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Quality Metrics Reporting After EHR Abstraction
Automated Data Abstraction for Seamless Quality Reporting
Healthcare providers face increasing demands for accurate and timely quality metrics reporting, often requiring manual data abstraction from EHRs. Traditionally, Nurse Abstractors spend countless hours reviewing structured and unstructured data, identifying key clinical elements, and inputting them into various registries and reporting platforms. Core Mobile’s AI-driven Quality Metrics Reporting After EHR Abstraction solution revolutionizes this process by automating data extraction, interpretation, and submission—saving time, reducing errors, and ensuring compliance with registry and reporting requirements.
Key Features & Benefits:
Automated Data Extraction: Captures structured and unstructured data from EHRs, clinical notes, and scanned documents.
Registry-Specific Mapping: Converts raw data into standardized formats required by CMS, HEDIS, AHRQ, NCDR, STS, and other quality reporting registries.
AI-Driven Accuracy: Reduces human error and improves data completeness and consistency.
Real-Time Compliance Monitoring: Ensures adherence to evolving reporting standards and regulatory requirements.
Seamless EHR Integration: Works with existing hospital and health system infrastructures for a smooth workflow.
Time & Cost Savings: Frees up clinical staff from manual abstraction, allowing them to focus on patient care.
AI-Powered Abstraction: Replace Manual Work with Intelligent Automation
Core Mobile’s advanced AI technology seamlessly integrates with EHRs to extract both structured (e.g., lab results, vitals, medications) and unstructured (e.g., physician notes, discharge summaries) data. By leveraging Natural Language Processing (NLP) and Machine Learning, our system identifies relevant clinical data, maps it to specific registry requirements, and automates abstraction—eliminating the need for manual review by Nurse Abstractors.