Objective To evaluate how clinical chemistry test results were assessed by volunteers when presented with four different visualization techniques. Materials and methods A total of 20 medical students reviewed quantitative test results from 4 patients using 4 different visualization techniques in a balanced, crossover experiment. The laboratory data represented relevant patient categories, including simple, emergency, chronic and complex patients. Participants answered questions about trend, overall levels and covariation of test results. Answers and assessment times were recorded and participants were interviewed on their preference of visualization technique. Results Assessment of results and the time used varied between visualization techniques. With sparklines and relative multigraphs participants made faster assessments. With relative multigraphs participants identified more covarying test results. With absolute multigraphs participants found more trends. With sparklines participants more often assessed laboratory results to be within reference ranges. Different visualization techniques were preferred for the four different patient categories. No participant preferred absolute multigraphs for any patient. Discussion Assessments of clinical chemistry test results were influenced by how they were presented. Importantly though, this association depended on the complexity of the result sets, and none of the visualization techniques appeared to be ideal in all settings. Conclusions Sparklines and relative multigraphs seem to be favorable techniques for presenting complex long-term clinical chemistry test results, while tables seem to suffice for simpler result sets.
Presentation of clinical laboratory results: an experimental comparison of four visualization techniques
Torbjørn Torsvik,Børge Lillebo,Gustav Mikkelsen
Published 2012 in J. Am. Medical Informatics Assoc.
ABSTRACT
PUBLICATION RECORD
- Publication year
2012
- Venue
J. Am. Medical Informatics Assoc.
- Publication date
2012-10-06
- Fields of study
Medicine, Computer Science
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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