Oncology Data Specialist (Allied)

Carenest Health Services•Atlanta, GA
•Remote

About The Position

The Oncology Data Specialist will work remotely, abstracting cancer registry cases. The role involves handling complex cases, including BMT treatments, multiple-facility abstracts, and rare or complex primary sites. The position requires completing user-defined fields and meeting quality-review expectations of at least 90% accuracy, with a mean accuracy of 95%. An assessment may be used to evaluate suitability for the network. Candidates must provide their own PC and dual-monitor setup. The schedule is Monday through Friday, eight-hour shifts totaling 40 hours per week, within an acceptable work window of 4:30 a.m. to 11:00 p.m. EST. Weekend work is not required. The assignment is 13 weeks, with an opportunity to extend. Local and travel candidates are accepted.

Requirements

  • Associate degree or equivalent in a related field.
  • Oncology Data Specialist (ODS) credential and/or Certified Tumor Registrar (CTR) credential from the National Cancer Registrars Association (NCRA).
  • CTR certification.
  • At least two years of experience in the cancer registry field or a similar field; the posting specifies recent certified experience within the specialty.
  • Experience using computer database systems.
  • Experience using Microsoft Outlook, Word, Excel, and PowerPoint.
  • Knowledge of anatomy, physiology, and medical terminology.
  • Ability to handle complex cases, including BMT treatments, multiple-facility abstracts, and rare or complex primary sites.
  • Must provide own PC and dual-monitor setup.

Nice To Haves

  • Experience using Microsoft Access and OneNote.
  • Bachelor of Science degree in Health Sciences, Health Information Management, or a related discipline.

Responsibilities

  • Abstract cancer registry cases, including complex cases involving BMT treatments, multiple-facility abstracts, and rare or complex primary sites.
  • Complete user-defined fields.
  • Meet quality-review expectations, with a minimum expected accuracy of 90% and mean accuracy of 95%.
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