How a Multi-Site Vascular Practice Recovered $4.1M and Cut $258K in Coding Costs in 12 Months

Executive summary

A 12-location, 14-provider outpatient vascular surgery and office-based lab (OBL) group in the Mid-Atlantic adopted the Medmio platform in 2024 to replace a manual, vendor-coded billing workflow that was leaking revenue at both ends of every encounter. Over twelve months, the practice recovered $4.1M in revenue that would have been written off, saved $258K in coding-vendor costs, and posted charges 4.7 days faster across 92,400 coded encounters — all without migrating off their existing EHR.

The practice

Twelve vascular care locations across multiple states, with 14 vascular surgeons and interventionalists splitting time between clinic visits, ultrasound studies, and OBL procedure days. Annual encounter volume above 90,000, with a payer mix weighted toward Medicare and large commercial carriers. Before Medmio, providers documented in their primary EHR, paper or in-EMR superbills routed to an external coding vendor, and the vendor returned coded claims to the in-house biller. The third-party coding contract ran roughly $300K annually, and the practice administrator suspected significant under-capture on the OBL side without the data to quantify it.

The challenge

Three concrete problems shaped the engagement:

1. Charge lag. Median time from encounter to clean coded charge on the clearinghouse was over a week. By the time low-confidence claims resolved, payer timely-filing windows were shrinking.
2. Lost charges. Procedure-day OBL work — phlebectomies, ablations, sclerotherapy — was leaking 3–5% of cases monthly through missed superbill entries, especially when patients rolled into a procedure mid-clinic.
3. Vendor cost vs. quality. The coding vendor charged per claim regardless of complexity, and denial root-cause data wasn't reaching the practice administrator — denials were re-coded silently, leaving no way to spot systemic issues like bundling or modifier errors.

Three competing automated-coding vendors had been evaluated. Two were priced for hospital systems ($200K+/year minimum). The third required a full EHR migration.

What changed

The practice deployed three Medmio modules in a phased pilot:

• Charge Capture (mobile app) — providers entered every clinic and OBL charge from an iPhone at the point of care, against a daily worklist of scheduled encounters. Custom CPT favorites per provider. Offline-capable for the OBL suite, where Wi-Fi coverage was inconsistent.
• CodeSight^TM — Medmio's automated coding engine ingested the clinical note via HL7, ran a six-stage pipeline (NLP parser → ICD-10 model → CPT model → consensus layer → payer rulebook → confidence scorer), and pushed back ICD-10 + CPT codes with confidence scores. Codes above 95% confidence auto-posted; lower-confidence ones routed to a Portal reviewer queue.
• Patient Recovery Queues (PRQ) — automated follow-up workflows triggered on denials, no-shows, missing documentation, and aged accounts.

The Analytics dashboard came online a month after pilot start, giving the practice administrator a single view of charge lag, denial rate, and net collection by provider, location, and payer.

Implementation timeline

Week	Milestone
1	HL7 channel design with practice's EHR; sandbox testing
2–3	Mobile app rollout to a pilot subset of 4 providers; CodeSightTM in shadow mode
4	Full provider rollout; CodeSightTM switched to autonomous-with-review
6	Coding-vendor contract notice-period letter sent
8	PRQ activated against full denial history
12	Coding vendor sunset; Medmio took over end-to-end

Time from contract signature to first claim through CodeSight^TM: 14 days. The pilot ran 30 days before commitment to platform-wide rollout.

Results after 12 months

• $258K saved annually. Full elimination of the third-party coding vendor. The practice retained one in-house RCM analyst to oversee the CodeSight^TM review queue — a new role that cost less than 20% of the prior vendor spend.
• 4.7-day reduction in charge lag. Median time from encounter to clean coded charge fell from 8.2 days to 3.5 days. Zero lost or missed charges across the year, verified against the EHR's scheduled-encounter list with reconciled chart-to-charge audits.
• $4.1M recovered via PRQ. Automated follow-up against aged claims, denial categories, and gap-in-documentation work surfaced revenue the prior workflow had silently written off. The practice administrator estimates roughly 60% of recovered revenue would not have been pursued under the previous workflow.

Secondary outcomes: denial rate fell from 6.3% to 4.1% (35% relative reduction). Net collection improved from 93.2% to 97.8%. Provider self-reported time on billing tasks fell from ~45 minutes per day to under 10.

Why it worked

Three factors made the deployment stick:

1. No migration. The primary EHR stayed where it was. The integration was a Mirth-routed HL7 channel into Medmio, plus a mobile app on each provider's phone. The biller's downstream workflow didn't change — claims still hit the same clearinghouse.
2. Provider adoption was measured in days, not months. Each provider's daily worklist auto-populated from the EHR's schedule, and one-tap charge entry was faster than the paper superbill it replaced.
3. The administrator had visibility for the first time. The Analytics dashboard surfaced denial reasons, charge lag by provider, and net collection by payer — without waiting on the prior vendor's monthly PDF.

What's next

The practice is rolling out Medmio's Patient Intake module to replace its paper intake workflow, expected to eliminate ~30 minutes of front-desk rekeying per visit. They are also piloting CodeSight^TM against a new pediatric vascular service line opening at one of the 12 locations.

Practice identifying information has been generalized to protect competitive details. Specific revenue, savings, and operational metrics are reproduced verbatim from the practice's internal financial and operational reports.