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. 2023 Dec 22;31(1):61-69.
doi: 10.1093/jamia/ocad209.

Inpatient nurses' preferences and decisions with risk information visualization

Alvin D Jeffery  1   2   3 , Carrie Reale  4   5 , Janelle Faiman  4   5 , Vera Borkowski  1 , Russ Beebe  4   5 , Michael E Matheny  2   3   6   7 , Shilo Anders  2   4   5
Affiliations

Inpatient nurses' preferences and decisions with risk information visualization

Alvin D Jeffery et al. J Am Med Inform Assoc. .

Abstract

Objective: We examined the influence of 4 different risk information formats on inpatient nurses' preferences and decisions with an acute clinical deterioration decision-support system.

Materials and methods: We conducted a comparative usability evaluation in which participants provided responses to multiple user interface options in a simulated setting. We collected qualitative data using think aloud methods. We collected quantitative data by asking participants which action they would perform after each time point in 3 different patient scenarios.

Results: More participants (n = 6) preferred the probability format over relative risk ratios (n = 2), absolute differences (n = 2), and number of persons out of 100 (n = 0). Participants liked average lines, having a trend graph to supplement the risk estimate, and consistent colors between trend graphs and possible actions. Participants did not like too much text information or the presence of confidence intervals. From a decision-making perspective, use of the probability format was associated with greater concordance in actions taken by participants compared to the other 3 risk information formats.

Discussion: By focusing on nurses' preferences and decisions with several risk information display formats and collecting both qualitative and quantitative data, we have provided meaningful insights for the design of clinical decision-support systems containing complex quantitative information.

Conclusion: This study adds to our knowledge of presenting risk information to nurses within clinical decision-support systems. We encourage those developing risk-based systems for inpatient nurses to consider expressing risk in a probability format and include a graph (with average line) to display the patient's recent trends.

Keywords: clinical; clinical decision rules; decision-support systems; electronic health records; medical informatics; risk prediction display.

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Conflict of interest statement

None declared.

Figures

Figure 1.
Figure 1.
Example of 4 different risk display formats.
Figure 2.
Figure 2.
Example of interface (Scenario C, Timepoint 2, with the Probability [P] risk format).
Figure 3.
Figure 3.
Four different options for presenting confidence intervals on trended risk graph. Subplot 1: example of scenario with no confidence intervals. Subplot 2: confidence interval illustrated as a linear function. Subplot 3: confidence interval illustrated as a step function (similar to point estimates presented in scenarios). Subplot 4: same as subplot 3 but with greyscale color palette.
Figure 4.
Figure 4.
(A-C) Highest-level action taken by each participant after each timepoint for all scenarios. While agreement moved from 60% at Time 1 to 90% at Time 4, there were increased deviations from the mode seen when participants saw “number of persons out of 100.”
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References

    1. Dunn Lopez K, Gephart SM, Raszewski R, et al.Integrative review of clinical decision support for registered nurses in acute care settings. J Am Med Inform Assoc. 2017;24(2):441-450. 10.1093/jamia/ocw084 - DOI - PMC - PubMed
    1. Miller K, Mosby D, Capan M, et al.Interface, information, interaction: a narrative review of design and functional requirements for clinical decision support. J Am Med Inform Assoc. 2018;25(5):585-592. 10.1093/jamia/ocx118 - DOI - PMC - PubMed
    1. Graham TA, Kushniruk AW, Bullard MJ, et al.How usability of a web-based clinical decision support system has the potential to contribute to adverse medical events. AMIA Annu Symp Proc. 2008:257-261. - PMC - PubMed
    1. Campbell EM, Guappone KP, Sittig DF, et al.Computerized provider order entry adoption: implications for clinical workflow. J Gen Intern Med. 2009;24(1):21-26. 10.1007/s11606-008-0857-9 - DOI - PMC - PubMed
    1. Kushniruk AW, Triola MM, Borycki EM, et al.Technology induced error and usability: the relationship between usability problems and prescription errors when using a handheld application. Int J Med Inform. 2005;74(7-8):519-526. 10.1016/j.ijmedinf.2005.01.003 - DOI - PubMed

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