Clinical Quality Data Abstraction Specialist - GWTG (Contractor)
Required skills
- GWTG Stroke Registry
- GWTG Heart Failure Registry
- EMR
- clinical databases
- abstraction
Nice to have
- AI
- LLM
- machine learning
- ever-changing environment
Role summary
Layer Health, a startup founded by MIT and Harvard Medical School researchers in 2023, is developing an AI layer to synthesize medical record information and reduce friction in healthcare. Their LLM-powered platform accelerates clinical registry abstraction for health systems, starting with surgery, cardiology, and oncology. They are seeking remote, part-time (approx. 15 hours/week) contract Clinical Quality Data Abstraction Specialists for GWTG work, specifically in Stroke and Heart Failure. The role involves assisting with case abstraction under a Team Leader's direction and completing assignments in a timely manner. Candidates need at least 1 year of abstraction experience within the GWTG Stroke or Heart Failure Registry and exposure to multiple EMRs and clinical databases.
Layer Health was founded in 2023 by leading machine learning researchers from MIT and Harvard Medical School. We are building an AI layer that can accurately and scalably synthesize information from medical records, with the mission to reduce friction everywhere in healthcare. Our LLM-powered platform is solving chart review once and for all, across use cases. For health systems, our first product dramatically accelerates clinical registry abstraction in areas ranging from surgery and cardiology, to oncology. Our long term vision is for our AI layer to safely transform patient care and minimize unnecessary heartbreak. Layer Health’s diverse founding team brings expertise across machine learning, UI/UX, large language models, and medicine.
Here’s a collection of articles about our product, mission, recent funding round, etc.
Job Description
We’re building a team of clinical abstractors for our GWTG work (specifically focused within Stroke and Heart Failure). This is a remote (US only) part time (~15 hours per week) contractor opportunity.
What you'll do
- Assist with case abstraction under the direction of a Team Leader
- Complete assigned abstractions in a timely manner
- As a start up organization, roles and responsibilities often evolve and adapt over time. As such, this job description may not comprehensively account for future activities, responsibilities, and priorities—these may evolve right along with us!
What you'll need
- 1+ years abstraction within the GWTG Stroke or Heart Failure Registry (this is a 100% requirement)
- Exposure to multiple patient medical record systems (EMRs) and clinical databases.
- Ability to thrive in a fast and ever-changing environment.
Expected compensation range for this role is $28-35/hour and this is a part time contractor role for ~15 hours per week. Compensation is dependent on experience, overall fit to our role, and candidate location. Expected compensation ranges for this role may change over time. If your compensation requirement is greater than our posted salary ranges, please still consider applying to our role. We will make a determination as to whether an exception can be made.
If you are excited about this role, we encourage you to apply even if you don't feel that you meet every single requirement. We're eager to meet people that believe in our mission and can contribute to our team in a variety of ways. We welcome diverse perspectives, rigorous thinking, and fearlessness in challenging the status quo.
Join us and help us transform healthcare with AI. Layer Health is committed to foster an environment of inclusion that is free from discrimination. We are an Equal Opportunity Employer where employment is decided on the basis of qualifications, merit, and business need. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected Veteran status, or any other characteristic protected by law.
Originally posted on Himalayas
