Design and Evaluation of Low-Fidelity Visual Display Prototypes for Multiple Hospital-Acquired Conditions

Abstract

Hospital-acquired conditions such as catheter-associated urinary tract infection, stage 3 or 4 hospital-acquired pressure injury, and falls with injury are common, costly, and largely preventable. This study used participatory design methods to design and evaluate low-fidelity prototypes of clinical dashboards to inform high-fidelity prototype designs to visualize integrated risks based on patient profiles. Five low-fidelity prototypes were developed through literature review and by engaging nurses, nurse managers, and providers as participants (N = 23) from two hospitals in different healthcare systems using focus groups and interviews. Five themes were identified from participatory design sessions: Need for Integrated Hospital-Acquired Condition Risk Tool, Information Needs, Sources of Information, Trustworthiness of Information, and Performance Tracking Perspectives. Participants preferred visual displays that represented patient comparative risks for hospital-acquired conditions using the familiar design metaphor of a gauge and green, yellow, and red “traffic light” colors scheme. Findings from this study were used to design a high-fidelity prototype to be tested in the next phase of the project. Visual displays of hospital-acquired conditions that are familiar in display and simplify complex information such as the green, yellow, and red dashboard are needed to assist clinicians in fast-paced clinical environments and be designed to prevent alert fatigue.

Dashboard Design to Identify and Balance Competing Risk of Multiple Hospital-Acquired Conditions

“…Participants suggested additional EHR design elements that would be helpful to the end user including (1) hovering over information in the EHR to understand patient-specific information, (2) predicting risk for multiple days, (3) viewing data of risk prospectively and retrospectively to help inform clinical decisions and "drilling down" for more patient data to understand multiple risks. Reeder et al 11 provided a full report of this segment of the study and results. Full analysis of findings from the low fidelity focus groups informed the final high-fidelity prototype.…”

“…Fifth, initial colors for the traffic light were informed by participants in the third part of the study. 11 Elements of color blindness for clinicians that may use the study were identified but not further developed in this proof of concept study. Further research is needed developing dashboard tools that provide meaningful color schemes addressing color blindness yet align with familiar symbols such as traffic light colors.…”

“…The intent was to observe participants' exploration and usability of the high-fidelity dashboard using a thinkaloud protocol with cognitive walk-throughs and exploratory questions. Think-aloud methods 11,[23][24][25] involved inviting the participants to talk aloud about their experiences while performing a task with a designed artifact and to narrate how they interpreted and would use the MHAC dashboard prototype.…”

“…The complexity of health care data and workflow associated with the electronic health records (EHRs) creates challenges within and among clinicians 9 and makes it difficult to see a clear profile of the patient's interrelated risks. 7 10 11 Comprehensive assessment of patient MHAC risks from single HAC information is not ideal because it requires navigation across multiple EHR screens and does not identify competing prevention strategies. Additionally, EHR navigation and displays of HAC risk assessment may be presented differently based on the user's health care role.…”

“…14 There is a lack of development and evaluation of dashboard tools that clinicians could use to monitor and manage competing risks of MHACs to reduce patient harm. 10 11 Understanding tradeoffs related to the clinical assessment and interventions focused on the prevention of one condition without considering the entire clinical context for each HAC risk for a patient presents an opportunity to understand how a dashboard might inform clinicians' understanding of risks of MHACs related to competing intervention strategies.…”