Lead Clinical Data Abstractor

POSITION SUMMARY: 

Assist direct Manager in overseeing and leading clinical data abstractors and related operations. Partner with the Lead Quality Abstractor, and the team’s software engineers and data management specialists to operationalize end-to-end abstraction, clinical data management workflows and activities, and lending technical support. Serve as the first line of communication and point of escalation amongst the data abstractors. 

PRIMARY RESPONSIBILITIES:

• Front-line Staff Support: Serve as the primary liaison and initial point of escalation for all abstraction/team-related issues, questions, and concerns.

• New Hire Onboarding and Training: Lead training new abstractors and provide ongoing guidance until released into production level activities by supporting the development and implementation of training workflows.  

• Mentoring and Subject Matter Expertise (SME): Provide ongoing clinical guidance and mentorship to existing abstraction team members- fostering professional development. Support maintaining high standards of quality and productivity by evangelizing the utilization of standard of care guidelines. 

• Technical Support: 

  • Lead ongoing clinical and medical guidance to engineering, data management specialists, and technical staff to ensure the development of bug-free data for systems such as Electronic Data Capture Systems (ECDs), applications, and workflows. 

  • Apply Medical Coding and Classification skills to support the creation of data standardization and harmonization rules to ensure clinical data are encoded into machine readable data in one common database schema.

  • Apply Data Management knowledge (e.g., CGDM, GCP) and skills to support establishing logical relationships between clinical events within database schemas and logical rules for ensuring data are accurate, legible, contemporaneous, original, attributable, complete, and consistent for end-to-end ETL workflows. 

  • Apply Technical Skills to translate abstraction and encoding requirements to technical product requirements to support prompt engineering and design activities for all AI and LLM initiatives.  

• Data Abstraction: Advanced level review, interpretation, abstraction and data encoding. Less than 5% of patients require quality review. 

• Quality Assurance and Control: Apply and lead efforts in resolving complex or ambiguous data abstraction questions, ensuring consistent and adherence to established protocols and standards 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. 

• Protocol Adherence: Support developing and ensuring strict adherence to all project and research protocols, institutional review board requirements, HIPAA regulations, data management best practices (e.g., DAMA, SCDM, ACRP, and SOCRA), and organizational policies regarding patient privacy and data security. 

• Reporting: Track, analyze, and report on key abstraction and staff level metrics to support the assessment of team performance and identify areas for process improvement by gathering and structuring KPIs using software such as Excel, googlesheets Pivot tables, formulas, and functions.                                                                                

• Process Improvement: Collaborate with cross-functional teams to effectively operationalize new abstraction activities, including the rollout of new protocols, standard operating procedures, and policies and technology platforms. 

• Daily Operations: Support direct manager in daily coordination of the clinical data abstraction team's activities and workload distribution.

• Conferences and Certifications: Maintenance of all relevant clinical or technical licensures. Attend conferences relevant to role and clinical field. 

• Other duties and responsibilities to be performed as assigned. 

QUALIFICATIONS: 

• Clinical Background: U. S. licensed Nurse, PA-C, NP, or DNP is required with a Master’s degree in health sciences. Strong understanding of medical terminology, disease processes (especially cancer), standard clinical workflows, and genetic testing.

• Clinical Experience: Minimum of 5-6 years of experience in clinical data abstraction and medical records review, preferably in cancer, women’s health, rare diseases. 

• Lead Experience: Minimum of 2-3 years of direct experience supervising staff or providing team lead support to senior level management. 

• Quality and Compliance: Demonstrated commitment to data