Graphical display of diagnostic test results in electronic health Records: a comparison of 8 systems. (19th March 2015)

• Record Type: Journal Article
• Authors: Sittig, Dean F; Murphy, Daniel R; Smith, Michael W; Russo, Elise; Wright, Adam; Singh, Hardeep
• Is Part Of: Journal of the American Medical Informatics Association. Volume 22:Number 4(2015:Jul.)
• Page Start: 900
• Page End: 904
• Publication Date: 2015-03-19
• Subjects: diagnostic tests -- user computer interface -- electronic health records -- national health policy; Medical informatics -- Periodicals; Information Services -- Periodicals; Medical Informatics -- Periodicals; Médecine -- Informatique -- Périodiques; Informatica; Geneeskunde; Informatique médicale; Computer network resources; Electronic journals; 610.285
• DOI: 10.1093/jamia/ocv013
• Languages: English
• ISSNs: 1067-5027

Abstract

Abstract: Accurate display and interpretation of clinical laboratory test results is essential for safe and effective diagnosis and treatment. In an attempt to ascertain how well current electronic health records (EHRs) facilitated these processes, we evaluated the graphical displays of laboratory test results in eight EHRs using objective criteria for optimal graphs based on literature and expert opinion. None of the EHRs met all 11 criteria; the magnitude of deficiency ranged from one EHR meeting 10 of 11 criteria to three EHRs meeting only 5 of 11 criteria. One criterion (i.e., the EHR has a graph with y -axis labels that display both the name of the measured variable and the units of measure) was absent from all EHRs. One EHR system graphed results in reverse chronological order. One EHR system plotted data collected at unequally-spaced points in time using equally-spaced data points, which had the effect of erroneously depicting the visual slope perception between data points. This deficiency could have a significant, negative impact on patient safety. Only two EHR systems allowed users to see, hover-over, or click on a data point to see the precise values of the x–y coordinates. Our study suggests that many current EHR-generated graphs do not meet evidence-based criteria aimed at improving laboratory data comprehension.