Clinical Data Abstracter - Thoracic Imaging
Company: University of Texas M.D. Anderson
Posted on: September 24, 2022
The ideal Clinical Data Abstractor will have experience in
contouring tumors for medical radiology images. This candidate will
also have experience with data mining, analyzing it and/or working
with large data sets. If the candidate has experience as an
annotator, the department can teach the individual how to analyze
the data. Internal candidates are welcomed. This is a remote
The mission of The University of Texas MD Anderson Cancer Center is
to eliminate cancer in Texas,
the nation, and the world through outstanding programs that
integrate patient care, research and
prevention, and through education for undergraduate and graduate
students, trainees, professionals,
employees and the public.
The primary function of the Clinical Data Abstractor role is to
abstract and codes information from
patient medical records to obtain clinical and research data and
work with the Tumor Measurement
Initiative (TMI). The Tumor Measurement Initiative aims to build an
institutional platform to
support standardized, automated, quantitative imaging-based tumor
measurement across each patient's
journey to advance multidisciplinary, data-driven, high precision
cancer treatment. This individual
be responsible for annotating images, meticulous record keeping
including procedural documentation,
and participating in optimization of TMI procedures and workflows
to fulfil this objective. They
will also have oversight and management of imaging databases
associated with TMI and research
projects. Scope includes regular collaboration and verbal updates
with TMI and lab team members.
Caring: By our words and actions we demonstrate caring toward
* We are sensitive to the concerns of our patients, their loved
ones and our
* We are respectful and courteous to each other and practice
* We promote and reward teamwork and inclusion.
Integrity: We work together with professionalism to merit the trust
of our colleagues and those we
serve in all that we do.
* We hold ourselves, and each other, accountable for our work -
decisions and data -
and for practicing our values and ethics.
* We advocate for diversity and equity for our workforce, for those
we serve and for
* We communicate frequently, honestly, openly and responsibly.
Discovery: We embrace creativity and seek new knowledge from
* We encourage continuous learning, seeking out information and new
* We team with each other to identify and resolve problems.
* We seek personal growth and enable others to do so.
Safety: We provide a safe environment - physically and
psychologically - for our patients, for our
colleagues and for our community.
* We create a sense of security and empowerment and are committed
to keeping one
another free from harm.
* We embrace a framework and best practices for the highest quality
of care and
* We inspire trust by modeling excellence in our work and
acceptance of each person's
Stewardship: We protect and preserve our institutional reputation
and the precious resources -
people, time, financial and environmental - entrusted to us.
* We prioritize the health and well-being of each other.
* We act responsibly to safeguard the institution's finances.
* We ensure the proper care and use of time, data, materials,
equipment and property
afforded to us.
The goals of our research are to curate and annotate imaging data
and associated data collected at
the institution to support development and validation of automate
tools to facilitate future image
analysis and quantitative imaging research with a longer-term goal
of clinical translation and
Artificial intelligence (AI) techniques are being developed to
segment (e.g. delineate the boundary) of tumors and normal tissues.
The ability to efficiently and automatically perform this task will
have a significant impact on image guidance techniques. The
segmentation and pre-treatment analysis information will be used as
input to the biomechanical model-based registration to optimize the
accuracy of the algorithm. Direct experience using RayStation for
image analysis, segmentation, and annotation is required.
Familiarity with DICOM standards, PACS integration, RIS, HL7
standards is highly preferred. Must be adaptable to change and able
to interact with co-workers and customers in a positive manner, as
well as communicate in an effective manner.
1. Generation of annotations for TMI automation
* Generating manual segmentations on images to support TMI
automation algorithm training and test data
* Clearly communicate and coordinate with subject matter experts to
ensure appropriate oversight and review of annotations.
* Prepare timely annotation progress updates for TMI sponsor
* Collaborate with TMI Automation team on use of tools and
processes which can be leveraged for segmentation and / or XNAT IQ
2. Work with Engineering Data Engineering Analytics Team to:
* Identify new data sets and elements required to support TMI
(e.g., genetic mutations from molecular diagnostics).
* Obtain knowledge and guidance on use of context engine tools
(e.g., Foundry, Slicer Dicer, etc.) for cohort curation and
development of data sets required to support TMI.
3. Record Keeping and Data Collection:
* Maintain accurate, detailed records and data and protocols.
* Prepare summary tables and graphs for data tracking and as
* Collaborate with subject matter experts to document procedures as
needed to support and / or sustain program initiatives.
4. Demonstrate and practice data governance precautions.
* Receive verbal and/or written instructions from supervisor on
standards and specialized data governance procedures.
* Attend required courses/certification for human subjects
* Have working knowledge of imaging-related platforms - with
reference to procedure manuals whenever necessary.
* Monitor workflow as it pertains to the need for additional data
ingress requests, alignment/coverage by IRB and material transfer
agreement requirements for data collaborations.
5. Organization and performance of TMI procedures and workflows
* Expand knowledge of ongoing techniques and enhance proficiency in
planning, executing, and troubleshooting these techniques.
* Participate in adopting new techniques while continuously
increasing knowledge and skills to enhance research efforts.
* Maintain assertiveness and flexibility in approaching new
responsibilities; utilize good work habits and time management.
6. Written and Verbal Communication to support research
* Assist with writing and submitting abstracts, research project
plans, grants, protocols and manuscripts
* Provide regular verbal updates on progress to the TMI team
7. Other duties as assigned by PI or supervisor.
High school diploma or equivalent. Two years of experience in tumor
registry, healthcare, or related field. Additional years of
education may be substituted for required experience on a one to
one year basis. It is the policy of The University of Texas MD
Anderson Cancer Center to provide equal employment opportunity
without regard to race, color, religion, age, national origin, sex,
gender, sexual orientation, gender identity/expression, disability,
protected veteran status, genetic information, or any other basis
protected by institutional policy or by federal, state or local
laws unless such distinction is required by law.
* Requisition ID: 152940
* Employment Status: Full-Time
* Employee Status: Regular
* FLSA: non-exempt, eligible for overtime, and is subject to the
provisions of the Fair Labor Standards Act (FLSA)
* Work Week: Days
* Fund Type: Soft
* Work Location: Onsite
* Pivotal Position: No
* Minimum Salary: US Dollar (USD) 39,500
* Midpoint Salary: US Dollar (USD) 49,500
* Maximum Salary : US Dollar (USD) 59,500
* Science Jobs: No
Keywords: University of Texas M.D. Anderson, Houston , Clinical Data Abstracter - Thoracic Imaging, Healthcare , Houston, Texas
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