(P-497) Use of Knowledge Bases in Medical Education: Medical Students’ Perspective

Background: A knowledgebase for drug information contains organized and structured data based on
scientific literature (1). Janusmed drug drug interaction, pregnancy, and breastfeeding are examples of well-known knowledgebases which provide evidence-based and easily accessible drug information (2). The medical
students to be excellent physicians in the future should learn how to access, search, navigate and evaluate the
available information resources efficiently. Understanding how the medical students approach this information
will give the educators structured feedback to enhance the learning process (3).

references
1. Stefik M. Introduction to knowledge systems. San Francisco, CA: Morgan Kaufman; 1995.
2. Janusinfo policy - Janusinfo.se [Internet]. [cited 2020 Nov 20]. Available from: https://janusinfo.se/omoss/janusinfopolicy.4.7e3d365215ec82458644fca0.html
3. Nicholson J. Understanding medical student evidence-based medicine information seeking in an authentic clinical simulation.

Objectives: To assess to what extent knowledgebases on drug information are integrated into medical education.

Methods: Study participants: Medical students who started clinical rotation at Karolinska Institutet and Linkoping University.
Methodology: Self-administered electronic questionnaire and focus group discussion. If Covid-19 regulation prevent physical discussion, zoom or Microsoft teams will be used.
Sample size: Electronic questionnaire will be distributed via email for all students and 12 students for focus group discussion will be asked to participate, one group discussion for each university.
Data collection timeline: Four weeks for questionnaires starting in February 2021. One focus group discussion at each university during March 2021.
What this study will add: Knowledge will be collected from the medical students to reflect their perceptions and needs.

Results: Questionnaire analysis: The raw data will be coded, entered, and analyzed using the SPSS (Statistical Package for Social Sciences) for windows. Data will be described using frequency distribution tables and the Z test will be used.
- FGD analysis: The raw data will be interpreted manually by using an excel sheet, where the FGD and transcripts will be coded, and for the extracted texts the underlying meaning, code, category, and theme will be assigned.

Conclusions: the data collection is in February and March 2021
the data analysis will be done in April 2021
this work is a master thesis work for a master degree in Health Informatics at Karolinska Institutet so the work will be finished in May 2021