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Internship Rn Data Abstraction Jobs (NOW HIRING)

Data Abstraction: Accurately review, interpret, and abstract clinical patient data from various ... U. S. licensed Nurse, PA-C, NP, or DNP is required with a Master's degree in health sciences.

New

Data Abstraction: Accurately review, interpret, and abstract clinical patient data from various ... U. S. licensed Nurse, PA-C, NP, or DNP is required with a Master's degree in health sciences.

New

... nursing, healthcare administration, informatics, or related field Preferred: • Experience in a clinical setting. • Clinical chart review and abstraction experience. • Database data entry and/or ...

... nursing, healthcare administration, informatics, or related field Preferred: • Experience in a clinical setting. • Clinical chart review and abstraction experience. • Database data entry and/or ...

... nursing, healthcare administration, informatics, or related field Preferred: • Experience in a clinical setting. • Clinical chart review and abstraction experience. • Database data entry and/or ...

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 ... Provides oversight of data abstraction (may use third party) Ensures data accuracy. Disseminates ...

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Internship Rn Data Abstraction information

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How much do internship rn data abstraction jobs pay per hour?

As of Sep 14, 2026, the average hourly pay for internship rn data abstraction in the United States is $22.50, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.52 per hour, depending on experience, location, and employer.

What does an internship RN data abstraction do?

An Internship RN Data Abstraction role typically involves working under the supervision of experienced nurses or data managers to collect, review, and enter clinical data from patient records into databases. The primary goal is to ensure accurate and timely data abstraction for purposes like quality improvement, research, or regulatory compliance. Interns in this position gain hands-on experience in medical record review, data management, and healthcare analytics while applying their nursing knowledge. This role helps bridge the gap between clinical practice and healthcare informatics, making it valuable for those interested in both nursing and data science.

What are the key skills and qualifications needed to thrive as an internship RN data abstraction?

To thrive as an Internship RN Data Abstraction, you need foundational nursing knowledge, keen attention to detail, and typically an active RN license or enrollment in a nursing program. Familiarity with electronic health records (EHR) systems, data abstraction tools, and medical coding standards is often required. Strong analytical thinking, time management, and effective communication are crucial soft skills for accurately interpreting and recording clinical information. These competencies ensure precise data collection, which supports patient care quality and compliance with regulatory standards.

What are some common challenges faced by interns in RN data abstraction roles, and how can they be addressed?

Interns in RN data abstraction roles often encounter challenges such as learning complex medical record systems, accurately interpreting clinical documentation, and maintaining data integrity under tight deadlines. Adapting to different electronic health record (EHR) platforms and understanding various healthcare terminologies can be overwhelming at first. These challenges can be addressed by seeking guidance from experienced team members, utilizing training resources provided by the employer, and regularly reviewing clinical guidelines. Building strong communication skills and asking questions when unsure can also help ensure accurate data abstraction and foster professional growth.

What is the difference between Internship Rn Data Abstraction vs Nursing Assistant?

AspectInternship Rn Data AbstractionNursing Assistant
Required CredentialsRN license, internship experienceCertified Nursing Assistant (CNA) certification
Work EnvironmentHospitals, clinics, healthcare facilitiesLong-term care, hospitals, nursing homes
Employer & Industry UsageHealthcare providers, hospitals, clinicsSkilled nursing facilities, hospitals
Common Search & ComparisonData abstraction, clinical data managementPatient care, basic nursing tasks

Internship Rn Data Abstraction involves reviewing and abstracting patient data for healthcare records, requiring an RN license and clinical internship experience. Nursing Assistants provide direct patient care, assisting with daily activities, and hold CNA certification. While both roles work in healthcare settings, Rn Data Abstraction focuses on data management, whereas Nursing Assistants focus on patient support and care.

What cities are hiring for Internship Rn Data Abstraction jobs?

Cities with the most Internship Rn Data Abstraction job openings:

What are the most commonly searched types of Rn Data Abstraction jobs?

The most popular types of Rn Data Abstraction jobs are:

What states have the most Internship Rn Data Abstraction jobs?

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What other helpful pages are available for Internship Rn Data Abstraction?

Other pages related to Internship Rn Data Abstraction:

Sr Clin Data Abstractor Temp to Hire

OR • On-site, Remote

Natera
Biotechnology Research and Development • 1 - 5K employees

Temporary

Posted 2 days ago

New


Natera rating

7.8

Company rating: 7.8 out of 10

Based on 39 frontline employees who took The Breakroom Quiz


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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