Description
A coarse classification of medications into two risk categories, one for high-risk medications and one for all others, allows people to focus safety improvement work on medications that carry the highest risks of harm. However, such coarse categorization does not distinguish the relative risk of harm for the majority of medications. To begin to develop a more fine-grained measurement scale for the relative risk of harm spanning many medications, we performed an experiment with 18 practicing pharmacists. Each pharmacist-participant made 210 paired comparisons of 21 commonly prescribed medications to reveal a subjective scale of perceived medication worrisomeness (PMW). Statistical analyses of their collective judgments of medication pairs differentiated five levels of PMW. This study illuminates one path towards a fine-grained medication risk scale based on PMW. It also shows how the method of paired comparisons can be used to remotely crowdsource expert knowledge in support of learning health systems.
Learning Objective: Learn methods for crowdsourcing knowledge from experts, including well-established data analytic approaches, and see how these methods can be applied to develop a measurement scale for perceived medication worrisomeness.
Authors:
Allen Flynn (Presenter)
School of Medicine University of Michigan
Greg Farris, School of Medicine University of Michigan
George Meng, School of Medicine University of Michigan
Jack Allan, School of Medicine University of Michigan
Sara Kurosu, School of Medicine University of Michigan
Natalie Lampa, University of Michigan
Koki Sasagawa, School of Medicine University of Michigan
Presentation Materials: