Clinical Data Abstractor at Citizen Health #vacancy #remote

At Citizen Health, we have a singular mission: to improve the lives of the 350 million+ people suffering from rare and complex conditions. Leveraging our AI-powered data platform, we empower patients with seamless access and control over their health data that they can share across our multi-sided ecosystem with caregivers, providers and researchers to illuminate better treatment and support options, while bringing therapies to patients faster. We support thousands of patients, work with a rapidly growing network of patient advocacy organizations, and innovate with leading biopharma organizations to accelerate therapies, always ensuring patients remain at the center.

We are a team of patients, caregivers, researchers and builders who have had first-hand experience across the spectrum of rare disease. Led by a seasoned founding team with a history of successful exits in healthcare and consumer startups, and supported by top-tier investors, we are a close-knit, mission-driven group seeking exceptional talents to join us.

Job Summary:

At Citizen Health, our most important asset is our clinical data. It is used to empower patients and researchers to help find better treatment and identify next steps for their conditions. Our Clinical Data Abstractors work within our abstraction product to review patient medical records and produce a longitudinal dataset for our patients and partners. 

We are seeking meticulous and experienced Clinical Data Abstractors to help us continue to build out and improve our data assets. The ideal candidate will have extensive experience in chart review and data extraction, with a strong ability to review medical records and accurately identify appropriate medical codes. The candidate should possess a deep understanding of clinical terminology and coding standards, ideally in the fields of neurology and oncology. This role is critical in ensuring the accuracy and integrity of our medical data, which is essential for research and reporting.

As an independent contractor, this work is remote and you can set your own hours for when you tackle the work. This is a perfect supplemental role for someone who is looking for flexible work. This role will start at up to 10 hours a week with an option to potentially expand hours in the future.

Key Responsibilities:

  • Conduct detailed chart reviews to extract relevant medical data from patient records, focused on data elements such as medical conditions and medications.
  • Identify and assign appropriate medical codes (e.g., SNOMED CT, RXNORM) to data within medical records.
  • Ensure accurate, consistent, and efficient data abstraction in accordance with established guidelines and protocols.
  • Collaborate with our team of annotation specialists to clarify any discrepancies in medical records.
  • Maintain up-to-date knowledge of coding standards and changes in medical terminology.
  • Participate in quality assurance activities to ensure data accuracy and integrity.

Qualifications:

  • Bachelor’s degree in Health Information Management, Nursing, or a related field.
  • Minimum of 3-5 years of experience in medical data abstraction, with a focus on neurology and/or oncology data.
  • Proficiency in clinical terminology and coding systems.
  • Strong attention to detail and excellent organizational skills.
  • Ability to work efficiently independently with high quality of clinical output.
  • Excellent communication skills, both written and verbal.
  • Familiarity with electronic health records (EHR) systems and data management software.

Preferred Experience:

  • Experience with neurology and oncology patient data abstraction.
  • Familiarity with common neurology and oncology diagnoses, treatments, and medical procedures.
  • Prior experience in a research, academic, or clinical start-up setting is beneficial.

Work Environment:

  • This position is remote and allows for flexible hours – you will get to set the time and days where you do your work, provided we have work volume to support it. 

Artificial intelligence (AI)

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