Literature DB >> 30040678

Usability of Reports Generated by a Computerised Dose Prediction Software.

Melissa Baysari1, Joanne Chan2, Jane Carland3, Sophie Stocker3, Maria Moran4, Richard Day3.   

Abstract

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.

Keywords:  Decision support; dose prediction software; usability

Mesh:

Year:  2018        PMID: 30040678

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  1 in total

1.  Would they accept it? An interview study to identify barriers and facilitators to user acceptance of a prescribing advice service.

Authors:  Rachel Constance Yager; Natalie Taylor; Sophie Lena Stocker; Richard Osborne Day; Melissa Therese Baysari; Jane Ellen Carland
Journal:  BMC Health Serv Res       Date:  2022-04-18       Impact factor: 2.908

  1 in total

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