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Medical Data Abstraction information

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$14

$25

$39

How much do medical data abstraction jobs pay per hour?

As of Aug 18, 2026, the average hourly pay for medical 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.

What is medical data abstraction?

Medical data abstraction is the process of reviewing, extracting, and summarizing specific information from medical records to be used for research, reporting, billing, or quality improvement. Abstractors carefully analyze charts and electronic health records to pull key data elements, such as patient demographics, diagnoses, treatments, and outcomes. This work is essential for ensuring accurate data collection, compliance with regulatory requirements, and supporting clinical decision-making. Medical data abstraction requires attention to detail, knowledge of medical terminology, and familiarity with healthcare documentation systems.

What are the key skills and qualifications needed to thrive as a medical data abstractor, and why are they important?

To thrive as a Medical Data Abstractor, you need a solid understanding of medical terminology, coding systems (such as ICD-10 and CPT), and health information management, often supported by a relevant associate degree or certification. Familiarity with electronic health record (EHR) systems, clinical data software, and HIPAA compliance is typically required. Attention to detail, analytical thinking, and strong organizational skills are crucial soft skills for accurately extracting and managing patient data. These competencies ensure data integrity, support regulatory compliance, and enable high-quality healthcare reporting and analysis.

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

Medical Data Abstraction professionals often encounter challenges such as inconsistent documentation, varying formats of electronic health records (EHRs), and tight turnaround times for data extraction projects. Addressing these challenges requires strong attention to detail, familiarity with multiple EHR systems, and effective communication with clinical staff to clarify ambiguous information. Additionally, ongoing training in medical terminology and data privacy regulations helps ensure accuracy and compliance while adapting to evolving healthcare standards.

What is the difference between Medical Data Abstraction vs Medical Coding?

AspectMedical Data AbstractionMedical Coding
Primary FocusExtracting and reviewing patient data for accuracy and completenessAssigning standardized codes to diagnoses and procedures
Required CertificationsNone mandatory, but certifications like AHIMA's Certified Health Data Analyst (CHDA) are beneficialCertified Professional Coder (CPC) or equivalent
Work EnvironmentHospitals, clinics, health information departmentsHospitals, billing companies, insurance companies
Industry UsageHealth information management, quality assuranceMedical billing, reimbursement, claims processing

Medical Data Abstraction involves reviewing and extracting relevant patient information to ensure data accuracy, while Medical Coding focuses on translating clinical information into standardized codes for billing and documentation. Both roles are essential in health information management but serve different functions within healthcare operations.

How to become a medical data abstractor?

To become a medical data abstractor, candidates typically need a high school diploma or equivalent, with some roles preferring an associate's degree or healthcare-related certification. Relevant skills include attention to detail, knowledge of medical terminology, and proficiency with electronic health records (EHR) systems. On-the-job training is common, and familiarity with coding standards like ICD or CPT can be advantageous.

What does a medical data abstraction do in healthcare?

A medical data abstraction involves reviewing and extracting relevant patient information from medical records to ensure accurate and complete documentation. Medical data abstractors often use electronic health record (EHR) systems and must understand medical terminology and coding standards like ICD or CPT. Their work supports clinical decision-making, billing, and quality reporting in healthcare settings.

What skills do you need to be a medical data abstractionist?

Medical data abstractionists need strong attention to detail, excellent organizational skills, and proficiency in electronic health record (EHR) systems. They should have a good understanding of medical terminology, coding standards like ICD and CPT, and often require familiarity with data privacy regulations such as HIPAA. Effective communication and the ability to work independently are also important for accurate data collection and management.
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Medical Data Abstraction jobs near you
Infographic showing various Medical Data Abstraction job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 15% Part Time, and 7% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $52,687 per year, or $25.3 per hour.

Clinical Quality Data Abstraction Specialist - GWTG (Contractor)

Layer Health

Remote

$28 - $35/hr

Full-time, Part-time

Re-posted 16 days ago

Job description

Layer Health was founded in 2023 by leading machine learning researchers from MIT and Harvard Medical School. We are building an AI layer that can accurately and scalably synthesize information from medical records, with the mission to reduce friction everywhere in healthcare. Our LLM-powered platform is solving chart review once and for all, across use cases. For health systems, our first product dramatically accelerates clinical registry abstraction in areas ranging from surgery and cardiology, to oncology. Our long term vision is for our AI layer to safely transform patient care and minimize unnecessary heartbreak. Layer Health's diverse founding team brings expertise across machine learning, UI/UX, large language models, and medicine.
Here's a collection of articles about our product, mission, recent funding round, etc.
Job Description
We're building a team of clinical abstractors for our GWTG work (specifically focused within Stroke and Heart Failure). This is a remote (US only) part time (~15 hours per week) contractor opportunity.
What you'll do
  • Assist with case abstraction under the direction of a Team Leader
  • Complete assigned abstractions in a timely manner
  • As a start up organization, roles and responsibilities often evolve and adapt over time. As such, this job description may not comprehensively account for future activities, responsibilities, and priorities-these may evolve right along with us!

What you'll need
  • 1+ years abstraction within the GWTG Stroke or Heart Failure Registry (this is a 100% requirement)
  • Exposure to multiple patient medical record systems (EMRs) and clinical databases.
  • Ability to thrive in a fast and ever-changing environment.

Expected compensation range for this role is $28-35/hour and this is a part time contractor role for ~15 hours per week. Compensation is dependent on experience, overall fit to our role, and candidate location. Expected compensation ranges for this role may change over time. If your compensation requirement is greater than our posted salary ranges, please still consider applying to our role. We will make a determination as to whether an exception can be made.
If you are excited about this role, we encourage you to apply even if you don't feel that you meet every single requirement. We're eager to meet people that believe in our mission and can contribute to our team in a variety of ways. We welcome diverse perspectives, rigorous thinking, and fearlessness in challenging the status quo.
Join us and help us transform healthcare with AI. Layer Health is committed to foster an environment of inclusion that is free from discrimination. We are an Equal Opportunity Employer where employment is decided on the basis of qualifications, merit, and business need. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected Veteran status, or any other characteristic protected by law.

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