Locum - Oncology Nurse - Medical Evaluation project

Staging It; London; Remote; GBP 40,000 - 60,000; Full time

Job summary

An established industry player is seeking a dedicated Oncology Nurse for a unique role in evaluating AI-generated medical summaries. This exciting opportunity involves ensuring the accuracy of clinical documents and collaborating with a multidisciplinary team to enhance the quality of medical evaluations. If you have a strong background in oncology and a passion for improving AI tools in healthcare, this role offers a chance to make a significant impact in the field of medical documentation. Join a forward-thinking organization and contribute to the future of healthcare technology.

Qualifications

• Experienced Oncology Nurse with strong clinical documentation skills.
• Ability to evaluate medical records and identify discrepancies.

Responsibilities

• Evaluate LLM summaries of medical records for accuracy.
• Collaborate with team to refine LLM outputs and ensure quality.

Skills

Oncology Nursing

Clinical Documentation

Attention to Detail

Medical Terminology

Education

Registered Nurse Qualification

Oncology Certification

Tools

Electronic Medical Records

MS Word

Job description

Locum - Oncology Nurse - Medical Evaluation project

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Locum - Oncology Nurse - Medical Evaluation project

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Locum - Oncology Nurse - Medical LLM Evaluation Project - 3 months - Fully remote - 40 hours per week

We are seeking a highly skilled Oncology Nurse to work as part of team, evaluating Large Language Model (LLM)-generated summaries of medical records as part of a specialised project. The successful candidate will be instrumental in ensuring the accuracy and reliability of LLM summaries of clinical documents, such as medical records, laboratory results, pathology reports, and more.

Responsibilities

• Evaluate LLM-produced summaries of medical records, including clinical notes, labs, and pathology reports.
• Work with a team to revise medical records and compare them with LLM-generated summaries.
• Identify and highlight any discrepancies or omissions in the summary, ensuring that critical medical information is accurately captured.
• Support model evaluation by answering standard questions based on the accuracy and comprehensiveness of the LLM summary.
• Collaborate with the team to refine LLM outputs and ensure high-quality documentation for future use.
• Input: Electronic copies of records and LLM-generated summaries (MS Word).
• Output: Provide feedback in the form of a template, answering evaluation questions and flagging issues for further review.
  
  

Qualifications / Experience

• An experienced Oncology Nurse with a strong understanding of clinical documentation, oncology treatments, and medical terminology.
• Experience in evaluating or reviewing medical records is highly preferred.
• Familiarity with Large Language Models (LLMs) and their application in clinical settings would be advantageous but by no means essential.
• Strong attention to detail and the ability to identify and correct inaccuracies in complex medical information.
• Ability to work independently and collaborate with a multidisciplinary team.
• Proficiency in using electronic medical records and MS Word.
  
  

If you're passionate about improving the accuracy of AI tools in healthcare and have an extensive oncology background, we invite you to apply for this exciting opportunity to contribute to the future of medical documentation evaluation.

Robert Half Ltd acts as an employment business for temporary positions and an employment agency for permanent positions. Robert Half is committed to diversity, equity and inclusion. Suitable candidates with equivalent qualifications and more or less experience can apply. Rates of pay and salary ranges are dependent upon your experience, qualifications and training. If you wish to apply, please read our Privacy Notice describing how we may process, disclose and store your personal data: roberthalf.com/gb/en/privacy-notice.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Temporary

Job function

• Job function

  Health Care Provider

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