Open Rank Clinical Data Coordinator (Entry – Senior)

University of Colorado•Aurora, CO

54d•$49,899 - $78,665•Onsite

About The Position

Clinical Data Coordinators play a vital role in collecting clinical data with a focus on accuracy and completeness. They are responsible for creating and managing patient databases essential for academic clinical research and basic science studies involving patient samples and information. This position also involves understanding data transfer mechanisms and their application, with the potential to contribute to strategies for improving these processes using computational and artificial intelligence approaches. This specific Clinical Data Coordinator role is part of a pilot program aimed at better utilizing clinical data across the campus. Initially funded for one year as a proof-of-concept, there is a possibility for extension based on success. The position is a collaboration with Refined Science, a biotech company located on the University of Colorado campus, offering an opportunity to develop translational tools for both academic and industry data projects. The coordinator will work closely with the clinical trials unit and the Refined Science clinical data team to enhance skills in clinical data collection and analysis. Successful performance over the first year could lead to opportunities to lead and expand data initiatives within the school of medicine and improve collaborative data efforts with Refined Science.

Requirements

Bachelor’s degree in any field.
Applicants must meet minimum qualifications at the time of hire.
Legally authorized to work in the United States without requiring sponsorship.
Knowledge and understanding of federal regulations and Good Clinical Practice (GCP).
Ability to communicate effectively, both in writing and orally.
Ability to establish and maintain effective working relationships with employees at all levels throughout the institution.
Outstanding customer service skills.
Knowledge of basic human anatomy, physiology, and medical terminology.
Ability to interpret and master complex research protocol information.
Familiarity with artificial intelligence and application in healthcare data.
Familiarity with malignant hematologic diseases, classifications, and outcome metrics.
Organized with great attention to detail and a commitment to accuracy.
A willingness to learn and ask questions.
Possess a high level of initiative and self-motivation.
Ability to maintain flexibility in a changing environment.
Ability to manage time well and prioritize.
Ability to handle problems in a solutions-oriented manner.

Nice To Haves

Bachelor’s degree in science or health related field.
Three (3) years of clinical research or related experience.
Experience with electronic data capture systems (e.g. EMR or EHR and data management systems).
Prior experience in a healthcare or research setting with oncology or blood cancers.
Prior experience with biostatistics.
Prior independent programming experience with R, particularly analysis with common healthcare outcome metrics such as kaplan-meier curves, hazard ratios, demographic statistic tables, and others.
Experience using REDCap databasing software and API functionality.
Prior experience with AI functionality as applied to healthcare databasing questions and challenges.
Two (2) or more years of data abstraction experience including knowledge of basic medical terminology and the use of electronic medical records.
Some programming knowledge or experience.

Responsibilities

Efficiently and accurately abstract pathology, treatment, and other clinical data from medical records.
Apply critical thinking skills with a high level of attention to detail during data abstraction.
Identify and address potential problems in the abstraction process to improve quality control.
Perform quality reviews on work completed by other data abstractors.
Review and correct data quality dashboards.
Respond to data quality inquiries from the multidisciplinary team.
Collaborate with the multidisciplinary team to support automated abstraction activities.
Develop new data abstraction procedures incorporating computational approaches and artificial intelligence.
Liaise with clinicians for necessary clarifications.
Assist in the development of data definitions and abstraction procedures.
Maintain a high level of integrity and honesty in handling confidential information.
Adhere to research regulatory standards.