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Garry Daniels
Data Abstractor
Summary
Highly accomplished Data Abstractor with 5+ years of proven experience in healthcare data abstraction and management. Proficient in utilizing ICD and CDA standards, NLP, and ML techniques to extract and analyze patient data accurately and efficiently. Demonstrated expertise in ensuring data integrity, completeness, and compliance with HIPAA regulations. Strong understanding of medical terminology and ability to collaborate effectively with clinicians and healthcare professionals.
Education
Bachelor’s degree in a related field
February 2019
Skills
- Data Entry
- Data Extraction
- Data Validation
- Data Cleansing
- Data Transformation
- Data Analysis
Work Experience
Data Abstractor
- Extracted and coded patient data from a variety of sources, including electronic health records (EHRs), paper charts, and medical imaging studies.
- Collaborated with clinicians and other healthcare professionals to gather additional information or resolve data discrepancies.
- Processed and deidentified patient data to ensure compliance with HIPAA and other privacy regulations.
- Utilized natural language processing (NLP) and machine learning (ML) tools to enhance the efficiency and accuracy of data abstraction.
Data Abstractor
- Abstracted and organized medical records, including patient history, physical examinations, and test results, to create comprehensive patient profiles.
- Utilized industrystandard tools and techniques for data abstraction, such as the International Classification of Diseases (ICD) and Clinical Document Architecture (CDA).
- Developed and implemented data abstraction protocols to ensure consistency and accuracy in the extraction process.
- Reviewed and analyzed data for completeness and accuracy, identifying potential errors or missing information.
Accomplishments
- Extracted and validated over 1 million data records with 99.9% accuracy, ensuring data integrity and reliability for downstream applications.
- Developed efficient data extraction pipelines using Python scripts, automating processes and improving productivity by 20%.
- Collaborated with data scientists to define data abstraction criteria, ensuring alignment with business requirements and facilitating accurate data analysis.
- Consistently met SLAs for data abstraction, delivering highquality data within tight deadlines.
- Identified and resolved data inconsistencies through thorough analysis and manual verification, maintaining the integrity of extracted data.
Certificates
- Certified Data Management Professional (CDMP)
- Certified Data Analytics Professional (CDAP)
- Certified Data Abstraction Specialist (CDAS)
- Microsoft Certified Solutions Expert: Data Management and Analytics (MCSE: DMA)
Languages
- English
- French
- German
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How To Write Resume For Data Abstractor
- Highlight your healthcare domain knowledge and experience in medical terminology.
- Quantify your accomplishments and provide specific examples of how your work impacted healthcare outcomes.
- Demonstrate your proficiency in data abstraction tools and technologies, such as NLP and ML.
- Emphasize your ability to work independently and as part of a team in a fast-paced healthcare environment.
- Showcase your commitment to data accuracy, privacy, and compliance with HIPAA regulations.
Essential Experience Highlights for a Strong Data Abstractor Resume
- Abstracted and organized medical records, including patient history, physical examinations, and test results, to create comprehensive patient profiles.
- Utilized industry-standard tools and techniques for data abstraction, such as the International Classification of Diseases (ICD) and Clinical Document Architecture (CDA).
- Developed and implemented data abstraction protocols to ensure consistency and accuracy in the extraction process.
- Reviewed and analyzed data for completeness and accuracy, identifying potential errors or missing information.
- Extracted and coded patient data from various sources, including electronic health records (EHRs), paper charts, and medical imaging studies.
- Collaborated with clinicians and other healthcare professionals to gather additional information or resolve data discrepancies.
- Processed and deidentified patient data to ensure compliance with HIPAA and other privacy regulations.
Frequently Asked Questions (FAQ’s) For Data Abstractor
What is the primary role of a Data Abstractor?
A Data Abstractor is responsible for extracting and organizing patient data from various medical records to create comprehensive patient profiles. They ensure the accuracy and completeness of data, adhering to industry standards and compliance regulations.
What skills are essential for a successful Data Abstractor?
Essential skills include proficiency in data entry, data extraction, data validation, data cleansing, data transformation, and data analysis. Knowledge of medical terminology, ICD and CDA standards, and experience with NLP and ML tools are also valuable.
What are the key qualities of an effective Data Abstractor?
Attention to detail, accuracy, strong analytical skills, and the ability to work independently and as part of a team are crucial qualities. Effective Data Abstractors possess a deep understanding of medical terminology and a commitment to data integrity and compliance.
What career advancement opportunities are available for Data Abstractors?
With experience and additional qualifications, Data Abstractors can advance to roles such as Data Analyst, Data Manager, or Clinical Research Coordinator. They may also pursue specialized certifications in healthcare data management or clinical research.
How can I prepare for a career as a Data Abstractor?
Consider pursuing a bachelor’s degree in a related field, such as health information management or medical coding. Volunteering or interning in healthcare settings can provide valuable hands-on experience. Additionally, obtaining certifications in data abstraction or medical terminology can enhance your qualifications.
What are the ethical considerations for Data Abstractors?
Data Abstractors must maintain patient confidentiality and adhere to HIPAA regulations. They must ensure the accuracy and integrity of data, avoiding any biases or errors that could compromise patient care or research outcomes.
How is technology impacting the role of Data Abstractors?
Advancements in NLP and ML are transforming data abstraction processes, automating tasks and enhancing efficiency. Data Abstractors must stay updated with these technologies to adapt to the evolving healthcare landscape.