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Data Abstraction Jobs (NOW HIRING)

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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 ...

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 ...

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 ...

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 ...

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 ...

$32/hr

Position: Flexible Schedule Clinical Data Abstractor Location: 100% Remote (Non-Benefit Position) Are you experienced in clinical data abstraction? Carta Healthcare Inc. is seeking talented ...

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How much do data abstraction jobs pay per hour?

As of Jun 19, 2026, the average hourly pay for data abstraction in the United States is $25.33, according to ZipRecruiter salary data. Most workers in this role earn between $18.51 and $31.97 per hour, depending on experience, location, and employer.

How much do clinical data abstractors make?

Clinical data abstractors typically earn between $40,000 and $70,000 annually, depending on experience, location, and certification level. They often work in healthcare settings, using electronic health records and data management tools to extract and organize clinical information.

What skills do you need to be a clinical data abstractor?

A clinical data abstractor needs strong attention to detail, excellent organizational skills, and familiarity with medical terminology and electronic health record (EHR) systems. Good communication skills and the ability to review and interpret medical records accurately are also essential. Some roles may require knowledge of coding standards like ICD or CPT and relevant certifications such as Certified Health Data Analyst (CHDA).

What is the difference between Data Abstraction vs Data Analyst?

AspectData AbstractionData Analyst
Required CredentialsTypically a degree in computer science, information systems, or related fieldsUsually a degree in statistics, mathematics, or related fields
Work EnvironmentSoftware development teams, IT departments, data management projectsBusiness intelligence teams, marketing, finance, and operations departments
Employer & Industry UsageTech companies, software firms, data management organizationsCorporations across various industries, consulting firms, market research

Data Abstraction focuses on simplifying complex data structures in software development, while Data Analysts interpret data to support business decisions. Both roles require analytical skills but serve different purposes within data management and analysis.

What are some common challenges faced by data abstraction professionals, and how can they be addressed?

Data abstraction professionals often encounter challenges such as ensuring the accuracy and consistency of extracted data, navigating incomplete or ambiguous source documents, and staying updated with changing data standards. To address these issues, it's important to develop strong attention to detail, establish clear data abstraction protocols, and participate in regular training sessions. Collaborating closely with quality assurance teams and leveraging technology, such as data abstraction software, can also help maintain high standards and efficiency in the role.

What is a data abstraction job?

A data abstraction job involves reviewing and summarizing information from medical records, documents, or databases to extract relevant data for analysis or reporting. It requires attention to detail, knowledge of data entry tools, and often adherence to privacy standards such as HIPAA.

How do I become a data abstractor?

To become a data abstractor, you typically need a high school diploma or equivalent, strong attention to detail, and proficiency in data management tools like Excel or database software. Relevant experience in healthcare, insurance, or research fields can be beneficial, and some employers may require certification in medical coding or data management.

What is data abstraction?

Data abstraction is the process of simplifying complex data by extracting relevant information and presenting it in a more manageable form. In many industries, especially healthcare, data abstractors review records and summarize key details into databases for analysis and reporting. This helps organizations make informed decisions by focusing on essential data points without unnecessary details. Data abstraction improves efficiency, accuracy, and data organization.

What are the key skills and qualifications needed to thrive as a Data Abstractor, and why are they important?

To thrive as a Data Abstractor, you need strong analytical skills, attention to detail, and a background in health information management or a related field, often supported by a relevant certification such as RHIT or RHIA. Familiarity with electronic health records (EHR) systems, data abstraction software, and coding standards like ICD-10 and CPT is typically required. Excellent organizational abilities, problem-solving skills, and clear communication help individuals excel in reviewing and extracting precise data from complex documents. These skills are crucial for ensuring data accuracy, supporting healthcare quality initiatives, and enabling effective decision-making.
More about Data Abstraction jobs
What cities are hiring for Data Abstraction jobs? Cities with the most Data Abstraction job openings:
What are the most commonly searched types of Data Abstraction jobs? The most popular types of Data Abstraction jobs are:
What states have the most Data Abstraction jobs? States with the most job openings for Data Abstraction jobs include:

Sr Clinical Data Abstractor

Natera

OR • On-site

Other

Posted 28 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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