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Internship Rn Clinical Data Abstractor Jobs (NOW HIRING)

OR · On-site

Interpret and manage complex clinical patient data for research, quality improvement, and ... U. S. licensed Nurse, PA-C, NP, or DNP is required with a Master's degree in health sciences.

Receive orientation to the entire data abstraction process including understanding data sources ... Active clinical license, such as RN, LPN, MD, DO, NP, in relevant clinical area (e.g. pediatrics or ...

Infection Control Data Abstractor

Brawley, CA · On-site

$79K - $106K/yr

Infection Control Data Abstractor works under the direction of the Infection Control Practitioner ... clinical nursing in a hospital setting preferred. SKILLS & ABILITIES: 1. Ability to analyze ...

Utilizes clinical knowledge to interact with physicians and other medical personnel on a frequent ... This information must be retained and continually updated by the Oncology Data Abstractor. Other ...

RN Abstractor - Cardiovascular

Las Cruces, NM · On-site

$1.8K - $2.4K/wk

RN Abstractor - Cardiovascular Las Cruces, NM 88011 Must-Haves Associate's degree is required ... Utilizes data for evaluation of clinical processes. Coordinates and oversees the ongoing CQI ...

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Internship Rn Clinical Data Abstractor information

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How much do internship rn clinical data abstractor jobs pay per hour?

As of Jun 19, 2026, the average hourly pay for internship rn clinical data abstractor in the United States is $47.93, according to ZipRecruiter salary data. Most workers in this role earn between $35.58 and $57.21 per hour, depending on experience, location, and employer.

What is the difference between Internship Rn Clinical Data Abstractor vs Clinical Data Coordinator?

AspectInternship Rn Clinical Data AbstractorClinical Data Coordinator
CredentialsRN license, internship experienceBachelor's degree, data management skills
Work EnvironmentHospitals, clinics, research settingsHealthcare facilities, research organizations
Job FocusData abstraction, chart review, clinical data collectionData management, database maintenance, reporting
Common UsageEntry-level, internship roles in clinical researchMid-level, data management in healthcare

While both roles involve handling healthcare data, the Internship Rn Clinical Data Abstractor primarily focuses on chart review and data abstraction during an internship, often for research purposes. The Clinical Data Coordinator manages data systems, ensures data quality, and oversees data reporting. The former is more clinical and entry-level, while the latter involves more data management responsibilities in healthcare settings.

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Infographic showing various Internship Rn Clinical Data Abstractor job openings in the United States as of June 2026, with employment types broken down into 100% Part Time. Highlights an 85% Physical, 1% Hybrid, and 14% Remote job distribution, with an average salary of $99,696 per year, or $47.9 per hour.

Senior Quality Clinical Data Abstractor

Natera

OR • On-site

Other

This job post has expired today. Applications are no longer accepted.


Natera rating

7.7

Company rating: 7.7 out of 10

Based on 35 frontline employees who took The Breakroom Quiz

48th of 103 rated laboratories


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 support ensuring abstracted data are accurate and clinical complete. 

  • Mentoring and Subject Matter Expertise (SME): Conduct peer reviews on medical record data interpreted and encoded by abstraction peers to ensure quality and productivity performance align with the programs expectations.

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

  • Process Improvement: Participate in the development and refinement of abstraction and quality guidelines, tools, and standard operating procedures.

  • Daily Operations: Provide timely and accurate daily, weekly, or monthly abstraction submissions, productivity reporting, and actively participate in team meetings and workshops. 

  • Certifications: Maintenance of all relevant clinical or technical licensures.

  • 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 4-5 years of experience in clinical data abstraction and medical records review, preferably in cancer, women's health, rare diseases. 

  • Data Abstraction Expertise: Proven ability to accurately read, interpret, and abstract complex clinical information from various electronic and paper medical record sources.

  • Data Management Expertise: Direct experience performing clinical data encoding using standard ontologies including but not limited to ICD-10-CM and SNOMED CT. Direct experience performing data mapping, standardization, and harmonization. 

  • Quality and Compliance: Demonstrated commitment to data integrity, quality control processes, and adherence to HIPAA and other data privacy regulations. 

  • Technical Proficiency: Proficient with Microsoft Office Suite or Google Suite, creating pivot tables, generating reports, data analysis, and using clinical data systems or databases common in clinical data abstraction, research, or clinical data management (e.g., fillable forms, ECDs, data registries). 

  • Certifications/Industry Expertise: CCDM, CCRP, ACR-P, or CRA preferred.

  • Communication: Excellent written and verbal communication skills, with the ability to effectively collaborate with clinical and non-clinical teams.

  • Autonomy: Proven ability to work independently, manage time effectively, prioritize and organize tasks, and meet strict productivity and quality deadlines.

  • General Expertise:

    • Possess a high level of initiative and self-motivation.

    • Capable of working part of a team on high visibility projects and tasks with high rates of communication. 

    • In-depth attention to detail and a fast learner. 

    • Responding to shifting priorities and changes. 


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