Supervisor, Clinical Data Abstraction

View full description

Requirements:

• Masters degree in a health-related or medical field.
• Currently U.S. certified Physician Assistants, Nurse Practitioners, or Nurses.
• 3+ years of clinical data abstraction experience across multiple platforms.
• 5+ years experience supervising staff.
• Experience with startup abstraction programs.
• Strong clinical and medical data experience.
• Ability to navigate real-world data and address data gaps.
• Strong communication skills for engaging with diverse professionals.
• Familiarity with clinical data abstraction models and ontologies.
• Experience in statistical reporting on patient data.
• Clinical expertise in cancer, rare diseases, or women’s health.
• Ability to work independently and as part of a team.
• Strong organizational skills and attention to detail.
• Familiarity with data abstraction tools, EDCs, and various clinical data systems.
• Experience with both electronic and paper records.

Responsibilities:

• Function as the front-line supervisor to all data abstractors.
• Oversee all daily abstraction activity and ensure high-quality abstracted data.
• Serve as the first escalation point for medical abstraction questions.
• Lead regular team meetings to address abstraction issues and workflows.
• Create and maintain clinical data abstraction dictionaries and business rules.
• Support standard operating procedures and ensure staff adherence.
• Generate reports for monitoring performance metrics.
• Create project-specific KPIs and report them to the Director.
• Partner with cross-functional teams to operationalize program objectives.
• Assign abstractors to projects and track productivity and quality.
• Support staff training and ensure certifications.
• Conduct performance evaluations and guide career development.
• Supervise staff schedule and track performance against deadlines.
• Support hiring and onboarding of new clinician abstractors.
• Build strong working relationships with stakeholders.
• Perform clinical data abstraction for high-priority projects.
• Forecast productivity and staffing requirements.
• Collaborate on QA and QC governance framework.