Automated Medical Billing Software for Specialty Practices | Marvix AI

77% of providers say it takes more than a month to collect payment. Most have responded by hiring more staff and adding review steps. And still, an estimated $125 billion¹ walks out the door every year. The problem was never the people.

It is the point in the visit where billing decisions get made. In specialty care, that moment is buried inside a complex encounter, and most billing tools never reach it. Marvix AI does.

Marvix AI approaches billing differently. We automate it at the source, inside the specialty care encounter, where complexity actually lives.

Specialty Billing Risks Without Automated Coding

How Marvix AI Automates Medical Billing for Specialty Care

1. Automated E/M Coding Based on Real Clinical Complexity

Specialty visits demand accurate Evaluation and Management leveling. Guesswork and manual calculation do not hold up and they cost practices real money when visits are consistently undercoded.

Marvix AI automatically assigns E/M codes using Medical Decision Making (MDM) guidelines, evaluating each encounter across the three MDM components that drive specialty billing:

1. The complexity of problems addressed
   The complexity of problems addressed, including stable chronic illnesses, acute illnesses, disease exacerbations, and conditions that may threaten organ function or overall patient stability.
   
   
2. The amount and type of data reviewed, including longitudinal records
   Marvix AIidentifies and scores each category of clinical data reviewed during the encounter, including laboratory tests, imaging, external notes, independent interpretation of diagnostic studies, and discussions with other physicians.
   
   
3. The risk of complications, morbidity, and comorbidities
   Risk scoring accounts for management decisions such as prescription drug management, therapy adjustments, potential medication toxicity, and other interventions that increase patient complexity.

The correct E/M level is assigned automatically, with a clear MDM rationale showing how problem complexity, data reviewed, and risk of complications drove the score. Add-on codes such as G2211 are applied where appropriate. Every code is supported by specialty-specific documentation that stands up to audit.

E/M Leveling Based on Total Physician Time

In some specialty encounters, E/M levels are determined by total physician time rather than Medical Decision Making.

Marvix AI automatically captures time spent across the full encounter, including pre-visit record review, patient counseling, documentation, and care coordination. It  applies the correct CPT time thresholds automatically when time-based billing is more appropriate.

The result is consistent E/M leveling that reflects the true cognitive load of specialty visits.

How Marvix AI Determines E/M Levels

Now let's see how Marvix AI generates E/M codes for a complex neurology case. 

How Marvix AI Generates Accurate E/M Codes for a Complex Neurology Visit

A 52-year-old male with a 14-year history of relapsing-remitting multiple sclerosis presents with worsening left-sided weakness, new visual blurring, and increased spasticity. He also has neurogenic bladder, chronic migraine, hypertension, and mild cognitive impairment related to demyelinating disease.

During the visit, the neurologist reviews prior MRI brain and cervical spine imaging, compares new scans, reviews lab monitoring for immunomodulatory therapy, and adjusts disease-modifying treatment. High-dose steroids are considered due to suspected relapse. Fall risk and functional decline are assessed. This is not a simple follow-up. It is longitudinal, high-risk neurological management with medication toxicity monitoring and active exacerbation.

For this case here’s what Marvix AI has generated:

How This Improves E/M Coding Accuracy

E/M codes capture the clinical reasoning behind the visit. Marvix AI generates a clear MDM rationale that shows how the complexity of problems addressed, the data reviewed, and the risk of complications determine the final E/M level.

In this case, a patient with long-standing multiple sclerosis presents with new neurological symptoms and imaging changes. The physician evaluates disease progression, reviews longitudinal imaging and lab data, and makes treatment decisions that include high-risk medications. All of this contributes to a moderate MDM level and supports the assigned E/M code.

Because the documentation links the clinical work directly to the coding decision, the visit is fully supported for billing and audit review.

2. Procedure Codes and Modifiers, Captured Correctly

Specialty care is often procedure-heavy and missing a procedure or a modifier is lost revenue.

Marvix AI detects billable procedures and generates the appropriate codes automatically. Each procedure is documented in a way that stands up to audit:

• Informed consent
• Anatomical site and laterality
• Medications, sedation, or anesthesia
• Procedural technique and approach
• Immediate outcomes and follow-up instructions

Required modifiers including laterality, repeat procedures, and staged or related procedures are attached to the correct codes without manual input.

This ensures procedure-driven specialty workflows are billed fully and accurately.

Let’s review the E/M codes Marvix AI assigned for a multi-year oncology case.

How Marvix AI Generates Procedure Codes and Modifiers for an Oncology Visit

A 64-year-old female with a 6-year history of metastatic breast cancer presents for chemotherapy infusion and evaluation of new right-sided chest wall pain. She previously underwent mastectomy with reconstruction and has an implanted port. She also has anemia related to chemotherapy and secondary hypertension from treatment.

During this encounter, the oncologist evaluates disease progression, orders tumor markers, performs port access, administers chemotherapy infusion, and adjusts supportive medications. The visit includes active cancer management and procedural administration.

For this case here’s what Marvix AI has generated:

How This Prevents Procedure Billing Errors

Procedure-heavy visits often include both a clinical evaluation and a treatment performed during the same encounter. If the modifier is missing or attached incorrectly, payers may bundle the services together and reimburse only the procedure.

In this case, the oncologist evaluates a new symptom, reviews imaging and lab data, and manages ongoing cancer treatment. The same visit also includes chemotherapy administration through an implanted port. The modifier clearly indicates that the evaluation and the procedure represent two distinct clinical services.

By attaching the correct modifier automatically, Marvix ensures the procedure and the physician’s evaluation are billed correctly and fully supported by documentation.

3. Automated ICD-10-CM Diagnosis Coding That Reflects Longitudinal Care

Diagnosis coding in specialty care is rarely limited to what was discussed in a single visit. Patients carry conditions that affect risk, management, and reimbursement, even when those conditions are not the primary focus of a given encounter.

This prevents undercoding in patients with long histories and multiple conditions which is one of the most common and costly billing gaps in specialty practice.

How it Works

Marvix AI assigns ICD-10-CM codes according to the latest guidelines, with specificity and laterality where applicable. More importantly, it builds diagnosis lists longitudinally.

These longitudinal diagnoses also support accurate risk adjustment and reflect the patient’s overall disease burden during specialty care management.

Diagnoses are pulled from the current visit and all prior encounters to create a complete problem list. Clinically relevant conditions are captured even if they were not actively discussed during the visit. Even problems that are not discussed during the visit but are documented in the patient’s history are included during billing code generation, ensuring no billable condition is missed.

This prevents undercoding in patients with long histories and multiple conditions, which is common in specialty practices.

Let’s explore how Marvix AI handles ICD-10-CM coding for a high-complexity cardiology visit.

How Marvix AI Captures Longitudinal ICD-10 Codes for a Cardiology Encounter

A 72-year-old male with a 10-year history of ischemic cardiomyopathy presents for routine follow-up. He has chronic systolic heart failure, permanent atrial fibrillation, stage 3 chronic kidney disease, prior myocardial infarction, hyperlipidemia, and an implanted defibrillator.

During this visit, heart failure is stable and medications are continued. Kidney function is reviewed but not deeply discussed. Atrial fibrillation remains controlled. The ICD device is interrogated. Even though CKD and hyperlipidemia are not the primary focus, they are clinically relevant and impact risk and management.

For this case here’s what Marvix AI has generated:

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Why Accurate Diagnosis Coding Matters

Diagnosis coding reflects the full clinical picture of the patient, not just the primary issue discussed during a single visit. In specialty care, patients often have multiple chronic conditions that influence treatment decisions, risk levels, and reimbursement.

In this case, the patient presents for routine cardiology follow-up, but several underlying conditions shape the encounter. Ischemic cardiomyopathy, chronic systolic heart failure, permanent atrial fibrillation, and stage 3 chronic kidney disease all affect medication management, monitoring, and long-term care planning. The presence of an implanted defibrillator also changes how the patient is evaluated and followed.

By generating a complete list of ICD-10-CM diagnoses from both the current encounter and prior records, Marvix captures the patient’s full disease burden. This supports accurate risk adjustment, reflects the longitudinal nature of specialty care, and prevents undercoding in patients with complex medical histories.

4. Automated HCC and RAF Aligned Risk Coding

Risk adjustment is foundational to accurate reimbursement.

Marvix integrates HCC coding directly into the encounter workflow. It identifies qualifying diagnoses from the full patient record and automatically generates RAF scores based on aggregated HCC data.

There is no need for separate HCC reviews or retrospective chart audits. Risk is captured as care is delivered.

Let’s take a look at the HCC and RAF scores Marvix generated for an orthopedic case.

How Marvix Generates HCC and RAF Codes for an Orthopedic Visit

A 64-year-old female with a history of bilateral knee osteoarthritis presents for follow-up due to worsening right knee pain. Her history includes obesity, hypertension, and a prior medial meniscus tear confirmed on MRI three years ago. She previously received corticosteroid injections for symptom relief and completed a course of physical therapy.

During this visit, the provider reviews prior imaging and recent knee X-rays, evaluates joint tenderness, swelling, and range of motion, and assesses functional limitations with walking and stair use. Conservative management is discussed, pain control options are reviewed, and an intra-articular corticosteroid injection is performed for symptomatic relief.

For this case here’s what Marvix AI has generated:

How This Supports Accurate Risk Adjustment

In risk-adjusted reimbursement models, documenting the full clinical picture is essential. Conditions such as obesity, hypertension, and hyperlipidemia influence disease progression, treatment planning, and overall patient risk, even when the visit focuses on a specific issue like worsening knee osteoarthritis.

Marvix captures these conditions when they meet MEAT criteria (Monitor, Evaluate, Assess/Address, Treat) and includes them alongside the primary diagnosis. By pulling relevant diagnoses from the encounter and longitudinal history, it ensures that the patient’s documented disease burden accurately reflects their clinical complexity.

This supports accurate HCC capture and RAF scoring, which directly affects reimbursement in value-based care programs while keeping documentation aligned with clinical evidence.

Reviewable, Editable, and Audit-Ready Billing Outputs

Before these codes are pushed into the EHR, providers or authorized staff can review and edit the generated codes. Every code is supported by clear specialty-specific documentation, explicit coding justification, and complete patient history. 

Codes are delivered in billing-ready format so they can be pushed directly into the EHR without manual re-entry.

Practices using Marvix see higher first-pass acceptance rates, fewer denials, faster claims processing, and far less back-and-forth between providers and billing teams.

Conclusion

Specialty care cannot rely on generic billing automation. It requires systems that understand longitudinal care, procedural intensity, and clinical risk. Marvix flags documentation gaps that could lead to claim denials, such as unsupported E/M levels, missing modifiers, or incomplete procedural documentation.

It brings documentation, coding, and risk adjustment into a single workflow, built around how specialty care actually works. When billing is accurate at the encounter, everything downstream moves faster: reducing denials, less rework, capturing missed revenue and eliminating manual MDM calculation.

Practices that fix billing at the source do not just recover missed revenue. Six months in, they spend less time on claim follow-up, less time on documentation cleanup, and more time on care.

Start your 30-day free trial of Marvix, customized to your workflow and integrated directly with your EHR (even during trial.)