Job Description

We are seeking a highly skilled Analyst – Clinical Data Abstraction with hands-on expertise in EHR/EMR systems and a strong foundation in medical terminology. The role involves extracting, analyzing, and validating clinical data to support registries, reporting initiatives, and quality improvement programs, while ensuring compliance with regulatory standards.

Key Responsibilities

• Data Extraction & Entry: Navigate multiple EMR/EHR platforms to identify and abstract relevant clinical data points.
• Quality & Accuracy: Achieve and maintain 98%+ accuracy in data collection, ensuring inter-rater reliability and adherence to project-specific guidelines.
• Clinical Analysis: Review and interpret pathology, radiology, and treatment reports to categorize data accurately.
• Compliance & Confidentiality: Maintain patient confidentiality and adhere to HIPAA regulations.
• Reporting & Documentation: Compile, summarize, and present data for clinical registries and quality reporting initiatives.
• Collaboration & Learning: Actively participate in team meetings, training sessions, and collaborative projects to achieve departmental goals.
• Technical Expertise: Maintain advanced knowledge of medical terminology and EMR/EHR systems. Proficiency in MS Excel for data management and reporting.

Quality Assurance

• Consistently meet or exceed quality benchmarks outlined in the QA plan.
• Incorporate feedback from Quality Analysts and reconcile errors promptly.
• Participate in quarterly inter-rater reliability assessments.
• Support QA processes to ensure data integrity and compliance.

Qualifications & Skills

• Education: Master’s degree in Life Sciences or related field.
• Experience: 1–5 years in clinical data abstraction, oncology, or registry work.
• Proficiency in EHR systems, Microsoft Office, and database tools.
• Strong command of medical terminology, anatomy, and disease processes; familiarity with Core Measures is a plus.

Exceptional attention to detail, analytical mindset, and ability to work independently with minimal supervision.