- American Academy of Nursing. 01/2017 - present. Position : Informatics and Technology Expert Panel Member.
- Board of Scientific Counselors, Lister Hill National Center for Biomedical Communications, National Library of Medicine. 01/2017 - 12/2018. Position : Chair (2017-2018).
- Ambassador Program, Friends of the National Institute of Nursing Research. 01/2017 - present. Position : Ambassador.
- Nurse Scientist Translational Interest Research Group (NIH NCATS sponsored working group). 08/2016 - present. Position : Member.
- Alliance for Nursing Informatics Emerging Leaders Program. 01/2016 - 12/2018. Position : Mentor.
- Academy of Health Sciences Educators. 01/2016 - present. Position : Member.
- NEXUS Systems, Leadership, Informatics and Policy Cluster Group. 01/2015 - 12/2016. Position : Member.
- American Medical Informatics Association. 01/01/2015 - 12/31/2015. Position : Member.
- Utah Nursing Informatics Network. 01/01/2015 - 12/31/2015. Position : President.
- Alliance for Nursing Informatics. 01/01/2015 - 12/31/2015. Position : Steering Committee - Elected Member.
- American Nurses Association. 01/01/2015 - 12/31/2015. Position : Member.
- American Academy of Nursing. 01/01/2015 - 12/31/2015. Position : Fellow.
- Healthcare Information and Management Systems Society (HIMSS). 01/01/2015 - 12/31/2015. Position : Member.
- Board of Scientific Counselors, Lister Hill National Center for Biomedical Communications, National Library of Medicine. 01/2014 - 12/2018. Position : Member.
- PCORI (Patient-Centered Outcomes Research Institute). 01/2014 - present. Position : Reviewer Pool.
- Alliance for Nursing Informatics. 01/2013 - 12/2016. Position : Steeering Committee Member at-large (national elected position).
I design coursework to meet specific and practical learning objectives through a variety of teaching methods. I believe problem solving and active learning lead to the best learning outcomes, and so I mix student-led activities and practical, problem-based learning exercises with lecture content. My courses typically involve at least one group assignment or activity because real-world informatics projects require interdisciplinary teamwork. I enjoy teaching online, and my preference to design courses with a mix of online asynchronous learning and synchronous, in-person class meetings.
Intro to Information & Information Technology
Introductory graduate course in information management focusing on the theoretical basis of information and technology with an emphasis on management and processing of clinical data, information, and knowledge. The emphasis of this course is on the use of information and technology in health care and nursing practice. Structured data and processes are addressed. Information technologies use in nursing practice are explored. Issues that impact clinical practice and administrative decision are explore
NURS 6802/ BMI 6300
Clinical Decision Support/ Medical Decision Making
Decision-making theories and strategies related to clinical reasoning discussed. Methods of computer support for different reasoning strategies in clinical settings presented.
Seminar Practicum in Clinical Informatics
This course focuses on the integration of informatics course content into an informatics experience in a work setting. The goal of the course is to provide synthesis of informatics course content, requisite competencies and actual role expectations. The experience is designed to help students transition into the workplace and prepare them future informatics positions.
Clinical/ Nursing Informatics Practicum
Synthesis experience in organizations and agencies with ongoing clinical information activities. Integration of clinical informatics content, skills, and role expectation in a clinical informatics environment is emphasized. Laboratory sessions provide an opportunity for analysis of and reflection on clinical experiences.
Knowledge Discovery in Databases
This course emphasizes health care applications and issues of Knowledge Discovery in Databases (KDD) at an introductory level. The entire KDD process is explored, including creation of target data sets, pre-processing, data mining, pattern interpretation and evaluation, corresponding with the Fayyad model of the KDD process. Lecture and practical exercises survey data mining methods for classification, prediction, rule induction, clustering, and attribute sub-set selection. Later in the course, emphasis shifts to critical analysis of KDD applications in health care.