Medical Reviewer

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Hiring Remotely in US
Remote
Internship
Information Technology • Legal Tech • Software
The Role

Who We Are

The Pattern Data platform was created for the rapid analysis of millions of medical records. Fueled by AI, our platform efficiently reviews and categorizes documents in minutes, significantly reducing validation time by highlighting pertinent information crucial for litigation in medical analysis and personal injury cases. Our platform has been successfully implemented in major national settlements to process, adjudicate, and value claims.

At Pattern, our team is built on a foundation of collaborative ownership, visionary problem-solving, customer-centric solutions, and authenticity. We’re looking for a Medical Reviewer to join our growing team.

What You’ll Do

As a Medical Reviewer at Pattern Data, you will review and analyze medical records to enhance the accuracy, quality, and compliance of legal reviews and claims processing. Your responsibilities will include interpreting medical documentation, classifying and labeling data, evaluating platform performance, and generating the data needed for our scientists and engineers to optimize outcomes. You will collaborate with a diverse team of implementation managers, machine learning engineers, and AI analysts. This position is perfect for individuals with a scientific or clinical background who are interested in working at the intersection of healthcare technology and data analysis.

Key Responsibilities:

  • Develop plans for implementing and improving the medical accuracy of litigation setups by identifying the conditions, treatments, and other relevant factors to be included in the litigation process, along with key risk areas
  • Review and evaluate medical records for accuracy, completeness, and litigation claims requirements
  • Perform quality reviews of trained model’s classifications on medical records to identify weaknesses. Create logs and reports detailing the platform's performance in extracting specific medical facts, serving as a basis for discussion and improvement by the AI teams
  • Research relevant medical literature to develop claims protocols that assist users in reviewing cases on Pattern. Utilize experience and research to formulate questions for medical experts and make informed medical decisions regarding qualifying claims requirements and rules, particularly in cases of ambiguity in claims processing or settlement allocation rules
  • Delegate tasks to Pattern’s contracted of clinical data reviewers, ensuring their work is high value add, efficient, and consistent with instructions 


What You’ll Bring

  • Clinical professionals such as registered nurses (RN), licensed practical nurse (LPN), advanced practice registered nurses (APRN/NP), emergency medical technician (EMT), and physician assistants (PA) are preferred, but non-clinical professionals with a Bachelor’s degree in a relevant field and extensive medical knowledge will also be considered
  • Minimum of 5 years of experience in medical record review, medical coding, medical content writing, healthcare compliance, or related roles
  • Strong knowledge of medical terminology, healthcare procedures, and industry-standard coding systems
  • Experience with Electronic Health Record (EHR) systems
  • Strong analytical and critical thinking skills
  • Familiarity with Natural Language Processing (NLP) and AI technologies for processing medical records, along with an interest in research in these areas, is a plus Ability to work independently and manage multiple tasks with tight deadlines
  • Strong communication skills, both written and verbal

Ready to meet us?

Please apply directly through our website or Linkedin. We are excited to hear from you!

The Company
Charlotte, North Carolina
18 Employees
On-site Workplace

What We Do

Pattern Data is an A.I.-powered software platform that accelerates and streamlines the biggest bottleneck of mass tort process: medical record review. Pattern Data uses AI to analyze thousands of pages of medical records, identifies key evidence for validation, and automates the creation of various work products

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