Oncology Data Abstractor & Registry Specialist

Yale New Haven Health; New Haven (CT); On-site; USD 55,000 - 75,000; Full time

Job summary

Yale New Haven Health is seeking a Medical Abstractor to collect, summarize, and abstract demographic and clinical oncology information from diverse data sources into tumor registry systems. You will ensure data quality through review and follow-up, while maintaining confidentiality in line with HIPAA and hospital policy.

The role involves supporting the Connecticut Tumor Registry and Commission on Cancer standards, with responsibilities for timely data submission and participation in tumor

Qualifications

• Two years college or equivalent with coursework in medical terminology/anatomy-physiology.
• Two years experience in medical abstracting or tumor registry or equivalent.
• Knowledge of oncology disease processes, anatomy/physiology, pathology and medical terminology is required.

Responsibilities

• Abstract clinical oncology data from multiple internal and external data sources into tumor registry software or databases.
• Review final records for errors and ensure completeness for quality review.
• Maintain lifetime follow-up data per registry requirements and contribute to special studies as needed.
• Ensure confidentiality and security of patient information per policy and HIPAA rules.
• Attend tumor boards at least monthly and contribute to data quality reviews.

Skills

Data entry

Organizational skills

Analytical thinking

Detail oriented

Education

Two years college

Tools

METRIQ

Microsoft Office

ICD-O

AJCC Staging

Job description

Yale New Haven Health is seeking a Medical Abstractor to collect, summarize, and abstract demographic and clinical oncology information from diverse data sources into tumor registry systems. You will ensure data quality through review and follow-up, while maintaining confidentiality in line with HIPAA and hospital policy.

The role involves supporting the Connecticut Tumor Registry and Commission on Cancer standards, with responsibilities for timely data submission and participation in tumor