From an Informatics Lens: Dashboards for Hospital Nurse Managers Influencing Unit Patient Outcomes

Dashboards display hospital quality and patient safety measures aimed to improve patient outcomes. Although literature establishes dashboards aid quality and performance improvement initiatives, research is limited from the frontline nurse manager's perspective. This study characterizes factors influencing hospital nurse managers' use of dashboards for unit-level quality and performance improvement with suggestions for dashboard design. Using a descriptive qualitative design, semistructured interviews were conducted with 11 hospital nurse managers from a health system in the Midwestern United States. Thematic analysis was used to describe four perceived factors influencing dashboard use: external, data, technology features, and personal. External factors included regulatory standards, professional standards of care, organizational expectations, and organizational resources. Data factors included dashboard data quality and usefulness. Technology features included preference for simple, interactive, and customizable visual displays. Personal factors included inherent nurse manager qualities and knowledge. Guidelines for dashboard design involve display of required relevant quality measures that are accurate, timely, useful, and usable. Future research should involve hospital nurse managers in user-centered design to ensure dashboards are favorable for use. Further, opportunities exist for nurse manager informatics training and education on dashboard use in preparation for their role and responsibilities in unit-level quality and performance improvement.

Perceptions of Cognitive Load and Workload in Nurse Handoffs: A Comparative Study Across Differing Patient-Nurse Ratios and Acuity Levels

Medical errors, often resulting from miscommunication and cognitive lapses during handoffs, account for numerous preventable deaths and patient harm annually. This research examined nurses' perceived workload and cognitive load during handoffs on hospital units with varying patient acuity levels and patient-nurse ratios. Conducted at a southeastern US medical facility, the study analyzed 20 handoff dyads using the National Aeronautics and Space Administration Task Load Index to measure perceived workload and cognitive load. Linear regressions revealed significant associations between patient acuity levels, patient-nurse ratios, and National Aeronautics and Space Administration Task Load Index subscales, specifically mental demand (P = .007) and performance (P = .008). Fisher exact test and Wilcoxon rank sum test showed no significant associations between these factors and nurses' roles (P > .05). The findings highlight the need for targeted interventions to manage workload and cognitive load, emphasizing standardized handoff protocols and technological aids. The study underscores the variability in perceived workload and cognitive load among nurses across different units. Medical-surgical units showed higher cognitive load, indicating the need for improved workload management strategies. Despite limitations, including the single-center design and small sample size, the study provides valuable insights for enhancing handoff communications and reducing medical errors.

Clinical Knowledge Model for the Prevention of Healthcare-Associated Venous Thromboembolism

Knowledge models inform organizational behavior through the logical association of documentation processes, definitions, data elements, and value sets. The development of a well-designed knowledge model allows for the reuse of electronic health record data to promote efficiency in practice, data interoperability, and the extensibility of data to new capabilities or functionality such as clinical decision support, quality improvement, and research. The purpose of this article is to describe the development and validation of a knowledge model for healthcare-associated venous thromboembolism prevention. The team used FloMap, an Internet-based survey resource, to compare metadata from six healthcare organizations to an initial draft model. The team used consensus decision-making over time to compare survey results. The resulting model included seven panels, 41 questions, and 231 values. A second validation step included completion of an Internet-based survey with 26 staff nurse respondents representing 15 healthcare organizations, two electronic health record vendors, and one academic institution. The final knowledge model contained nine Logical Observation Identifiers Names and Codes panels, 32 concepts, and 195 values representing an additional six panels (groupings), 15 concepts (questions), and the specification of 195 values (answers). The final model is useful for consistent documentation to demonstrate the contribution of nursing practice to the prevention of venous thromboembolism.