TY - GEN
T1 - Usability of reports generated by a computerised dose prediction software
AU - Baysari, Melissa
AU - Chan, Joanne
AU - Carland, Jane
AU - Stocker, Sophie
AU - Moran, Maria
AU - Day, Richard
N1 - Copyright the Author(s) and IOS Press 2018. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.
PY - 2018/1/1
Y1 - 2018/1/1
N2 - Computerised dose prediction software assist clinicians in undertaking therapeutic drug monitoring by providing individualised dosing recommendations, typically communicated to prescribers in the form of a report. These software are highly sophisticated and accurate in predicting individualised dosage regimens, but if the information contained in the report is not understood by prescribers, the benefits of the software are not achieved. In this study, we set out to assess the perceived usability of a report generated from a dose prediction system. Fifteen prescribers were presented with a mock report and asked a number of questions to elicit their views of the report's content and design. Overall, we found that the mock report was effective in communicating the recommended dose of a drug, but this recommendation was presented alongside information that was not understood or was unlikely to be utilised by prescribers. In particular, the aspects of the report viewed negatively by end-users largely related to a lack of familiarity with the pharmacological terminology used in the report, which hindered understanding and caused confusion. Involving prescribers early on in the process of designing decision support systems is likely to result in systems and outputs that are more useful, usable and accessible to users.
AB - Computerised dose prediction software assist clinicians in undertaking therapeutic drug monitoring by providing individualised dosing recommendations, typically communicated to prescribers in the form of a report. These software are highly sophisticated and accurate in predicting individualised dosage regimens, but if the information contained in the report is not understood by prescribers, the benefits of the software are not achieved. In this study, we set out to assess the perceived usability of a report generated from a dose prediction system. Fifteen prescribers were presented with a mock report and asked a number of questions to elicit their views of the report's content and design. Overall, we found that the mock report was effective in communicating the recommended dose of a drug, but this recommendation was presented alongside information that was not understood or was unlikely to be utilised by prescribers. In particular, the aspects of the report viewed negatively by end-users largely related to a lack of familiarity with the pharmacological terminology used in the report, which hindered understanding and caused confusion. Involving prescribers early on in the process of designing decision support systems is likely to result in systems and outputs that are more useful, usable and accessible to users.
KW - Decision support
KW - dose prediction software
KW - usability
UR - http://www.scopus.com/inward/record.url?scp=85056391997&partnerID=8YFLogxK
U2 - 10.3233/978-1-61499-890-7-27
DO - 10.3233/978-1-61499-890-7-27
M3 - Conference proceeding contribution
C2 - 30040678
SN - 9781614998891
T3 - Studies in health technology and informatics
SP - 27
EP - 32
BT - Connecting the System to Enhance the Practitioner and Consumer Experience in Healthcare
A2 - Cummings, Elizabeth
A2 - Ryan, Angela
A2 - Schaper, Louise K.
PB - IOS Press
CY - Amsterdam
T2 - 26th Australian National Health Informatics Conference (HIC 2018)
Y2 - 29 July 2018 through 1 August 2018
ER -