Solutions for Clinical Research and Healthcare
Advanced AI Systems Applications:
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Utilization Review and Continuous Documentation Improvement
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Inpatient Determinations
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Clinical Research Participant Identification
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Continual Analysis of Large Datasets for Quality Improvement
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Streamline Prior Authorizations
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ARAIOS
Revolutionizing Clinical Trial Recruitment with Data-Driven Precision and Advanced Participant Identification
Searching all US Clinical Trials
ARAIOSTM uses sophisticated data extraction, social media tracking, and open-source intelligence (OSINT) to help clinical researchers efficiently and ethically identify qualified participants. By extracting clinical trial data from resources like ClinicalTrials.gov, we capture key enrollment criteria, including age, sex, medical conditions, and location.
Continual Monitoring of Prospects
information is then transformed into targeted search queries, enabling precise identification of potential participants across digital platforms.
Our system tracks discussions on social media and forums, analyzes user behavior, and refines potential candidate profiles based on health-related posts and sentiment.
Participant Identification
Comprehensive reports provide insights such as usernames, actual legal names, DOB, email addresses, physical addresses, cell phone numbers, sentiment analysis, and conversation highlights that demonstrate interest in clinical trials.
U-PAS (Utilization Review - Physician Advisor Services)
We offer a secure, customized system that leverages the most advanced AI technology available today to identify and maximize reimbursements from payors.
AI Systems and Experts
Identify the policy and contract information from the payor and ensure it aligns with the patient's needs based on a comprehensive assessment of the patient. By using precise information and exact references, you will optimize your monthly revenue
Private Repository
Create a private database of past approvals and denials to effectively support a case for approval. Analyzing historical approvals of cases that closely resemble the current one can significantly aid in the approval and appeal process.
Documentation Gaps
Identify gaps between approvals and denials related to documentation within the medical record. Understand exactly why particular cases were not approved based on lack of a test, detailed conditions or contract/policy imitations.
Peer to Peer Support
Have your staff create the best notes to providers for P2P with payor physicians in less than a minute.
M-REV
How much money do you waste chasing prior authorizations? M-REV might be a great solution.
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It was recently found that about 14 hours per week of staff time is spent on prior authorizations per practitioner. On average, practices must complete 41 prior authorizations per physician each week.
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How many cases have failed prior authorization and require appeals or peer-to-peer meetings per month in your practice?
Unprecedented Velocity. Impeccable Reliability.
After many successes with several AI platforms in US healthcare, including chronic care management, patient outreach, patient-reported outcomes, utilization review, and pre-surgery patient automation, MED-ROC was founded.
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The system is a private, standalone, enterprise AI system that does not share information with any other AI models or LLMs. The system has the latest security, including AES 256-bit encryption and SOC 2.
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​Each system is designed specifically for your research site, CRO, biotech company, or practice, tailored to include specific commercial payor plans and policies.
We build a dedicated agent for each workflow. This approach allows us to fine-tune each agent, enabling them to learn the processes of that payor intimately. As a result, the agent has the best knowledge base to achieve the highest sensitivity and specificity of data.
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