- Clinical NLP
Elevate Healthcare Operations & Patient Care Powered by AI
Empowering clinical data with Connected Intelligence to uncover crucial health correlations swiftly, accurately, dependably, and on a broader scale.
Empowering clinical data with Connected Intelligence to uncover crucial health correlations swiftly, accurately, dependably, and on a broader scale.
Our AI solution leverages a strong foundation in utilizing NLP constructs for Risk Adjustment, culminating in an efficient suite of automated analytics designed to deliver significant ROI
Our CNLP-driven solutions streamline manual tasks like chart validation, verification, and real-time pattern recognition, boosting coding accuracy, revenue cycles, and patient care efficiency.
Clinical NLP prevents missed codes, denials, and recoupments, enhancing accuracy in risk adjustment processes efficiently.
Clinical NLP reduces documentation burdens and administrative time, alleviating physician burnout and enhancing productivity.
Clinical NLP automates chart review and accelerates data extraction, optimizing workflows and reducing care delays effectively.
Clinical NLP enables proactive care interventions and closes quality gaps, enhancing patient outcomes and healthcare quality significantly.
NLP solutions for ICD-10-CM audits automate coding, ensure accuracy, reduce errors and enhance coding efficiency by minimizing manual reviews.
NLP discerns coding discrepancies, enhancing accuracy.
NLP proposes precise alternative codes for validation.
NLP offers instant coder feedback, facilitating prompt error rectification.
NLP aids payors in unifying coding standards for consistency.
Partnering for AI risk adjustment solutions provides a strategic edge for coding and healthcare IT firms, ensuring precision, efficacy, and enhanced patient care amidst the intricate realm of HCC coding.
Our NLP solution is tailored to scrutinize vast data from varied sources like EMRs and claims, detecting patterns hinting at potential missed HCCs. Easily review charts with consolidated records and auto-code suggestions.
HCC Retrospective Coding involves assessing past patient records to accurately assign Hierarchical Condition Categories for appropriate risk adjustment and reimbursement purposes.
Reviews historical patient charts to ensure compliance, accuracy, and quality of documentation and coding practices.
Our cNLP used a combination of Application Programming Interfaces facilitating seamless integration and data exchange between various healthcare software systems for improved interoperability and functionality.
Leave all your technological concerns behind – we will take care of it. Let’s move forward from Risk to Revenue
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