Hosted by the Self-Care Therapeutics/Nonprescription Medicine SIG
In this presentation, we will share information about an electronic tool we have developed to help pharmacy students practice making therapeutic decisions related to common health conditions that can be self-treated. The tool uses decision algorithms that include both patient- and condition-related factors that should be considered when making evidence-based treatment recommendations. We will share preliminary data about the impact of the tool on student learning based on exam scores, student perceptions, and website utilization.
Objectives
- Identify patient- and condition-related factors that influence whether a patient is a candidate for self-treatment, and if so, medication appropriateness.
- Discuss the impact of access to electronic decision algorithms on student learning in a P1 self-therapeutics course.
Moderator
Erin Slazak, PharmD, BCPS, BCACP
Clinical Associate Professor
University at Buffalo School of Pharmacy and Pharmaceutical Sciences
Presenters
Sarah Vordenberg, PharmD, MPH
Clinical Associate Professor
University of Michigan College of Pharmacy
Michael Dorsch, PharmD, MS
Assistant Professor
University of Michigan College of Pharmacy
Ken Debacker, B.S.
Software Developer/Data Analyst
University of Michigan College of Pharmacy
Paige Whittaker, PharmD Candidate 2023
University of Michigan College of Pharmacy