AI MEDICAL AGENT · TERTIARY HOSPITALS
AI does not replace physicians.
It adds evidence to every decision.
MEV supports claims, coding, and referrals within the clinician's existing EMR/OCS screens. Every recommendation comes with evidence, the physician makes the final decision, and the entire process is recorded.
Within your existing screens,
it works in three steps.
No separate system to adopt. MEV recommends within the EMR/OCS workflow, and the clinician confirms.
EMR/OCS integration
Connects with existing systems inside the hospital's internal network. Data never leaves the hospital.
Analysis · recommendation · evidence
Generates recommendations and drafts for claims, coding, and referrals, with evidence accompanying every result.
Physician confirmation · record
The physician makes the final decision. Who confirmed what and when is preserved in the audit trail.
Your hospital's revenue, records, and care delivery —
all three at once.
The three areas are equal in standing. In each, MEV generates recommendations and drafts, and the clinician confirms.
Insurance Reimbursement & Claims Optimization AI
Checks for denial risk and omissions just before submission to protect rightful revenue.
- Pre-empt claim denial risk before submission
- Surface missed claims
- Improve claim accuracy
Automated Clinical Coding Conversion & Recommendation
Recommends diagnosis and reimbursement codes from medical records, readings, and procedures; the physician confirms.
- Cut time on repetitive coding work
- Reduce variation between coders
- Coding accuracy = claim and statistical accuracy
Patient Referral & Back-Referral AI Agent
Identifies patients who need back-referral, drafts referral and back-referral letters, and manages back-referral-rate metrics.
- Manage back-referral-rate metrics for tertiary-hospital designation review
- Cut time spent writing referral/back-referral letters
We prove it through what we do
and how we do it.
Here is what MEV actually performs. Measured metrics from adopting hospitals will be published separately once the data is confirmed.
One agent reads the encoder's full context
It understands records, readings, procedures, and claims together, recommending as a single flow rather than as fragmented tools.
Prevent claim denials in advance
Detects denial-risk items just before submission and points out correction spots with evidence.
Automatically identify referral candidates
Identifies patients meeting the criteria and drafts referral/back-referral letters to aid metric management.
Automated clinical coding recommendation
Recommends diagnosis and reimbursement codes from records, readings, and procedures, and checks for omissions.
Evidence-based claim accuracy
Links coding and claims with evidence to improve accuracy and appropriateness-evaluation response.
Designed so that tertiary hospitals
can adopt it.
Data never leaves the hospital, decisions are made by the physician, and every process is traceable. MEV is not a separate system; it operates within the existing EMR/OCS workflow.
Data governance
Patient data never leaves the hospital network.
- ·On-premises and air-gapped deployment supported
- ·Processed after pseudonymization; no external transmission of identifying information
- ·Designed to the standards of the Medical Service Act and the Personal Information Protection Act
Regulatory compliance
Designed to the standards of the Medical Service Act and the Personal Information Protection Act, with the clinical validity of results verified.
- ·Compliance with the Medical Service Act and the Personal Information Protection Act from the design stage
- ·Built-in procedures for verifying clinical validity and evidence
Human-in-the-loop
AI goes up to recommendation and draft. The physician confirms.
Explainable AI · XAI
We never output a result without evidence.
- ·Every recommendation is accompanied by record text, codes, and guideline sources
- ·Source chips show instantly which evidence it came from
Built by a team that knows
medicine, AI, and regulation.
MEV is a team that understands clinical practice, insurance review, AI engineering, and medical regulation together.
About the CEO
Tae-Hoon Ko
Professor, AI & Brain Science Division, Catholic Central Medical Center
A medical informatics researcher who has studied medical AI and data standardization at Catholic Central Medical Center. He brings clinical data expertise to life in MEV's claims, coding, and referral products.
- Education
- Ph.D. in Industrial Engineering, Seoul National University · specialization in data mining
- Awards
- Korean Society of Medical Informatics Award in Informatics Medicine (2024) · Minister of Health and Welfare Commendation
- Research
- 30+ SCI papers on medical AI · multimodal clinical AI, data standardization, and more
The questions hospitals
ask before adopting.
Common questions about the AI medical agent, data security, regulatory compliance, and integration with your existing EMR/OCS.
What kind of company is MEV?
MEV is an AI medical agent company for tertiary general hospitals and university hospitals. It supports three areas — insurance reimbursement & claims optimization (RCM), automated clinical coding conversion & recommendation, and patient referral & back-referral — within the clinician's existing EMR/OCS workflow. Every recommendation comes with evidence, and the physician makes the final decision.
How is an AI medical agent different from existing medical AI?
MEV's AI agent is not a single diagnostic aid; it supports the entire administrative workflow that runs from records to coding, claims, and referrals. It generates recommendations and drafts within the EMR/OCS screens without adopting a separate system, and attaches a source, physician verification, and an audit trail to every output.
How do you prevent claim denials? (insurance review · RCM)
Just before submission, we check for denial-risk items and missed claims against the review criteria, and show the evidence for why each item is at risk. We monitor appropriateness-evaluation metrics — including New DRG-based bundled payment, DRG, and non-covered services — to protect rightful revenue.
How does clinical coding automation work?
From medical records, readings, and procedure records, it recommends diagnosis (KCD), reimbursement, and procedure codes, and shows the supporting record text alongside. The AI only goes up to recommendation; the physician makes the final decision, and confirmed codes are linked directly to EDI claims.
What does the patient referral & back-referral feature do?
It automatically identifies patients who need back-referral, drafts referral and back-referral letters, and matches them with partner institutions. It helps manage the back-referral-rate metric for tertiary general hospital designation review.
Does the AI replace the physician's judgment?
No. MEV follows a Human-in-the-loop principle. The AI presents recommendations and drafts together with evidence, and the final confirmation is always made by the physician. Who confirmed what and when is recorded in the audit log.
Is patient data safe? Does it leave the hospital?
Patient data never leaves the hospital network. We support on-premises and air-gapped (network-isolated) deployment, process data after pseudonymization, and do not transmit identifying information externally.
How do you comply with regulations such as the Medical Service Act and the Personal Information Protection Act?
We build to the standards of the Medical Service Act and the Personal Information Protection Act from the design stage, with built-in procedures to verify the clinical validity and evidence of results. We also review applicability as an MFDS medical device (SaMD).
How does it integrate with existing EMR/OCS?
MEV is not a separate program; it operates within the clinician's existing EMR/OCS screens. It surfaces recommendations without a separate login or double entry, and without interrupting the care flow.
How can I verify the impact and see a demo?
In a 30-minute demo, we show you your area of interest across claims, coding, and referrals firsthand. Measured metrics from adopting hospitals will be published separately once the data is confirmed; we do not present estimates as if they were facts.
See whether it fits
your hospital's workflow first.
In a 30-minute demo, we show you your area of interest across claims, coding, and referrals firsthand.
Request a Demo