RN Clinical Data Abstractor, Core Measures
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POST DATE 9/17/2016
END DATE 11/22/2016
Salt Lake City, UT
JOB DESCRIPTIONAPPLY Job Code: 06032-32617
When you work with MountainStar Healthcare as an RN Clinical Data Abstractor you will have the opportunity to be a part of a great team while making an impact on the quality of care our patients throughout our healthcare system receive. The RN Clinical Data Abstractor will report to the Division Clinical Abstraction Director and will be responsible for the abstraction of clinical data from a patient s medical record and input into an electronic database for summary analysis and public reporting.
The individual will demonstrate an attention to detail, accuracy in abstracting clinical information and proficiency in the required data abstraction tools. The individual must have the ability to accurately interpret data definitions and communicate both verbally and in writing the core measure variances to Division Clinical Abstraction Director.
This individual will enter clinical data or information into electronic data bases, or registries, or other abstraction software. They will track and validate data accuracy and timeliness in accordance with HCA policies and procedures; and perform quality assurance tasks such as inter rater reliability and validity. They will communicate medical record status and key project issues to management as needed, be familiar with medical terminology and basic medical record design and requirements. The individual will utilize basic computer skills, to include the navigation of several electronic databases including Horizon Patient Folder, Meditech, Excel, Comet, and Epic.
* Current RN License
* Associates Degree required, Bachelor's degree preferred.
* Minimum of 2-5 years experience in a Hospital or acute care setting as a Registered Nurse and/or abstractor.
* Current Core Measures abstraction experience or working with core measures in a Quality department required.
* Quality, Critical Care, Medical/Surgical or Emergency nursing experience preferred.
Last Edited: 11/08/2016