Natera
Healthcare
SeniorQualityClinicalDataAbstractor
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Quality Clinical Data Abstractor at Natera. Skills: Clinical data abstraction, Medical coding, Data management, Quality assurance. Review clinical patient data. Interpret clinical patient data”
What You'll Achieve.
Ensure quality and productivity performance
Industry & Context.
Data analysis
What They're Looking For.
Must Have
U.S. licensed Nurse, PA-C, NP, or DNP required, Master’s degree in health sciences required, Minimum of 4-5 years of experience in clinical data abstraction, Proficient with Microsoft Office Suite or Google Suite
Nice to Have
CCDM, CCRP, ACR-P, or CRA preferred, PhD preferred
What You'll Do.
Review clinical patient data
Interpret clinical patient data
Abstract clinical patient data
Apply medical coding systems
Classify abstracted clinical data
Categorize abstracted clinical data
Maintain integrity of clinical data
Translate abstraction requirements
Support prompt engineering
Support AI initiatives
Support LLM initiatives
Establish data management best practices
Ensure abstracted data are accurate
Ensure abstracted data are clinical complete
Maintain adherence to protocols
Maintain adherence to IRB requirements
Maintain adherence to HIPAA regulations
Maintain adherence to data management best practices
Maintain adherence to organizational policies
Participate in development of guidelines
Participate in refinement of guidelines
Participate in development of tools
Participate in refinement of tools
Participate in development of SOPs
Participate in refinement of SOPs
Provide abstraction submissions
Provide productivity reporting
Participate in team meetings
Participate in workshops
How You'll Work.
Team & Collaboration
Cross-functional teams; High visibility projects
Communication Scope
Verbal communication; Written communication
Full Job Description
POSITION SUMMARY: Perform high-quality medical record abstraction by combining proficient-level experiences in data management and software with medical terminology, medical coding, information encoding, and analytical capabilities. Interpret and manage complex clinical patient data for research, quality improvement, and regulatory reporting. PRIMARY RESPONSIBILITIES: Data Abstraction: Accurately review, interpret, and abstract clinical patient data from various electronic health record (EHR) systems, paper charts, and other source documents in accordance with defined project or research protocols, clinical, data, and technical specifications, and dictionaries. Coding and Classification: Apply knowledge of medical coding systems (e.g., ICD-10, MedDRA, CPT, HCPCS) and standard of care guidelines, to interpret, classify and categorize abstracted clinical data points from unstructured text to standardized machine readable data in one common database schema. Electronic Data Capture (EDC): Utilize specialized data management software (e.g., REDCap, registries, and custom built EDC systems) to enter, track, and maintain the integrity of clinical data encoded into queryable databases. Technical Support: Aid cross-functional teams in translating clinical and data abstraction and encoding requirements. Support prompt engineering and design for all AI and LLM initiatives. Data Management: Apply and support establishing program specific clinical data management best practices (CGDMP) and good clinical practice (GCP) during the abstraction and encoding process resulting in accurate, legible, contemporaneous, original, attributable, complete and consistent for end-to-end ETL workflows. Quality Assurance and Control: Apply industry standard best practices for utilizing real-world data for research, quality monitoring, and regulatory reporting using technical and analytical software such as running MACROs and using Excel/Google Sheets functions and formulas, and pivot tables to su
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