Clinical Data Manager - Part Time

August 27

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RefinedScience

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Advance care by bringing together the best science, data and minds to discover pathways to life beyond disease.

Precision Medicine • Biotechnology • Bioinformatics • Clinical Data Science • Cloud Engineering

11 - 50

Description

• Efficient abstraction of pathology, treatment and other clinical data from medical records that is thorough and accurate • Utilization of critical thinking skills with a high attention to detail while performing abstraction • Identify potential problems affecting the abstraction process for improvement and quality control • Perform quality review on work completed by other data abstractors • Review data quality dashboards and make corrections • Address data quality questions from the multidisciplinary team • Work with the multidisciplinary team to support automated abstraction activities • Work with clinicians for clarification when needed • Assist in the development of data definitions and abstraction procedures • Practice a high level of integrity and honesty in maintaining confidentiality

Requirements

• Bachelor’s degree or higher in a relevant field • 2+ years of data abstraction experience including knowledge of basic medical terminology and the use of electronic medical records • Organized with great attention to detail and a commitment to accuracy • Willing to learn and ask questions • Possess a high level of initiative and self-motivation • Flexible in a changing environment • Manage time well and be able to prioritize • Team player who is collaborative and can work in an independent environment • Handle problems in a solutions-oriented manner • Commitment to ensuring compliance with regulatory guidelines and standards • Must live/work in the USA and be able to work during normal working hours (8:00 am – 6:00 pm MST)

Benefits

• The target hourly range is $35 - $55 per hour • 20 hours per week, any overtime is to be approved by the manager ahead of time. • Base pay offered may vary within the posted range based on several factors, including but not limited to education, job-related knowledge, skills, experience, and location.