Information Needs Assessment for a Medicine Ward-Focused Rounding Dashboard

Information and Data Visualization Needs among Direct Care Nurses in the Intensive Care Unit

OBJECTIVES

Intensive care unit (ICU) direct care nurses spend 22% of their shift completing tasks within the electronic health record (EHR). Miscommunications and inefficiencies occur, particularly during patient hand-off, placing patient safety at risk. Redesigning how direct care nurses visualize and interact with patient information during hand-off is one opportunity to improve EHR use. A web-based survey was deployed to better understand the information and visualization needs at patient hand-off to inform redesign.

METHODS

A multicenter anonymous web-based survey of direct care ICU nurses was conducted (9-12/2021). Semi-structured interviews with stakeholders informed survey development. The primary outcome was identifying primary EHR data needs at patient hand-off for inclusion in future EHR visualization and interface development. Secondary outcomes included current use of the EHR at patient hand-off, EHR satisfaction, and visualization preferences. Frequencies, means, and medians were calculated for each data item then ranked in descending order to generate proportional quarters using SAS v9.4.

RESULTS

In total, 107 direct care ICU nurses completed the survey. The majority (46%, n = 49/107) use the EHR at patient hand-off to verify exchanged verbal information. Sixty-four percent (n = 68/107) indicated that current EHR visualization was insufficient. At the start of an ICU shift, primary EHR data needs included hemodynamics (mean 4.89 ± 0.37, 98%, n = 105), continuous IV medications (4.55 ± 0.73, 93%, n = 99), laboratory results (4.60 ± 0.56, 96%, n = 103), mechanical circulatory support devices (4.62 ± 0.72, 90%, n = 97), code status (4.40 ± 0.85, 59%, n = 108), and ventilation status (4.35 + 0.79, 51%, n = 108). Secondary outcomes included mean EHR satisfaction of 65 (0-100 scale, standard deviation = ± 21) and preferred future EHR user-interfaces to be organized by organ system (53%, n = 57/107) and visualized by tasks/schedule (61%, n = 65/107).

CONCLUSION

We identified information and visualization needs of direct care ICU nurses. The study findings could serve as a baseline toward redesigning an EHR interface.

Impact of EHR-based rounding tools on interactive communication: A prospective observational study

OBJECTIVE

Structured rounding tools have shown to improve the overall efficiency and perceived satisfaction with the rounding process. However, little is known about how EHR-integrated rounding tools impact the content, structure and interactivity of communication during rounds.

METHOD

We conducted a prospective pre-post evaluation with two rounding tools: a Microsoft Word-based fillable rounding tool (usual tool), and an EHR-integrated rounding report tool (RRT). 27 clinicians across two teams participated in rounds for 169 patients (n_usual=84, n_RRT=85). We audio-recorded and coded communication during rounds using conversational analysis methods. Using the coded communication interactions, we investigated differences between the two tools on: clinical content discussed, questions raised, and breakdowns in interactive communication. Additionally, we gathered clinician perspectives on the rounding tools through follow-up interviews.

RESULTS

We found that the use of RRT was associated with significantly more discussion of patient identifiers (e.g., name), and action items (e.g., to-do list) and significantly less discussion of imaging (e.g., X-rays) than the usual tool. RRT was also associated with fewer questions (t = 3.1, p = 0.03), and correspondingly, fewer responses (t = 3.2, p = 0.02). Communication breakdowns related to incorrect responses was fewer during the use of RRT (t = 0.5, p = 0.01). There were no statistically significant differences in the time spent for rounding between the two tools.

CONCLUSIONS

Our findings showed that RRT impacted rounding workflow: during pre-rounding, by saving time and effort in gathering information from multiple sources; during rounding, by streamlining content of the conversations using the structured RRT template; and during post-rounding, by supporting explicit discussion of patient tasks and action items for patient care planning and management.

Demonstration of a Fair Level of Agreement Between Escalation Scores Reported by Hospital Managers and Analysis of Stress-Related Hospital Metrics

BACKGROUND

The National Health System in Wales has developed a novel national electronic dashboard which reports a daily "escalation score," reflecting management's opinion of the pressure each hospital is facing, primarily due to unscheduled care. The aim of this study was to examine the possibility of replacing human scores with a quantitative model, based on the relationship between reported escalation scores and selected hospital metrics.

METHODS

Generalized linear mixed models were used to model the association between hospital metrics and escalation scores between October one year and October the next year utilizing hospital bed occupancy rate, ambulance hours lost waiting outside emergency departments, number of "boarded out" patients in the hospital, and the daily ratio of admissions to discharges in the hospital. These models were tested against a subsequent period (December unto May the following year), using three models: "general," "hospital-specific," and "group-specific." The model generated by the initial time frame was tested against data from the subsequent time frame using weighted κ.

RESULTS

Across 16 hospitals, using 3343 escalation scores, the rates of agreement and weighted κ were: general model (48.8%; 0.16), hospital-specific model (45.0%; 0.25), and group-specific model (43.1%; 0.25). A 17th small hospital was excluded due to missing data.

CONCLUSIONS

This is novel research as no similar studies were identified, although the topic is important as it addresses a major current health-care challenge. Automated scores can be derived which have the advantage of being derived objectively, avoiding human inter- and intraindividual variation. Prospective testing is recommended to assess potential service planning benefit.