Evaluations of physiological monitoring displays: a systematic review.
OBJECTIVE
The purpose of this paper is to present the findings from a systematic review of evaluation studies for physiologic monitoring displays, centered on empirical assessments across all available settings and samples. The findings from this review give readers the opportunity to examine past work across studies and set the stage for the design and conduct of future evaluations.


METHODS
A broad literature search of the literature from 1991 to June 2007 on PubMed and PsycINFO databases was completed to locate data-based articles for physiologic monitoring device display evaluations. The results of this search plus several unpublished works yielded 23 publications and 31 studies.


RESULTS
Participants were faster detecting an adverse event, making a diagnosis or a clinical decision in 18 of 31 studies. They showed improved accuracy in a clinical decision or diagnosis in 13 of 19 studies and they perceived a decreased mental workload in 3 of 8 studies. Eighteen studies used a within subjects design (mean sample size 16.5), and 9 studies used a between group design (mean group size 7.6). Study settings were usability laboratories for 15 studies and patient simulation laboratories for 6 studies. Study participants were anesthesiologists or anesthesiology residents for 19 studies and nurses for 5 studies.


CONCLUSIONS
The advent of integrated graphical displays ushered a new era into physiological monitoring display designs. All but one study reported significant differences between traditional, numerical displays and novel displays; yet we know little about which graphical displays are optimal and why particular designs work. Future authors should use a theoretical model or framework to guide the study design, focus on other clinical study participants besides anesthesiologists, employ additional research methods and use more realistic and complex tasks and settings to increase external validity.
Department of Anesthesiology, University of Utah, Salt Lake City, UT 84132, USA. matthias@abl.med.utah.edu
Matthias
M
Görges
Nancy
N
Staggers
D000328:Adult; D000776:Anesthesiology / Q000295:instrumentation; D003626:Data Display; D004867:Equipment Design; D006801:Humans; D008954:Models, Biological; D008991:Monitoring, Physiologic / Q000295:instrumentation* / Q000379:methods*; D013673:Technology Assessment, Biomedical; D014584:User-Computer Interface