Evaluating Varied Label Designs for Use with Medical Devices: Optimized Labels Outperform Existing Labels in the Correct Selection of Devices and Time to Select.
OBJECTIVE
Effective standardization of medical device labels requires objective study of varied designs. Insufficient empirical evidence exists regarding how practitioners utilize and view labeling.


OBJECTIVE
Measure the effect of graphic elements (boxing information, grouping information, symbol use and color-coding) to optimize a label for comparison with those typical of commercial medical devices.


METHODS
Participants viewed 54 trials on a computer screen. Trials were comprised of two labels that were identical with regard to graphics, but differed in one aspect of information (e.g., one had latex, the other did not). Participants were instructed to select the label along a given criteria (e.g., latex containing) as quickly as possible. Dependent variables were binary (correct selection) and continuous (time to correct selection).


METHODS
Eighty-nine healthcare professionals were recruited at Association of Surgical Technologists (AST) conferences, and using a targeted e-mail of AST members.


RESULTS
Symbol presence, color coding and grouping critical pieces of information all significantly improved selection rates and sped time to correct selection (α = 0.05). Conversely, when critical information was graphically boxed, probability of correct selection and time to selection were impaired (α = 0.05). Subsequently, responses from trials containing optimal treatments (color coded, critical information grouped with symbols) were compared to two labels created based on a review of those commercially available. Optimal labels yielded a significant positive benefit regarding the probability of correct choice ((P<0.0001) LSM; UCL, LCL: 97.3%; 98.4%, 95.5%)), as compared to the two labels we created based on commercial designs (92.0%; 94.7%, 87.9% and 89.8%; 93.0%, 85.3%) and time to selection.


CONCLUSIONS
Our study provides data regarding design factors, namely: color coding, symbol use and grouping of critical information that can be used to significantly enhance the performance of medical device labels.
Michigan State University School of Packaging; East, Lansing, Michigan, United States of America.
Laura
http://orcid.org/0000-0002-5779-7474
L
Bix
Michigan State University School of Packaging; East, Lansing, Michigan, United States of America.
Do Chan
DC
Seo
Statistical Consulting Center, CANR Biometry Group, Michigan State University; East Lansing, Michigan, United States of America.
Moslem
M
Ladoni
Michigan State University School of Packaging; East, Lansing, Michigan, United States of America.
Eric
E
Brunk
Cognitive and Cognitive Neurosciences Group, Department of Psychology, Michigan State University; East Lansing, Michigan, United States of America.
Mark W
MW
Becker
D001288:Attention / Q000502:physiology; D002755:Choice Behavior / Q000502:physiology; D003116:Color; D003201:Computers; D004864:Equipment and Supplies; D005260:Female; D007722:Health Knowledge, Attitudes, Practice; D006282:Health Personnel / Q000523:psychology*; D006801:Humans; D008297:Male; D008875:Middle Aged; D011356:Product Labeling / Q000379:methods*