CLINICAL NATURAL LANGUAGE PROCESSING

Med Data Quest’s approach is to apply machine learning and deep learning algorithms and comprehensive medical ontology to build high throughput and accurate clinical NLP pipeline. It is used to extract new insights from electronic medical records (EMR). Our Computer Assisted Coding system provides accurate and effective diagnosis coding using advanced clinical natural language processing (NLP), machine learning approaches, and complex statistical models learned from large scale electronic medical records (EMR).

Predictive Modeling

MDQ integrates with client’s existing clinical data sources (EMR, clinical registries, claims, etc.), then uses robust tools to validate and ensure the highest levels of data quality. We built the platform using advanced statistic modeling techniques, such as multivariate logistic regression, hazard regression, and time series analysis, for predicting outcomes and classification different disease. By simplifying and automating the process of adjusting for both risk and reliability, the MDQ system can recalculate outcome measures in real-time as new patient data are available.

Machine Learning

An application of artificial intelligence that provides systems with the ability to automatically learn and improve from experience without being explicitly programmed. This technique focuses on the development of computer programs that can access data and use it to learn for themselves. We develop the software program by training with clinical data for the purpose of clinical applications.

DEEP LEARNING

MDQ applies deep learning algorithms to build sophisticated logical Neural Networks for handling comprehensive medical data. As a brain inspired machine learning tool and technique, deep learning is used to solve medical problems which required ‘thought’ — human or artificial - electronic medical records, optical character recognition(OCR) and medical image analysis.

AI CODING

• Streamline coding services to optimize disease classification
• Risk Adjustment services to provide health assessment, retrospective chart review, and gap identification
• Identifiers to detect under and overpayments
• Patient Data Analytics
• Consulting Services

RISK ADJUSTMENT

• Prioritizing risk analysis, adjustments and outcome
• Perform Risk Assessment for each client to identify assets, threats, vulnerabilities and countermeasures for each service performed
• Assess, Evaluate and Present options for recovery
• Produce a Contingency Plan of Action tailored for your business
• Test, review and revise the plan on a regular basis or as requested

AUDITING SERVICES

• high-quality auditing services
• medical audits that are comprehensive and transparent
• claims audits to meet our client's specific needs
• using database platforms and custom coding to allow us to apply our expertise across large data sets
• healthcare audits to help identify and recover potentially overpayments

AR & BILLING SOLUTIONS

• MDQ offers an array of accounting services for your financial needs
• Ability to customize and automate our services to your company's needs
• Practice Management System such as Affinity, Cerner, CPSI, eClinicalWorks, EPIC, Meditech, NextGen, Vision and more

ENCOUNTER REPORTING

• Encounter reporting - EHR or dictation service
• Reporting Encounter Data to Federal Sources
• MDQ works collaboratively with Plans and understands managed care data collection
• Reporting Encounter Data to Federal Sources
• Programming, Quantitative analysis, Technical assistance, Verbal and written communications
• Data privacy and security for your records by adhering to industry accepted data security practices
• Ability to evaluate clinically appropriate care, create performance metrics measuring health outcomes, and communicate with providers

GAP IDENTIFICATION

• Identify gaps in disease diagnosis and clinical care with a proactive approach to medical billing and coding, and auditing services
• Help close the gaps in Patient Care with accurate patient list and supporting evidences
• Improve compliance by leveraging deep clinical data expertise to help support clinics, hospitals and practices with innovative technologies to minimize errors in billing and coding

POPULATION HEALTH

• Chronic Disease Management
• Patient Engagement
• Clinical Care Identification
• Disease Models Gap Identification
• Coverage Gaps - (If were going to target highly uninsured areas, assist clients with patient management and outcomes)