Appl Clin Inform 2010; 01(02): 177-196
DOI: 10.4338/ACI-2010-02-RA-0012
Research Article
Schattauer GmbH

Improving Clinical Trial Participant Tracking Tools Using Knowledge-anchored Design Methodologies

P.R.O. Payne
1  The Ohio State University, Department of Biomedical Informatics and Center for Clinical and Translational Science, Columbus, OH
,
P.J. Embi
2  University of Cincinnati, Center for Health Informatics and Department of Medicine, Cincinnati, OH
,
S.B. Johnson
3  Columbia University, Department of Biomedical Informatics, New York, NY
,
E. Mendonca
4  The University of Chicago, Department of Pediatrics, Chicago, IL
,
J. Starren
5  Marshfield Clinic Research Foundation, Marshfield, WI
› Author Affiliations
Further Information

Correspondence to:

Philip R.O. Payne, Ph.D.
The Ohio State University
Dept. of Biomedical Informatics, 3190 Graves Hall
333 West 10th Avenue
Columbus, Ohio, USA 43210

Publication History

Received 02 February 2010

Accepted 06 June 2010

Publication Date:
20 December 2017 (online)

 

Summary

Objective: Rigorous human-computer interaction (HCI) design methodologies have not traditionally been applied to the development of clinical trial participant tracking (CTPT) tools. Given the frequent use of iconic HCI models in CTPTs, and prior evidence of usability problems associated with the use of ambiguous icons in complex interfaces, such approaches may be problematic. Presentation Discovery (PD), a knowledge-anchored HCI design method, has been previously demonstrated to improve the design of iconic HCI models. In this study, we compare the usability of a CTPT HCI model designed using PD and an intuitively designed CTPT HCI model.

Methods: An iconic CPTP HCI model was created using PD. The PD-generated and an existing iconic CTPT HCI model were subjected to usability testing, with an emphasis on task accuracy and completion times. Study participants also completed a qualitative survey instrument to evaluate subjective satisfaction with the two models.

Results: CTPT end-users reliably and reproducibly agreed on the visual manifestation and semantics of prototype graphics generated using PD. The performance of the PD-generated iconic HCI model was equivalent to an existing HCI model for tasks at multiple levels of complexity, and in some cases superior. This difference was particularly notable when tasks required an understanding of the semantic meanings of multiple icons.

Conclusion: The use of PD to design an iconic CTPT HCI model generated beneficial results and improved end-user subjective satisfaction, while reducing task completion time. Such results are desirable in information and time intensive domains, such as clinical trials management.

Citation: Payne PRO, Embi PJ, Johnson SB, Mendonca E, Starren J. Improving clinical trial participant tracking tools using knowledge-anchored design methodologies. Appl Clin Inf 2010; 1: 177–196 http://dx.doi.org/10.4338/ACI-2010-02-RA-0012


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Conflict of Interest

The authors have no conflicts of interest related to the content or findings reported in this manuscript.


Correspondence to:

Philip R.O. Payne, Ph.D.
The Ohio State University
Dept. of Biomedical Informatics, 3190 Graves Hall
333 West 10th Avenue
Columbus, Ohio, USA 43210