Sociotechnical feasibility of natural language processing-driven tools in clinical trial eligibility prescreening for Alzheimer’s disease and related dementias
Journal of the American Medical Informatics Association, Volume 31, Issue 5, May 2024, Pages 1062–1073,
Presenter
Betina Idnay, PhD, RN
Statement of Purpose
Current clinical trials continue to suffer from low recruitment rates. Improving the recruitment process is a crucial step towards eliminating barriers that inhibit participation and expediting potential treatments as they hold significant implications for enhancing better health outcomes. This challenge is potentially addressable via natural language processing (NLP) technologies for researchers to effectively identify eligible clinical trial participants. However, implementing informatics systems in clinical research, just like in any other setting, requires a deep understanding of sociotechnical systems. This present study evaluated the sociotechnical feasibility of electronic prescreening tools, both NLP and non-NLP-driven systems, for ADRD clinical research eligibility prescreening. We focused on how cognitive complexity influences system usability, identified sociotechnical gaps in system implementation, and recommended the necessary cognitive support for optimal use of NLP systems.
Learning Outcomes
Participants will be able to:
- discuss how NLP technology can optimize the prescreening process for clinical research by extracting data from both structured and unstructured EHR sources,
- interpret the feasibility of electronic prescreening tools within sociotechnical systems, and
- evaluate the impact of cognitive complexity on the usability of informatics systems, including the subjective experience of users interacting with NLP tools.
Format
- 35-minute presentation by article author(s) considering salient features of the published study and its potential impact on practice
- 25-minute discussion of questions submitted by listeners via the webinar tools and moderated by JAMIA Student Editorial Board members.
CME Credit
The American Medical Informatics Association is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians.
The American Medical Informatics Association designates this live activity for a maximum of 1.0 AMA PRA Category 1™ credits. Physicians should claim only the credit commensurate with the extent of their participation in the activity.
CNE Credit
The American Medical Informatics Association is accredited as a provider of nursing continuing professional development by the American Nurses Credentialing Center's Commission on Accreditation.
- Approved Contact Hours: 1.0 total
- Nurse Planner: Jenna Thate, PhD, RN, CNE