Alecia Lashier
Papers
1
Total Citations
41
H-Index
1
About
Alecia Lashier is a researcher whose work sits at the intersection of healthcare operations, data mining, and pharmacy informatics. Her primary research area focuses on optimizing pharmacy workflows through computational analysis, particularly in the context of robotic dispensing systems. Lashier’s most notable contribution is her 2016 study, "Pharmacy robotic dispensing and planogram analysis using association rule mining with prescription data," which has garnered 41 citations. In this work, she pioneered the application of association rule mining—a technique commonly used in market basket analysis—to prescription data, enabling more efficient arrangement of medications in automated dispensing cabinets. This approach not only reduced retrieval times but also minimized errors in high-volume pharmacy settings. By bridging the gap between data science and clinical pharmacy practice, Lashier has provided a scalable framework for improving inventory management and workflow efficiency. Her research is particularly impactful for hospital systems and large-scale pharmacies seeking to integrate robotics with data-driven decision-making. For students and researchers in health informatics, Lashier’s work exemplifies how traditional data mining methods can be creatively repurposed to solve real-world healthcare logistics challenges.
Research Focus
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Top Papers
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