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BackgroundThe proliferation of health care data in electronic health records (EHRs) is fueling the need for clinical decision support (CDS) that ensures accuracy and reduces cognitive processing and documentation burden. The CDS format can play a key role in achieving the desired outcomes. Building on our laboratory-based pilot study with 60 registered nurses (RNs) from 1 Midwest US metropolitan area indicating the importance of graph literacy (GL), we conducted a fully powered, innovative, national, and web-based randomized controlled trial with 203 RNs. ObjectiveThis study aimed to compare care planning time (CPT) and the adoption of evidence-based CDS recommendations by RNs randomly assigned to 1 of 4 CDS format groups: text only (TO), text+table (TT), text+graph (TG), and tailored (based on the RN’s GL score). We hypothesized that the tailored CDS group will have faster CPT (primary) and higher adoption rates (secondary) than the 3 nontailored CDS groups. MethodsEligible RNs employed in an adult hospital unit within the past 2 years were recruited randomly from 10 State Board of Nursing lists representing the 5 regions of the United States (Northeast, Southeast, Midwest, Southwest, and West) to participate in a randomized controlled trial. RNs were randomly assigned to 1 of 4 CDS format groups—TO, TT, TG, and tailored (based on the RN’s GL score)—and interacted with the intervention on their PCs. Regression analysis was performed to estimate the effect of tailoring and the association between CPT and RN characteristics. ResultsThe differences between the tailored (n=46) and nontailored (TO, n=55; TT, n=54; and TG, n=48) CDS groups were not significant for either the CPT or the CDS adoption rate. RNs with low GL had longer CPT interacting with the TG CDS format than the TO CDS format (P=.01). The CPT in the TG CDS format was associated with age (P=.02), GL (P=.02), and comfort with EHRs (P=.047). Comfort with EHRs was also associated with CPT in the TT CDS format (P

BackgroundPatient mobility is an evidenced-based physical activity intervention initiated during intensive care unit (ICU) admission and continued throughout hospitalization to maintain functional status, yet mobility is a complex intervention and not consistently implemented. Cognitive work analysis (CWA) is a useful human factors framework for understanding complex systems and can inform future technology design to optimize outcomes. ObjectiveThe aim of this study is to understand the complexity and constraints of the ICU work environment as it relates to nurses carrying out patient mobility interventions, using CWA. MethodsWe conducted a work domain analysis and completed an abstraction hierarchy using the CWA framework. Data from documents, observation (32 hours), and interviews with nurses (N=20) from 2 hospitals were used to construct the abstraction hierarchy. ResultsNurses seek information from a variety of sources and integrate patient and unit information to inform decision-making. The completed abstraction hierarchy depicts multiple high-level priorities that nurses balance, specifically, providing quality, safe care to patients while helping to manage unit-level throughput needs. Connections between levels on the abstraction hierarchy describe how and why nurses seek patient and hospital unit information to inform mobility decision-making. The analysis identifies several opportunities for technology design to support nurse decision-making about patient mobility. ConclusionsFuture interventions need to consider the complexity of the ICU environment and types of information nurses need to make decisions about patient mobility. Considerations for future system redesign include developing and testing clinical decision support tools that integrate critical patient and unit-level information to support nurses in making patient mobility decisions.

BackgroundPoor usability is a primary cause of unintended consequences related to the use of electronic health record (EHR) systems, which negatively impacts patient safety. Due to the cost and time needed to carry out iterative evaluations, many EHR components, such as clinical decision support systems (CDSSs), have not undergone rigorous usability testing prior to their deployment in clinical practice. Usability testing in the predeployment phase is crucial to eliminating usability issues and preventing costly fixes that will be needed if these issues are found after the system’s implementation. ObjectiveThis study presents an example application of a systematic evaluation method that uses clinician experts with human-computer interaction (HCI) expertise to evaluate the usability of an electronic clinical decision support (CDS) intervention prior to its deployment in a randomized controlled trial. MethodsWe invited 6 HCI experts to participate in a heuristic evaluation of our CDS intervention. Each expert was asked to independently explore the intervention at least twice. After completing the assigned tasks using patient scenarios, each expert completed a heuristic evaluation checklist developed by Bright et al based on Nielsen’s 10 heuristics. The experts also rated the overall severity of each identified heuristic violation on a scale of 0 to 4, where 0 indicates no problems and 4 indicates a usability catastrophe. Data from the experts’ coded comments were synthesized, and the severity of each identified usability heuristic was analyzed. ResultsThe 6 HCI experts included professionals from the fields of nursing (n=4), pharmaceutical science (n=1), and systems engineering (n=1). The mean overall severity scores of the identified heuristic violations ranged from 0.66 (flexibility and efficiency of use) to 2.00 (user control and freedom and error prevention), in which scores closer to 0 indicate a more usable system. The heuristic principle user control and freedom was identified as the most in need of refinement and, particularly by nonnursing HCI experts, considered as having major usability problems. In response to the heuristic match between system and the real world, the experts pointed to the reversed direction of our system’s pain scale scores (1=severe pain) compared to those commonly used in clinical practice (typically 1=mild pain); although this was identified as a minor usability problem, its refinement was repeatedly emphasized by nursing HCI experts. ConclusionsOur heuristic evaluation process is simple and systematic and can be used at multiple stages of system development to reduce the time and cost needed to establish the usability of a system before its widespread implementation. Furthermore, heuristic evaluations can help organizations develop transparent reporting protocols for usability, as required by Title IV of the 21st Century Cures Act. Testing of EHRs and CDSSs by clinicians with HCI expertise in heuristic evaluation processes has the potential to reduce the frequency of testing while increasing its quality, which may reduce clinicians’ cognitive workload and errors and enhance the adoption of EHRs and CDSSs.