TY - GEN
T1 - An Interactive Visualization Tool for Medication (Re)fill Adherence
T2 - 10th IEEE International Conference on Healthcare Informatics, ICHI 2022
AU - Gorman, Kevin
AU - Ratsev, Ilia
AU - Lu, Louise
AU - Taylor, Casey Overby
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - While many studies have examined reasons for poor adherence to drug labeling instructions, there is a lack of research into the characteristics of individuals who stop taking their medication after an initial fill. We designed an interactive visualization tool (IVT) for showing trends in medication adherence across medication types and insurance types. The IVT was validated by showing results consistent with trends of previous studies indicating decreases in asthma medication fill rates in the summer between peak rates in the spring and fall across multiple sexes, insurance types, and ages. This drop-off is greater for inhaled corticosteroid fills than for leukotriene modifiers, which was also previously observed. Having an IVT enables rapidly visualizing more targeted populations and may show new insights. For example, there appears to be a similar degree of drop-off in medication fills for different sexes, but not for different age groups. We believe that the use of this tool may help guide new research directions as illustrated in our case study visualizing asthma medication adherence.
AB - While many studies have examined reasons for poor adherence to drug labeling instructions, there is a lack of research into the characteristics of individuals who stop taking their medication after an initial fill. We designed an interactive visualization tool (IVT) for showing trends in medication adherence across medication types and insurance types. The IVT was validated by showing results consistent with trends of previous studies indicating decreases in asthma medication fill rates in the summer between peak rates in the spring and fall across multiple sexes, insurance types, and ages. This drop-off is greater for inhaled corticosteroid fills than for leukotriene modifiers, which was also previously observed. Having an IVT enables rapidly visualizing more targeted populations and may show new insights. For example, there appears to be a similar degree of drop-off in medication fills for different sexes, but not for different age groups. We believe that the use of this tool may help guide new research directions as illustrated in our case study visualizing asthma medication adherence.
KW - Adherence
KW - Asthma
KW - Medication
KW - Medication Disparity
KW - Visualization
UR - http://www.scopus.com/inward/record.url?scp=85139073940&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85139073940&partnerID=8YFLogxK
U2 - 10.1109/ICHI54592.2022.00044
DO - 10.1109/ICHI54592.2022.00044
M3 - Conference contribution
AN - SCOPUS:85139073940
T3 - Proceedings - 2022 IEEE 10th International Conference on Healthcare Informatics, ICHI 2022
SP - 239
EP - 244
BT - Proceedings - 2022 IEEE 10th International Conference on Healthcare Informatics, ICHI 2022
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 11 June 2022 through 14 June 2022
ER -