Developing an emergency department crowding dashboard: A design science approach

The Effects of Layout Order on Interface Complexity: An Eye-Tracking Study for Dashboard Design

This study investigated the effect of layout order on the complexity of the dashboard interface based on screen-based eye trackers. By simplifying and abstracting dashboard interfaces and incorporating subjective ratings (symmetry and unity calculations), we successfully manipulated the levels of complexity and layout order of the interface materials. Using four types of eye movement data (total fixation count, total gaze duration, scanning paths, and hotspot maps) and behavioral data, we compared participants' visual search behavior on interfaces with different layout orders and complexity levels. Experiment 1 revealed a significant interaction between layout order and interface complexity, with participants performing significantly better in the high-level layout order condition. Experiment 2 confirmed that the position of the core chart plays a crucial role in users' visual search behavior and that the optimal layout order for the dashboard is to place the core chart on the left side of the interface's horizontal axis, with partial symmetry in the no-core chart areas. This study highlights the effectiveness of eye-tracking techniques in user interface design research and provides valuable insights into optimizing dashboard interface design. Designers should adopt the design principle of "order is more" in addition to "less is more" and consider designing the core chart in the left-center position.

Main Features and Control Strategies to Reduce Overcrowding in Emergency Departments: A Systematic Review of the Literature

Purpose

Overcrowding is a problem that affects emergency departments (ED) all over the world; it occurs due to a disproportion between user demand and the physical, human and structural resources available. Essential prerequisites to assessing and managing the phenomenon are its accurate measurement and an understanding of its impact. The objective of this systematic review is to identify the characteristics of the problem, analyzing the proposed strategies aimed at improving patient flow, delay in services provided and overcrowding of emergency departments.

Methods

To achieve our objectives, a manual computerized search was performed in the bibliographic databases using as keywords "Emergency Department", "Overcrowding", "Emergency Room", "Emergency Service", "Emergency Unit"",Emergency Ward", "Emergency Outpatient Unit", "Emergency Hospital", "Crowding", "Mass Gathering", "Management" and "Comprehensive Health Care". Two independent reviewers analyzed abstracts, titles and full text articles for admissibility, according to the selected inclusion and exclusion criteria.

Results

The process lead to include 19 articles. It was possible to group the solutions proposed in five categories: work organization, investment in primary care, creation of new dedicated professional figures, work and structural modifications and implementation of predictive simulation models using mathematical algorithms.

Conclusion

The most effective measures to guarantee an improvement in the flow of patients are represented by both improving the efficiency of human resources and by developing predictive mathematical models, regardless of the type of hospital and its location. Considering the complexity of EDs and the multiple characteristics of overcrowding and that the causes of crowding are different and site-specific, a careful examination of the specifics of each ED is necessary to identify improving fields.

Requirements and challenges of hospital dashboards: a systematic literature review

Background

Today, the use of data in administrative and clinical processes is quite challenging due to the large volume of data, data collection from various sources, and lack of data structure. As a data management tool, dashboards play an important role in timely visual display of critical information on key performances.

Objectives

This systematic review aimed to identify functional and non-functional requirements, as well as challenges of using dashboards in hospitals.

Methods

In this systematic review, four databases, including the Web of Science, PubMed, EMBASE, and Scopus, were searched to find relevant articles from 2000 until May 30, 2020. The final search was conducted on May 30, 2020. Data collection was performed using a data extraction form and reviewing the content of relevant studies on the potentials and challenges of dashboard implementation.

Results

Fifty-four out of 1254 retrieved articles were selected for this study based on the inclusion and exclusion criteria. The functional requirements for dashboards included reporting, reminders, customization, tracking, alert creation, and assessment of performance indicators. On the other hand, the non-functional requirements included the dashboard speed, security, ease of use, installation on different devices (e.g., PCs and laptops), integration with other systems, web-based design, inclusion of a data warehouse, being up-to-data, and use of data visualization elements based on the user’s needs. Moreover, the identified challenges were categorized into four groups: data sources, dashboard content, dashboard design, implementation, and integration in other systems at the hospital level.

Conclusion

Dashboards, by providing information in an appropriate manner, can lead to the proper use of information by users. In order for a dashboard to be effective in clinical and managerial processes, particular attention must be paid to its capabilities, and the challenges of its implementation need to be addressed.

Development of a low-dimensional model to predict admissions from triage at a pediatric emergency department

Objectives

This study aims to develop and internally validate a low-dimensional model to predict outcomes (admission or discharge) using commonly entered data up to the post-triage process to improve patient flow in the pediatric emergency department (ED). In hospital settings where electronic data are limited, a low-dimensional model with fewer variables may be easier to implement.

Methods

This prognostic study included ED attendances in 2017 and 2018. The Cross Industry Standard Process for Data Mining methodology was followed. Eligibility criteria was applied to the data set, splitting into 70% train and 30% test. Sampling techniques were compared. Gradient boosting machine (GBM), logistic regression, and naïve Bayes models were created. Variables of importance were obtained from the model with the highest area under the curve (AUC) and used to create a low-dimensional model.

Results

Eligible attendances totaled 72,229 (15% admission rate). The AUC was 0.853 (95% confidence interval [CI], 0.846-0.859) for GBM, 0.845 (95% CI, 0.838-0.852) for logistic regression and 0.813 (95% CI, 0.806-0.821) for naïve Bayes. Important predictors in the GBM model used to create a low-dimensional model were presenting complaint, triage category, referral source, registration month, location type (resuscitation/other), distance traveled, admission history, and weekday (AUC 0.835 [95% CI, 0.829-0.842]).

Conclusions

Admission and discharge probability can be predicted early in a pediatric ED using 8 variables. Future work could analyze the false positives and false negatives to gain an understanding of the implementation of these predictions.

Emergency Department Quality Dashboard; a Systematic Review of Performance Indicators, Functionalities, and Challenges

Introduction:

Effective information management in the emergency department (ED) can improve the control and management of ED processes. Dashboards, known as data management tools, efficiently provide information and contribute greatly to control and management of ED. This study aimed to identify performance indicators quality dashboard functionalities, and analyze the challenges associated with dashboard implementation in the ED.

Methods:

This systematic review began with a search in four databases (Web of Science, PubMed, Embase, and Scopus) from 2000 to May 30, 2020, when the final search for papers was conducted. The data were collected using a data extraction form and the contents of the extracted papers were analyzed through ED performance indicators, dashboard functionalities, and implementation challenges.

Results:

Performance indicators reported in the reviewed papers were classified as the quality of care, patient flow, timeliness, costs, and resources. The main dashboard functionalities noted in the papers included reporting, customization, alert creation, resource management, and real-time information display. The dashboard implementation challenges included data sources, data quality, integration with other systems, adaptability of dashboard functionalities to user needs, and selection of appropriate performance indicators.

Conclusions:

Quality dashboards facilitate processes, communication, and situation awareness in the ED; hence, they can improve care provision in this department. To enhance the effectiveness and efficiency of ED dashboards, officials should set performance indicators and consider the conformity of dashboard functionalities with user needs. They should also integrate dashboards with other relevant systems at the departmental and hospital levels.

Development, implementation and preliminary evaluation of clinical dashboards in a department of anesthesia

Clinical dashboards summarize indicators of high-volume patient data in a concise, user-friendly visual format. There are few studies of the use of dashboards to improve professional practice in anesthesiology. The objective of the present study was to describe the user-centered development, implementation and preliminary evaluation of clinical dashboards dealing with anesthesia unit management and quality assessment in a French university medical center. User needs and technical requirements were identified in end user interviews and then synthesized. Several representations were then developed (according to good visualization practice) and submitted to end users for appraisal. Lastly, dashboards were implemented and made accessible for everyday use via the medical center’s network. After a period of use, end user feedback on the dashboard platform was collected as a system usability score (range 0 to 100). Seventeen themes (corresponding to 29 questions and 42 indicators) were identified. After prioritization and feasibility assessment, 10 dashboards were ultimately implemented and deployed. The dashboards variously addressed the unit’s overall activity, compliance with guidelines on intraoperative hemodynamics, ventilation and monitoring, and documentation of the anesthesia procedure. The mean (standard deviation) system usability score was 82.6 (11.5), which corresponded to excellent usability. We developed clinical dashboards for a university medical center’s anesthesia units. The dashboards’ deployment was well received by the center’s anesthesiologists. The dashboards’ impact on activity and practice after several months of use will now have to be assessed.

Improving Health Care Management in Hospitals Through a Productivity Dashboard

Health information systems have been developed to help hospital managers steer daily operations, including key performance indicators (KPIs) for monitoring on a time-aggregated basis. Yet, current literature lacks in proposals of productivity dashboards to assist hospitals stakeholders. This research focuses on two related problems: (1) hospital organizations need access to productivity information to improve access to services; and (2) managers need productivity information to optimize resource allocation. This research consists in the development of dashboards to monitor information obtained from a hospital organization to support decision makers. To develop and evaluate the productivity dashboard, the Design Science Research (DSR) methodology was adopted. The dashboard was evaluated by stakeholders of a large Portuguese hospital who contributed to iteratively improving its design toward a useful decision support tool. Additionally, it was ascertained that monitoring productivity needs more study and that the dashboards on these themes are valuable assets at a monitoring level and subsequent decision-making process.

Challenges, consequences, and lessons for way-outs to emergencies at hospitals: a systematic review study

Background

Emergency Department (ED) overcrowding adversely affects patients’ health, accessibility, and quality of healthcare systems for communities. Several studies have addressed this issue. This study aimed to conduct a systematic review study concerning challenges, lessons and way outs of clinical emergencies at hospitals.

Methods

Original research articles on crowding of emergencies at hospitals published from 1st January 2007, and 1st August 2018 were utilized. Relevant studies from the PubMed and EMBASE databases were assessed using suitable keywords. Two reviewers independently screened the titles, abstracts and the methodological validity of the records using data extraction format before their inclusion in the final review. Discussions with the senior faculty member were used to resolve any disagreements among the reviewers during the assessment phase.

Results

Out of the total 117 articles in the final record, we excluded 11 of them because of poor quality. Thus, this systematic review synthesized the reports of 106 original articles. Overall 14, 55 and 29 of the reviewed refer to causes, effects, and solutions of ED crowding, respectively. The review also included four articles on both causes and effects and another four on causes and solutions. Multiple individual patients and healthcare system related challenges, experiences and responses to crowding and its consequences are comprehensively synthesized.

Conclusion

ED overcrowding is a multi-facet issue which affects by patient-related factors and emergency service delivery. Crowding of the EDs adversely affected individual patients, healthcare delivery systems and communities. The identified issues concern organizational managers, leadership, and operational level actions to reduce crowding and improve emergency healthcare outcomes efficiently.

Near-simultaneous intensive care unit (ICU) admissions and all-cause mortality: a cohort study

PURPOSE

Prior studies have reported the adverse effects of strain on patient outcomes. There is a paucity of literature about a type of strain that may be caused by near-simultaneous intensive care unit (ICU) admissions. We hypothesized that when multiple admissions arrive nearly at the same time, the ICU teams are excessively strained, and this leads to unfavorable patient outcomes.

METHODS

This is a retrospective cohort study of consecutive adult patients admitted to an academic medical ICU of a tertiary referral center over five consecutive years. Primary outcomes were the all-cause hospital and ICU mortality.

RESULTS

We enrolled 13,234 consecutive ICU admissions during the study period. One-fourth of the admissions had an elapsed time since the last admission (ETLA) of < 55 min. Near-simultaneous admissions (NSA) had on average, a higher unadjusted odds ratio (OR) of ICU death of 1.16 (95% CI 1-1.35, P = 0.05), adjusted 1.23 (95% CI 1.04-1.44, P = 0.01), unadjusted hospital death of 1.11 (95% CI 0.99-1.24, P = 0.06), adjusted 1.20 (95% 1.05-1.35, P = 0.004), and a lower adjusted OR of home discharge of 0.91 (95% CI 0.84-0.99, P = 0.04). NSA was associated with 0.16 (95% CI 0.04-0.29, P = 0.01) added days in the ICU. For each incremental unit increase of the logarithmic transformation of ETLA [log (ETLA in minutes)], the average adjusted hospital mortality OR incrementally decreased by an added average OR of 0.93 (95% CI 0.89‒0.97, P = 0.001).

CONCLUSION

Our results suggest that near-simultaneous ICU admissions (NSA) are frequent and are associated with a dose-dependent effect on mortality, length of stay, and odds of home versus nursing facility discharge.