clinicians head home with fewer unfinished charts and a little more gas left in the tank for the next shift.

Your Next Step

If you’re leading an ED or hospital group and you want to:

  • Cut documentation time by 2–3 hours per clinician per day
  • Capture legitimate revenue you’re currently leaving on the table
  • Improve documentation quality without cranking up burnout

It may be time to see what an AI clinical assistant built for emergency medicine can do.

You can:

  • Start a free trial of Empathia AI with up to 100 free encounters
  • Or book a demo for your team and walk through exactly how specialty-tuned ER workflows can reduce billing errors while lightening the documentation load

Your ED is already delivering high-value care under intense pressure. Let your documentation—and your billing—finally reflect that.