Skip To Content
Identifying Red Flags and Patterns that Increase Cancer Risk – CNE is a Course

Identifying Red Flags and Patterns that Increase Cancer Risk – CNE

Self-paced
0.25 credits

Enroll

Full course description

About This Course

Identifying genetic red flags and patterns in a family medical history can help determine if a condition (or similar conditions) present in a family has a significant genetic contribution. In this course, you will watch a short video that demonstrates identifying cancer risk factors in a family history. Then, you will practice identifying risk factors in several case scenarios and be presented with tools to help make this task easy to implement in your practice.

Already enrolled? Access the course directly here.


CNE Information and Disclosures

Original Release: May 3, 2017
Expiration Date: February 25, 2021

Target Audience
This activity is designed to meet the educational needs of practicing nurses and advanced practice nurses.

Learning outcomes

  • Analyze family history to screen for cancer risk.
  • Identify red flags to help determine risk levels.
  • Communicate genomic information, including family history, in a patient-centered way

CNE Approval Statement
This continuing nursing education activity was approved by the Northeast Multi-State Division (NE-MSD), an accredited approver by the American Nurses Credentialing Center’s Commission on Accreditation. Maine, New Hampshire, New York, Rhode Island, Vermont Nurses Associations are members of the Northeast Multi-State Division of the American Nurses Association.

Claiming Your Credit
In order to claim credit 1) answer the pre-assessment questions, 2) work through the module content in its entirety, 3) successfully complete the post-assessment answering 2 out of 4 questions correctly and 4) complete the evaluation.   

Nurses are eligible for a maximum of .25 contact hours upon the completion of this activity.

Planners, Writers, and Reviewers

  • Emily Edelman, MS, CGC – The Jackson Laboratory
  • Greg Feero, MD, PhD - Maine Dartmouth Family Medicine Residency
  • Therese Ingram, MA – The Jackson Laboratory
  • Susan Levasseur, APRN
  • Kate Reed, MPH, ScM, CGC – The Jackson Laboratory
  • Linda Steinmark, MS, LGC – The Jackson Laboratory
  • Beverly Tenenholz, MS, LGC – Hartford Healthcare

The following individuals contributed to an earlier version of this program: Abdullah Elias, MD, Shodair Children's Hospital; Susan Miesfeldt, MD, Maine Medical Center, Suzanna Schott, ScM, CGC, Robin Schwartz, MS, LGC, UCONN Health, and Mary Lou Woodford, RN, MBA, Cancer1Source.

Conflict of Interest Disclosure
This educational activity does not include any content that relates to the products and/or services of a commercial interest that would create a conflict of interest. Unless otherwise noted, the program planners and faculty do not have a financial interest/arrangement or affiliation with any organizations that could be perceived as a real or apparent conflict of interest in the context of the subject of this course.

The following disclosures are reported that could be perceived as a real or apparent conflict of interest in the education program: Emily Edelman and Kate Reed receive salary support from Pfizer Inc. through an unrestricted quality improvement grant that focuses on improving ascertainment of hereditary breast cancer, provided by the American Community Cancer Centers and Pfizer Independent Grants for Learning & Change. In their roles as a planners and content authors, Ms. Edelman and Ms. Reed recused themselves from all deliberations relating to content related to the commercial entity with which they have financial interest and were not responsible for reviewing for bias any related content. All educational material has been peer-reviewed by external reviewers to assess for bias.

Commercial Support
An earlier version of this program was supported by educational grants from The Maine Cancer Foundation and The Jackson Laboratory Director's Innovation Fund. There is no commercial support being received for this activity.


Hardware/software Requirements

Audio speakers or headphones
Screen resolution of 800X600 or higher
Adobe Reader 5.0 or higher

For best performance in a mobile environment, please download the Canvas Mobile App for IOS and Android.

Check the basic computer specifications and supported browsers.


Should you have technical questions or questions regarding the content of the activity, please email Clinical and Continuing Education at the Jackson Laboratory.




Sign up for this course today!

Enroll