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Rn Clinical Data Abstractor Jobs (NOW HIRING)

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.

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.

Review large volumes of medical documentation, abstract key clinical data and label it ... Holds an active, unencumbered certification (required for MA or CNA applicants) * Familiar with ...

Clinical Data Abstractor I

Chicago, IL · On-site

$50K - $55K/yr

We are looking for Jr. Data Abstractors (JDAs) to join our rapidly growing clinical data team. JDAs will be responsible for reviewing clinical records, structuring key data elements and helping to ...

$21.85 - $32.80/hr

Independently abstracts and interprets pertinent data from medical records with an average level of ... Registered Nurse experience preferred * Cardiac Clinical experience preferred SKILLS/QUALIFICATIONS:

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 ...

HEDIS Abstractor

Monterey Park, CA · On-site

$27 - $33/hr

... and submission of clinical data in accordance with NCQA HEDIS technical specifications and ... Certified Professional Coder (CPC), RHIT, RHIA, LVN/LPN, RN, or other healthcare-related ...

HEDIS Abstractor

Monterey Park, CA · Hybrid

$27 - $33/hr

... and submission of clinical data in accordance with NCQA HEDIS technical specifications and ... Certified Professional Coder (CPC), RHIT, RHIA, LVN/LPN, RN, or other healthcare-related ...

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Rn Clinical Data Abstractor information

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

As of Jun 16, 2026, the average hourly pay for 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 does an RN data abstractor do?

An RN data abstractor reviews and extracts relevant clinical information from patient records to ensure accurate and complete data for research, quality improvement, or regulatory purposes. They typically use electronic health record systems and must have strong attention to detail, clinical knowledge, and familiarity with data standards. Certification or experience in healthcare data management is often required.

What are some typical challenges faced by RN Clinical Data Abstractors in their daily work?

RN Clinical Data Abstractors often encounter challenges such as interpreting complex or incomplete medical records, staying current with changing abstraction guidelines, and ensuring absolute accuracy in data entry. Balancing multiple cases under tight deadlines and working with various healthcare teams to clarify documentation can also be demanding. However, these challenges are manageable with strong attention to detail, ongoing professional development, and effective communication. Many abstraction teams foster supportive environments with access to clinical experts and regular training, which helps abstractors maintain quality and stay confident in their work.

How to become a clinical data abstractor with no experience?

To become a clinical data abstractor, individuals typically need a high school diploma or equivalent, strong attention to detail, and basic computer skills. Gaining familiarity with medical terminology, electronic health records, and data abstraction processes through online courses or training programs can help entry-level candidates qualify for positions, which often provide on-the-job training.

How much do nurse abstractors make?

Nurse abstractors, also known as clinical data abstractors, typically earn between $50,000 and $70,000 annually, depending on experience, location, and employer. They often work in healthcare settings, reviewing medical records and using electronic health record systems to extract relevant data.

How to become a nurse data abstractor?

To become a nurse data abstractor, one typically needs a registered nurse (RN) license and experience in clinical settings. Familiarity with medical records, coding, and data management tools is important, and some roles may require certification in health information management or related fields.

What is an RN Clinical Data Abstractor job?

An RN Clinical Data Abstractor is a registered nurse responsible for reviewing medical records and extracting key clinical data for reporting, compliance, and quality improvement purposes. They ensure accuracy in documentation and may work with databases, electronic health records, and regulatory guidelines. This role supports healthcare organizations in meeting quality metrics, accreditation requirements, and research initiatives. Strong attention to detail, knowledge of medical terminology, and proficiency in data abstraction tools are essential for success in this position.

What are the key skills and qualifications needed to thrive in the Rn Clinical Data Abstractor position, and why are they important?

To thrive as an RN Clinical Data Abstractor, you need a valid RN license, strong clinical knowledge, and keen attention to detail in reviewing medical records. Proficiency with electronic health records (EHRs), clinical data abstraction software, and experience with quality reporting systems like Core Measures or HEDIS are highly valued. Excellent organizational skills, analytical thinking, and clear communication help abstractors collaborate effectively with healthcare teams and ensure data accuracy. These skills are critical for delivering reliable clinical data that supports quality improvement, regulatory compliance, and optimal patient outcomes.

More about Rn Clinical Data Abstractor jobs
What cities are hiring for Rn Clinical Data Abstractor jobs? Cities with the most Rn Clinical Data Abstractor job openings:
What are the most commonly searched types of Rn Clinical Data Abstractor jobs? The most popular types of Rn Clinical Data Abstractor jobs are:
What states have the most Rn Clinical Data Abstractor jobs? States with the most job openings for Rn Clinical Data Abstractor jobs include:
Infographic showing various Rn Clinical Data Abstractor job openings in the United States as of June 2026, with employment types broken down into 4% As Needed, 78% Full Time, 8% Part Time, and 10% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $99,696 per year, or $47.9 per hour.

Other

Posted 26 days ago


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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