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Park S, Yoo J, Lee Y, DeGuzman PB, Kang MJ, Dykes PC, Shin SY, Cha WC. Quantifying emergency department nursing workload at the task level using NASA-TLX: An exploratory descriptive study. Int Emerg Nurs 2024; 74:101424. [PMID: 38531213 DOI: 10.1016/j.ienj.2024.101424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 01/20/2024] [Accepted: 02/14/2024] [Indexed: 03/28/2024]
Abstract
BACKGROUND Emergency departments (ED) nurses experience high mental workloads because of unpredictable work environments; however, research evaluating ED nursing workload using a tool incorporating nurses' perception is lacking. Quantify ED nursing subjective workload and explore the impact of work experience on perceived workload. METHODS Thirty-two ED nurses at a tertiary academic hospital in the Republic of Korea were surveyed to assess their subjective workload for ED procedures using the National Aeronautics and Space Administration Task Load Index (NASA-TLX). Nonparametric statistical analysis was performed to describe the data, and linear regression analysis was conducted to estimate the impact of work experience on perceived workload. RESULTS Cardiopulmonary resuscitation (CPR) had the highest median workload, followed by interruption from a patient and their family members. Although inexperienced nurses perceived the 'special care' procedures (CPR and defibrillation) as more challenging compared with other categories, analysis revealed that nurses with more than 107 months of experience reported a significantly higher workload than those with less than 36 months of experience. CONCLUSION Addressing interruptions and customizing training can alleviate ED nursing workload. Quantified perceived workload is useful for identifying acceptable thresholds to maintain optimal workload, which ultimately contributes to predicting nursing staffing needs and ED crowding.
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Affiliation(s)
- Sookyung Park
- School of Nursing, University of Virginia, 225 Jeanette Lancaster Way, Charlottesville, VA 22903-3388, USA
| | - Junsang Yoo
- Department of Digital Health, Samsung Advanced Institute for Health Science & Technology (SAIHST), Sungkyunkwan University, 115 Irwon-ro Gangnam-gu, Seoul 06355, Republic of Korea
| | - Yerim Lee
- Department of Digital Health, Samsung Advanced Institute for Health Science & Technology (SAIHST), Sungkyunkwan University, 115 Irwon-ro Gangnam-gu, Seoul 06355, Republic of Korea
| | - Pamela Baker DeGuzman
- School of Nursing, University of Virginia, 225 Jeanette Lancaster Way, Charlottesville, VA 22903-3388, USA
| | - Min-Jeoung Kang
- Harvard Medical School, 25 Shattuck Street, Boston MA 02115, MA, USA; Department of Medicine, Division of General Internal Medicine and Primay Care, Brigham and Women's Hospital, 1620 Tremont Street, MA, USA
| | - Patricia C Dykes
- Harvard Medical School, 25 Shattuck Street, Boston MA 02115, MA, USA; Department of Medicine, Division of General Internal Medicine and Primay Care, Brigham and Women's Hospital, 1620 Tremont Street, MA, USA
| | - So Yeon Shin
- Department of Nursing, Samsung Medical Center, 81 Irwon-ro Gangnam-gu, Seoul 06351, Republic of Korea
| | - Won Chul Cha
- Department of Digital Health, Samsung Advanced Institute for Health Science & Technology (SAIHST), Sungkyunkwan University, 115 Irwon-ro Gangnam-gu, Seoul 06355, Republic of Korea; Department of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 115 Irwon-ro Gangnam-gu, Seoul 06355, Republic of Korea; Digital Innovation Center, Samsung Medical Center, 81 Irwon-ro Gangnam-gu, Seoul 06351, Republic of Korea.
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2
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Usability Evaluation of Dashboards: A Systematic Literature Review of Tools. BIOMED RESEARCH INTERNATIONAL 2023; 2023:9990933. [PMID: 36874923 PMCID: PMC9977530 DOI: 10.1155/2023/9990933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/01/2023] [Revised: 01/16/2023] [Accepted: 02/04/2023] [Indexed: 02/25/2023]
Abstract
Introduction In recent years, the use of dashboards in healthcare has been considered an effective approach for the visual presentation of information to support clinical and administrative decisions. Effective and efficient use of dashboards in clinical and managerial processes requires a framework for the design and development of tools based on usability principles. Objectives The present study is aimed at investigating the existing questionnaires used for the usability evaluation framework of dashboards and at presenting more specific usability criteria for evaluating dashboards. Methods This systematic review was conducted using PubMed, Web of Science, and Scopus, without any time restrictions. The final search of articles was performed on September 2, 2022. Data collection was performed using a data extraction form, and the content of selected studies was analyzed based on the dashboard usability criteria. Results After reviewing the full text of relevant articles, a total of 29 studies were selected according to the inclusion criteria. Regarding the questionnaires used in the selected studies, researcher-made questionnaires were used in five studies, while 25 studies applied previously used questionnaires. The most widely used questionnaires were the System Usability Scale (SUS), Technology Acceptance Model (TAM), Situation Awareness Rating Technique (SART), Questionnaire for User Interaction Satisfaction (QUIS), Unified Theory of Acceptance and Use of Technology (UTAUT), and Health Information Technology Usability Evaluation Scale (Health-ITUES), respectively. Finally, dashboard evaluation criteria, including usefulness, operability, learnability, ease of use, suitability for tasks, improvement of situational awareness, satisfaction, user interface, content, and system capabilities, were suggested. Conclusion General questionnaires that were not specifically designed for dashboard evaluation were mainly used in reviewed studies. The current study suggested specific criteria for measuring the usability of dashboards. When selecting the usability evaluation criteria for dashboards, it is important to pay attention to the evaluation objectives, dashboard features and capabilities, and context of use.
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Østervang C, Lassen A, Schmidt T, Coyne E, Dieperink KB, Jensen CM. Development of a health information system to promote emergency care pathways: A participatory design study. Digit Health 2022; 8:20552076221145856. [PMID: 36601282 PMCID: PMC9806496 DOI: 10.1177/20552076221145856] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 11/30/2022] [Indexed: 12/28/2022] Open
Abstract
Objective The successful development and implementation of sustainable healthcare technologies require an understanding of the clinical setting and its potential challenges from a user perspective. Previous studies have uncovered a gap between what emergency departments deliver and the needs and preferences of patients and family members. This study investigated whether a user-driven approach and participatory design could provide a technical solution to bridge the identified gap. Methods We conducted four workshops, and five one-to-one workshops with patients, family members, healthcare professionals, and information technology specialists to codesign a prototype. Revisions of the prototype were made until an acceptable solution was agreed upon and tested by the participants. The data were analyzed following iterative processes (plan → act → observe → reflect). Results The participants emphasized the importance of a person-centered approach focusing on improved information. An already implemented system for clinicians' use only was redesigned into a unique patient module that provides a process line displaying continually updated informative features, including (1) person-centered activities, (2) general information videos, (3) a notepad, (4) estimated waiting time, and (5) the nurse and physician responsible for care and treatment. Conclusion Participatory design is a usable approach to designing an information system for use in the emergency department. The process yielded insight into the complexity of translating ideas into technologies that can actually be implemented in clinical practice, and the user perspectives revealed the key to identifying these complex aspects. The iterations with the participants enabled us to redesign an existing technology.
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Affiliation(s)
- Christina Østervang
- Department of Emergency Medicine, Odense University
Hospital, Odense, Denmark,Department of Clinical Research, University of Southern
Denmark, Odense, Denmark,Christina Østervang, Department of
Emergency Medicine, Odense University Hospital, Odense, Denmark; Department of
Clinical Research, University of Southern Denmark, Fælles Akutmodtagelse, Odense
University Hospital, Kløvervænget 25 DK-5000, Odense, Denmark.
| | - Annmarie Lassen
- Department of Emergency Medicine, Odense University
Hospital, Odense, Denmark,Department of Clinical Research, University of Southern
Denmark, Odense, Denmark
| | - Thomas Schmidt
- Center for Health Informatics and Technology,
University of
Southern Denmark, Odense, Denmark
| | - Elisabeth Coyne
- Department of Clinical Research, University of Southern
Denmark, Odense, Denmark,School of Nursing and Midwifery, Griffith
University, Brisbane, Australia
| | - Karin Brochstedt Dieperink
- Department of Clinical Research, University of Southern
Denmark, Odense, Denmark,Department of Oncology, Odense University
Hospital, Odense, Denmark,Family-Focused Healthcare Research Centre (FaCe),
University of
Southern Denmark, Odense, Denmark
| | - Charlotte Myhre Jensen
- Department of Clinical Research, University of Southern
Denmark, Odense, Denmark,Department of Orthopedic Surgery and Traumatology,
Odense
University hospital, Odense, Denmark
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4
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ALqurashi MM, Al Thobaity A, Alzahrani F, Alasmari HA. Nurses’ Experiences with an Electronic Tracking System in the Emergency Department: A Qualitative Study. NURSING: RESEARCH AND REVIEWS 2022. [DOI: 10.2147/nrr.s384136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
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5
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Rabiei R, Almasi S. Requirements and challenges of hospital dashboards: a systematic literature review. BMC Med Inform Decis Mak 2022; 22:287. [DOI: 10.1186/s12911-022-02037-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 11/01/2022] [Indexed: 11/09/2022] Open
Abstract
Abstract
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.
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Design and Implementation of a Comprehensive AI Dashboard for Real-Time Prediction of Adverse Prognosis of ED Patients. Healthcare (Basel) 2022; 10:healthcare10081498. [PMID: 36011155 PMCID: PMC9408009 DOI: 10.3390/healthcare10081498] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 08/02/2022] [Accepted: 08/03/2022] [Indexed: 11/16/2022] Open
Abstract
The emergency department (ED) is at the forefront of medical care, and the medical team needs to make outright judgments and treatment decisions under time constraints. Thus, knowing how to make personalized and precise predictions is a very challenging task. With the advancement of artificial intelligence (AI) technology, Chi Mei Medical Center (CMMC) adopted AI, the Internet of Things (IoT), and interaction technologies to establish diverse prognosis prediction models for eight diseases based on the ED electronic medical records of three branch hospitals. CMMC integrated these predictive models to form a digital AI dashboard, showing the risk status of all ED patients diagnosed with any of these eight diseases. This study first explored the methodology of CMMC’s AI development and proposed a four-tier AI dashboard architecture for ED implementation. The AI dashboard’s ease of use, usefulness, and acceptance was also strongly affirmed by the ED medical staff. The ED AI dashboard is an effective tool in the implementation of real-time risk monitoring of patients in the ED and could improve the quality of care as a part of best practice. Based on the results of this study, it is suggested that healthcare institutions thoughtfully consider tailoring their ED dashboard designs to adapt to their unique workflows and environments.
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7
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Leonard F, Gilligan J, Barrett MJ. Development of a low‐dimensional model to predict admissions from triage at a pediatric emergency department. J Am Coll Emerg Physicians Open 2022; 3:e12779. [PMID: 35859857 PMCID: PMC9286530 DOI: 10.1002/emp2.12779] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 05/24/2022] [Accepted: 06/17/2022] [Indexed: 11/26/2022] Open
Abstract
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.
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Affiliation(s)
- Fiona Leonard
- Business Intelligence Unit Children's Health Ireland at Crumlin Dublin Ireland
| | - John Gilligan
- School of Computer Science Technological University Dublin Dublin Ireland
| | - Michael J. Barrett
- Department of Paediatric Emergency Medicine Children's Health Ireland at Crumlin Dublin Ireland
- Women's and Children's Health School of Medicine University College Dublin Dublin Ireland
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8
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Lim HC, Austin JA, van der Vegt AH, Rahimi AK, Canfell OJ, Mifsud J, Pole JD, Barras MA, Hodgson T, Shrapnel S, Sullivan CM. Toward a Learning Health Care System: A Systematic Review and Evidence-Based Conceptual Framework for Implementation of Clinical Analytics in a Digital Hospital. Appl Clin Inform 2022; 13:339-354. [PMID: 35388447 PMCID: PMC8986462 DOI: 10.1055/s-0042-1743243] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Abstract
Objective
A learning health care system (LHS) uses routinely collected data to continuously monitor and improve health care outcomes. Little is reported on the challenges and methods used to implement the analytics underpinning an LHS. Our aim was to systematically review the literature for reports of real-time clinical analytics implementation in digital hospitals and to use these findings to synthesize a conceptual framework for LHS implementation.
Methods
Embase, PubMed, and Web of Science databases were searched for clinical analytics derived from electronic health records in adult inpatient and emergency department settings between 2015 and 2021. Evidence was coded from the final study selection that related to (1) dashboard implementation challenges, (2) methods to overcome implementation challenges, and (3) dashboard assessment and impact. The evidences obtained, together with evidence extracted from relevant prior reviews, were mapped to an existing digital health transformation model to derive a conceptual framework for LHS analytics implementation.
Results
A total of 238 candidate articles were reviewed and 14 met inclusion criteria. From the selected studies, we extracted 37 implementation challenges and 64 methods employed to overcome such challenges. We identified common approaches for evaluating the implementation of clinical dashboards. Six studies assessed clinical process outcomes and only four studies evaluated patient health outcomes. A conceptual framework for implementing the analytics of an LHS was developed.
Conclusion
Health care organizations face diverse challenges when trying to implement real-time data analytics. These challenges have shifted over the past decade. While prior reviews identified fundamental information problems, such as data size and complexity, our review uncovered more postpilot challenges, such as supporting diverse users, workflows, and user-interface screens. Our review identified practical methods to overcome these challenges which have been incorporated into a conceptual framework. It is hoped this framework will support health care organizations deploying near-real-time clinical dashboards and progress toward an LHS.
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Affiliation(s)
- Han Chang Lim
- Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Herston, Brisbane, Australia.,Department of Health, eHealth Queensland, Queensland Government, Brisbane, Australia
| | - Jodie A Austin
- Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Herston, Brisbane, Australia.,Department of Health, eHealth Queensland, Queensland Government, Brisbane, Australia
| | - Anton H van der Vegt
- Information Engineering Lab, School of Information Technology and Electrical Engineering, The University of Queensland, St Lucia, Brisbane, Australia
| | - Amir Kamel Rahimi
- Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Herston, Brisbane, Australia.,Digital Health Cooperative Research Centre, Australian Government, Sydney, New South Wales, Australia
| | - Oliver J Canfell
- Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Herston, Brisbane, Australia.,Digital Health Cooperative Research Centre, Australian Government, Sydney, New South Wales, Australia.,UQ Business School, Faculty of Business, Economics and Law, The University of Queensland, St. Lucia, Brisbane, Australia
| | - Jayden Mifsud
- Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Herston, Brisbane, Australia
| | - Jason D Pole
- Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Herston, Brisbane, Australia
| | - Michael A Barras
- School of Pharmacy, Faculty of Health and Behavioural Sciences, The University of Queensland, PACE Precinct, Woolloongabba, Brisbane, Australia.,Pharmacy Department, Princess Alexandra Hospital, Woolloongabba, Brisbane, Australia
| | - Tobias Hodgson
- UQ Business School, Faculty of Business, Economics and Law, The University of Queensland, St. Lucia, Brisbane, Australia
| | - Sally Shrapnel
- Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Herston, Brisbane, Australia.,School of Mathematics and Physics, Faculty of Science, The University of Queensland, St Lucia, Brisbane, Australia
| | - Clair M Sullivan
- Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Herston, Brisbane, Australia.,Department of Health, Metro North Hospital and Health Service, Queensland Government, Herston QLD, Australia
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Zhuang M, Concannon D, Manley E. A Framework for Evaluating Dashboards in Healthcare. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2022; 28:1715-1731. [PMID: 35213306 DOI: 10.1109/tvcg.2022.3147154] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
In the era of 'information overload', effective information provision is essential for enabling rapid response and critical decision making. In making sense of diverse information sources, dashboards have become an indispensable tool, providing fast, effective, adaptable, and personalized access to information for professionals and the general public alike. However, these objectives place heavy requirements on dashboards as information systems in usability and effective design. Understanding these issues is challenging given the absence of consistent and comprehensive approaches to dashboard evaluation. In this article we systematically review literature on dashboard implementation in healthcare, where dashboards have been employed widely, and where there is widespread interest for improving the current state of the art, and subsequently analyse approaches taken towards evaluation. We draw upon consolidated dashboard literature and our own observations to introduce a general definition of dashboards which is more relevant to current trends, together with seven evaluation scenarios - task performance, behaviour change, interaction workflow, perceived engagement, potential utility, algorithm performance and system implementation. These scenarios distinguish different evaluation purposes which we illustrate through measurements, example studies, and common challenges in evaluation study design. We provide a breakdown of each evaluation scenario, and highlight some of the more subtle questions. We demonstrate the use of the proposed framework by a design study guided by this framework. We conclude by comparing this framework with existing literature, outlining a number of active discussion points and a set of dashboard evaluation best practices for the academic, clinical and software development communities alike.
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10
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Strauss AT, Morgan C, El Khuri C, Slogeris B, Smith AG, Klein E, Toerper M, DeAngelo A, Debraine A, Peterson S, Gurses AP, Levin S, Hinson J. A Patient Outcomes-Driven Feedback Platform for Emergency Medicine Clinicians: Human-Centered Design and Usability Evaluation of Linking Outcomes Of Patients (LOOP). JMIR Hum Factors 2022; 9:e30130. [PMID: 35319469 PMCID: PMC8987968 DOI: 10.2196/30130] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 07/11/2021] [Accepted: 11/11/2021] [Indexed: 02/05/2023] Open
Abstract
Background The availability of patient outcomes–based feedback is limited in episodic care environments such as the emergency department. Emergency medicine (EM) clinicians set care trajectories for a majority of hospitalized patients and provide definitive care to an even larger number of those discharged into the community. EM clinicians are often unaware of the short- and long-term health outcomes of patients and how their actions may have contributed. Despite large volumes of patients and data, outcomes-driven learning that targets individual clinician experiences is meager. Integrated electronic health record (EHR) systems provide opportunity, but they do not have readily available functionality intended for outcomes-based learning. Objective This study sought to unlock insights from routinely collected EHR data through the development of an individualizable patient outcomes feedback platform for EM clinicians. Here, we describe the iterative development of this platform, Linking Outcomes Of Patients (LOOP), under a human-centered design framework, including structured feedback obtained from its use. Methods This multimodal study consisting of human-centered design studios, surveys (24 physicians), interviews (11 physicians), and a LOOP application usability evaluation (12 EM physicians for ≥30 minutes each) was performed between August 2019 and February 2021. The study spanned 3 phases: (1) conceptual development under a human-centered design framework, (2) LOOP technical platform development, and (3) usability evaluation comparing pre- and post-LOOP feedback gathering practices in the EHR. Results An initial human-centered design studio and EM clinician surveys revealed common themes of disconnect between EM clinicians and their patients after the encounter. Fundamental postencounter outcomes of death (15/24, 63% respondents identified as useful), escalation of care (20/24, 83%), and return to ED (16/24, 67%) were determined high yield for demonstrating proof-of-concept in our LOOP application. The studio aided the design and development of LOOP, which integrated physicians throughout the design and content iteration. A final LOOP prototype enabled usability evaluation and iterative refinement prior to launch. Usability evaluation compared to status quo (ie, pre-LOOP) feedback gathering practices demonstrated a shift across all outcomes from “not easy” to “very easy” to obtain and from “not confident” to “very confident” in estimating outcomes after using LOOP. On a scale from 0 (unlikely) to 10 (most likely), the users were very likely (9.5) to recommend LOOP to a colleague. Conclusions This study demonstrates the potential for human-centered design of a patient outcomes–driven feedback platform for individual EM providers. We have outlined a framework for working alongside clinicians with a multidisciplined team to develop and test a tool that augments their clinical experience and enables closed-loop learning.
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Affiliation(s)
- Alexandra T Strauss
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Cameron Morgan
- Center for Social Design, Maryland Institute College of Art, Baltimore, MD, United States
| | - Christopher El Khuri
- Department of Emergency Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Becky Slogeris
- Center for Social Design, Maryland Institute College of Art, Baltimore, MD, United States
| | - Aria G Smith
- Department of Emergency Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Eili Klein
- Department of Emergency Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Matt Toerper
- Department of Emergency Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States.,StoCastic, Towson, MD, United States
| | | | | | - Susan Peterson
- Department of Emergency Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Ayse P Gurses
- Department of Emergency Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States.,Armstrong Institute Center for Health Care Human Factors, Johns Hopkins Medicine, Baltimore, MD, United States.,Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Scott Levin
- Department of Emergency Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States.,StoCastic, Towson, MD, United States
| | - Jeremiah Hinson
- Department of Emergency Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States.,StoCastic, Towson, MD, United States
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11
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Lai CH, Li KW, Hu FW, Su PF, Hsu IL, Huang MH, Huang YT, Liu PY, Shen MR. Integration of an ICU Visualization Dashboard (i-Dashboard) as a Platform to Facilitate Multidisciplinary Rounds: A Cluster Randomized Controlled Trial (Preprint). J Med Internet Res 2022; 24:e35981. [PMID: 35560107 PMCID: PMC9143774 DOI: 10.2196/35981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2022] [Revised: 02/20/2022] [Accepted: 04/25/2022] [Indexed: 11/13/2022] Open
Abstract
Background Multidisciplinary rounds (MDRs) are scheduled, patient-focused communication mechanisms among multidisciplinary providers in the intensive care unit (ICU). Objective i-Dashboard is a custom-developed visualization dashboard that supports (1) key information retrieval and reorganization, (2) time-series data, and (3) display on large touch screens during MDRs. This study aimed to evaluate the performance, including the efficiency of prerounding data gathering, communication accuracy, and information exchange, and clinical satisfaction of integrating i-Dashboard as a platform to facilitate MDRs. Methods A cluster-randomized controlled trial was performed in 2 surgical ICUs at a university hospital. Study participants included all multidisciplinary care team members. The performance and clinical satisfaction of i-Dashboard during MDRs were compared with those of the established electronic medical record (EMR) through direct observation and questionnaire surveys. Results Between April 26 and July 18, 2021, a total of 78 and 91 MDRs were performed with the established EMR and i-Dashboard, respectively. For prerounding data gathering, the median time was 10.4 (IQR 9.1-11.8) and 4.6 (IQR 3.5-5.8) minutes using the established EMR and i-Dashboard (P<.001), respectively. During MDRs, data misrepresentations were significantly less frequent with i-Dashboard (median 0, IQR 0-0) than with the established EMR (4, IQR 3-5; P<.001). Further, effective recommendations were significantly more frequent with i-Dashboard than with the established EMR (P<.001). The questionnaire results revealed that participants favored using i-Dashboard in association with the enhancement of care plan development and team participation during MDRs. Conclusions i-Dashboard increases efficiency in data gathering. Displaying i-Dashboard on large touch screens in MDRs may enhance communication accuracy, information exchange, and clinical satisfaction. The design concepts of i-Dashboard may help develop visualization dashboards that are more applicable for ICU MDRs. Trial Registration ClinicalTrials.gov NCT04845698; https://clinicaltrials.gov/ct2/show/NCT04845698
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Affiliation(s)
- Chao-Han Lai
- Department of Surgery, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan City, Taiwan
- Department of Biochemistry and Molecular Biology, College of Medicine, National Cheng Kung University, Tainan City, Taiwan
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Kai-Wen Li
- Department of Nursing, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan City, Taiwan
| | - Fang-Wen Hu
- Department of Nursing, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan City, Taiwan
| | - Pei-Fang Su
- Department of Statistics, College of Management, National Cheng Kung University, Tainan City, Taiwan
| | - I-Lin Hsu
- Department of Surgery, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan City, Taiwan
| | - Min-Hsin Huang
- Department of Surgery, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan City, Taiwan
| | - Yen-Ta Huang
- Department of Surgery, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan City, Taiwan
| | - Ping-Yen Liu
- Division of Cardiology, Department of Internal Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan City, Taiwan
- Institute of Clinical Medicine, College of Medicine, National Cheng Kung University, Tainan City, Taiwan
- Department of Clinical Medical Research, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan City, Taiwan
| | - Meng-Ru Shen
- Department of Obstetrics and Gynecology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
- Department of Pharmacology, College of Medicine, National Cheng Kung University, Tainan City, Taiwan
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12
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Walshe N, Ryng S, Drennan J, O'Connor P, O'Brien S, Crowley C, Hegarty J. Situation awareness and the mitigation of risk associated with patient deterioration: A meta-narrative review of theories and models and their relevance to nursing practice. Int J Nurs Stud 2021; 124:104086. [PMID: 34601204 DOI: 10.1016/j.ijnurstu.2021.104086] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Revised: 07/27/2021] [Accepted: 08/31/2021] [Indexed: 10/20/2022]
Abstract
BACKGROUND Accurate situation awareness has been identified as a critical component of effective deteriorating patient response systems and an essential patient safety skill for nursing practice. However, situation awareness has been defined and theorised from multiple perspectives to explain how individuals, teams and systems maintain awareness in dynamic task environments. AIM Our aim was to critically analyse the different approaches taken to the study of situation awareness in healthcare and explore the implications for nursing practice and research as it relates to clinical deterioration in ward contexts. METHODS We undertook a meta-narrative review of the healthcare literature to capture how situation awareness has been defined, theorised and studied in healthcare. Following an initial scoping review, we conducted an extensive search of ten electronic databases and included any theoretical, empirical or critical papers with a primary focus on situation awareness in an inpatient hospital setting. Included papers were collaboratively categorised in accordance with their theoretical framing, research tradition and paradigm with a narrative review presented. RESULTS A total of 120 papers were included in this review. Three overarching narratives reflecting philosophical, patient safety and solution focussed framings of situation awareness and seven meta-narratives were identified as follows: individual, team and systems perspectives of situation awareness (meta-narratives 1-3), situation awareness and patient safety (meta-narrative 4), communication tools, technologies and education to support situation awareness (meta-narratives 5-7). We identified a concentration of literature from anaesthesia and operating rooms and a body of research largely located within a cognitive engineering tradition and a positivist research paradigm. Endsley's situation awareness model was applied in over 80% of the papers reviewed. A minority of papers drew on alternative situation awareness theories including constructivist, collaborative and distributed perspectives. CONCLUSIONS Nurses have a critical role in identifying and escalating the care of deteriorating patients. There is a need to build on prior studies and reflect on the reality of nurse's work and the constraints imposed on situation awareness by the demands of busy inpatient wards. We suggest that this will require an analysis that complements but goes beyond the dominant cognitive engineering tradition to reflect the complex socio-cultural reality of ward-based teams and to explore how situation awareness emerges in increasingly complex, technologically enabled distributed healthcare systems.
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Affiliation(s)
- Nuala Walshe
- School of Nursing and Midwifery, University College Cork, College Road, Cork T12 AK54, Ireland.
| | - Stephanie Ryng
- School of Nursing and Midwifery, University College Cork, College Road, Cork T12 AK54, Ireland
| | - Jonathan Drennan
- School of Nursing and Midwifery, University College Cork, College Road, Cork T12 AK54, Ireland.
| | - Paul O'Connor
- Department of General Practice, National University of Ireland, Distillery Road, Newcastle, Co Galway H91 TK33, Ireland.
| | - Sinéad O'Brien
- School of Nursing and Midwifery, University College Cork, College Road, Cork T12 AK54, Ireland.
| | - Clare Crowley
- School of Nursing and Midwifery, University College Cork, College Road, Cork T12 AK54, Ireland.
| | - Josephine Hegarty
- School of Nursing and Midwifery, University College Cork, College Road, Cork T12 AK54, Ireland.
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13
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Almasi S, Rabiei R, Moghaddasi H, Vahidi-Asl M. Emergency Department Quality Dashboard; a Systematic Review of Performance Indicators, Functionalities, and Challenges. ARCHIVES OF ACADEMIC EMERGENCY MEDICINE 2021; 9:e47. [PMID: 34405145 PMCID: PMC8366462 DOI: 10.22037/aaem.v9i1.1230] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
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.
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Affiliation(s)
- Sohrab Almasi
- Department of Health Information Technology and Management, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Reza Rabiei
- Department of Health Information Technology and Management, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Hamid Moghaddasi
- Department of Health Information Technology and Management, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mojtaba Vahidi-Asl
- Faculty of Computer Science and Engineering, Shahid Beheshti University, Tehran, Iran
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14
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Leonard F, Gilligan J, Barrett MJ. Predicting Admissions From a Paediatric Emergency Department - Protocol for Developing and Validating a Low-Dimensional Machine Learning Prediction Model. Front Big Data 2021; 4:643558. [PMID: 33937750 PMCID: PMC8085432 DOI: 10.3389/fdata.2021.643558] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Accepted: 03/22/2021] [Indexed: 12/02/2022] Open
Abstract
Introduction: Patients boarding in the Emergency Department can contribute to overcrowding, leading to longer waiting times and patients leaving without being seen or completing their treatment. The early identification of potential admissions could act as an additional decision support tool to alert clinicians that a patient needs to be reviewed for admission and would also be of benefit to bed managers in advance bed planning for the patient. We aim to create a low-dimensional model predicting admissions early from the paediatric Emergency Department. Methods and Analysis: The methodology Cross Industry Standard Process for Data Mining (CRISP-DM) will be followed. The dataset will comprise of 2 years of data, ~76,000 records. Potential predictors were identified from previous research, comprising of demographics, registration details, triage assessment, hospital usage and past medical history. Fifteen models will be developed comprised of 3 machine learning algorithms (Logistic regression, naïve Bayes and gradient boosting machine) and 5 sampling methods, 4 of which are aimed at addressing class imbalance (undersampling, oversampling, and synthetic oversampling techniques). The variables of importance will then be identified from the optimal model (selected based on the highest Area under the curve) and used to develop an additional low-dimensional model for deployment. Discussion: A low-dimensional model comprised of routinely collected data, captured up to post triage assessment would benefit many hospitals without data rich platforms for the development of models with a high number of predictors. Novel to the planned study is the use of data from the Republic of Ireland and the application of sampling techniques aimed at improving model performance impacted by an imbalance between admissions and discharges in the outcome variable.
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Affiliation(s)
- Fiona Leonard
- Business Intelligence Unit, Children's Health Ireland at Crumlin, Dublin, Ireland
| | - John Gilligan
- School of Computer Science, Technological University Dublin, Dublin, Ireland
| | - Michael J Barrett
- Department of Emergency Medicine, Children's Health Ireland at Crumlin, Dublin, Ireland.,School of Medicine, University College Dublin, Dublin, Ireland
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15
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Housbane S, Khoubila A, Ajbal K, Agoub M, Battas O, Othmani MB. Real-Time Monitoring System to Manage Mental Healthcare Emergency Unit. Healthc Inform Res 2020; 26:344-350. [PMID: 33190469 PMCID: PMC7674820 DOI: 10.4258/hir.2020.26.4.344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Accepted: 07/17/2020] [Indexed: 12/04/2022] Open
Abstract
Objectives Real-time relevant information helps guide the healthcare decision-making process in daily clinical practice as well as the management and optimization of healthcare processes. However, proprietary business intelligence suite solutions supporting the production of decision-making information requires investment that is out of reach of small and medium-sized healthcare facilities or those with limited resources, particularly in developing countries. This paper describes our experience in designing and implementing a real-time healthcare monitoring system solution to manage healthcare emergency units. Methods Through the use of free Business Intelligence tools and Python data science language we designed a real-time monitoring system, which was implemented to explore the Electronic Medical Records system of a university mental health emergency unit and render an electronic dashboard to support health professional daily practice. Results Three main dashboards were created to monitor patient waiting time, to access the clinical notes summary for the next waiting patient, and to obtain insights into activity during the last 24 hours. Conclusions The designed system could serve as a monitoring support model using free and user-friendly data science tools, which are good alternatives to proprietary business intelligence solutions and drastically reduce cost. Still, the key to success in decision-making systems is based on investment in human resources, business intelligence skills training, the organizational aspect of the decision-making process, and data production quality insurance.
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Affiliation(s)
- Samy Housbane
- Medical Informatics Laboratory, Faculty of Medicine and Pharmacy, University Hassan II, Casablanca, Morocco.,Clinical Neurosciences and Mental Health Research Laboratory, University Hassan II, Casablanca, Morocco
| | - Adil Khoubila
- Clinical Neurosciences and Mental Health Research Laboratory, University Hassan II, Casablanca, Morocco.,University Psychiatric Centre, University Hospital Ibn Rochd, Casablanca, Morocco
| | - Khaoula Ajbal
- Medical Informatics Laboratory, Faculty of Medicine and Pharmacy, University Hassan II, Casablanca, Morocco.,Clinical Neurosciences and Mental Health Research Laboratory, University Hassan II, Casablanca, Morocco
| | - Mohamed Agoub
- Clinical Neurosciences and Mental Health Research Laboratory, University Hassan II, Casablanca, Morocco.,University Psychiatric Centre, University Hospital Ibn Rochd, Casablanca, Morocco
| | - Omar Battas
- Clinical Neurosciences and Mental Health Research Laboratory, University Hassan II, Casablanca, Morocco.,University Psychiatric Centre, University Hospital Ibn Rochd, Casablanca, Morocco
| | - Mohamed Bennani Othmani
- Medical Informatics Laboratory, Faculty of Medicine and Pharmacy, University Hassan II, Casablanca, Morocco.,Clinical Neurosciences and Mental Health Research Laboratory, University Hassan II, Casablanca, Morocco
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16
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Laurent G, Moussa MD, Cirenei C, Tavernier B, Marcilly R, Lamer A. Development, implementation and preliminary evaluation of clinical dashboards in a department of anesthesia. J Clin Monit Comput 2020; 35:617-626. [PMID: 32418147 PMCID: PMC7229430 DOI: 10.1007/s10877-020-00522-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Accepted: 05/05/2020] [Indexed: 12/15/2022]
Abstract
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.
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Affiliation(s)
- Géry Laurent
- INSERM, CHU Lille, CIC-IT/Evalab 1403 - Centre d'Investigation Clinique, 59000, Lille, France.,Univ. Lille, CHU Lille, ULR 2694 - METRICS: Évaluation des Technologies de santé et des Pratiques médicales, 59000, Lille, France.,Univ. Lille, Faculté Ingénierie et Management de la Santé, 59000, Lille, France
| | | | - Cédric Cirenei
- CHU Lille, Pôle d'Anesthésie-Réanimation, 59000, Lille, France
| | - Benoît Tavernier
- Univ. Lille, CHU Lille, ULR 2694 - METRICS: Évaluation des Technologies de santé et des Pratiques médicales, 59000, Lille, France.,CHU Lille, Pôle d'Anesthésie-Réanimation, 59000, Lille, France
| | - Romaric Marcilly
- INSERM, CHU Lille, CIC-IT/Evalab 1403 - Centre d'Investigation Clinique, 59000, Lille, France.,Univ. Lille, CHU Lille, ULR 2694 - METRICS: Évaluation des Technologies de santé et des Pratiques médicales, 59000, Lille, France
| | - Antoine Lamer
- INSERM, CHU Lille, CIC-IT/Evalab 1403 - Centre d'Investigation Clinique, 59000, Lille, France. .,Univ. Lille, CHU Lille, ULR 2694 - METRICS: Évaluation des Technologies de santé et des Pratiques médicales, 59000, Lille, France. .,Univ. Lille, Faculté Ingénierie et Management de la Santé, 59000, Lille, France.
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17
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Hur S, Lee J, Kim T, Choi JS, Kang M, Chang DK, Cha WC. An Automated Fast Healthcare Interoperability Resources-Based 12-Lead Electrocardiogram Mobile Alert System for Suspected Acute Coronary Syndrome. Yonsei Med J 2020; 61:416-422. [PMID: 32390365 PMCID: PMC7214107 DOI: 10.3349/ymj.2020.61.5.416] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Revised: 03/10/2020] [Accepted: 03/26/2020] [Indexed: 11/27/2022] Open
Abstract
PURPOSE For patients with time-critical acute coronary syndrome, reporting electrocardiogram (ECG) findings is the most important component of the treatment process. We aimed to develop and validate an automated Fast Healthcare Interoperability Resources (FHIR)-based 12-lead ECG mobile alert system for use in an emergency department (ED). MATERIALS AND METHODS An automated FHIR-based 12-lead ECG alert system was developed in the ED of an academic tertiary care hospital. The system was aimed at generating an alert for patients with suspected acute coronary syndrome based on interpretation by the legacy device. The alert is transmitted to physicians both via a mobile application and the patient's electronic medical record (EMR). The automated FHIR-based 12-lead ECG alert system processing interval was defined as the time from ED arrival and 12-lead ECG capture to the time when the FHIR-based notification was transmitted. RESULTS During the study period, 3812 emergency visits and 1581 12-lead ECGs were recorded. The FHIR system generated 155 alerts for 116 patients. The alerted patients were significantly older [mean (standard deviation): 68.1 (12.4) years vs. 59.6 (16.8) years, p<0.001], and the cardiac-related symptom rate was higher (34.5% vs. 19%, p<0.001). Among the 155 alerts, 146 (94%) were transmitted successfully within 5 minutes. The median interval from 12-lead ECG capture to FHIR notification was 2.7 min [interquartile range (IQR) 2.2-3.1 min] for the group with cardiac-related symptoms and 3.0 min (IQR 2.5-3.4 min) for the group with non-cardiac-related symptoms. CONCLUSION An automated FHIR-based 12-lead ECG mobile alert system was successfully implemented in an ED.
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Affiliation(s)
- Sujeong Hur
- Department of Digital Health, Samsung Advanced Institute for Health Science & Technology (SAIHST), Sungkyunkwan University, Seoul, Korea
- Department of Nursing, Samsung Medical Center, Seoul, Korea
| | - Jeanhyoung Lee
- Health Information and Strategy Center, Samsung Medical Center, Seoul, Korea
| | - Taerim Kim
- Department of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Jong Soo Choi
- Department of Digital Health, Samsung Advanced Institute for Health Science & Technology (SAIHST), Sungkyunkwan University, Seoul, Korea
- Health Information and Strategy Center, Samsung Medical Center, Seoul, Korea
| | - Mira Kang
- Department of Digital Health, Samsung Advanced Institute for Health Science & Technology (SAIHST), Sungkyunkwan University, Seoul, Korea
- Health Information and Strategy Center, Samsung Medical Center, Seoul, Korea
- Center for Health Promotion, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Dong Kyung Chang
- Department of Digital Health, Samsung Advanced Institute for Health Science & Technology (SAIHST), Sungkyunkwan University, Seoul, Korea
- Health Information and Strategy Center, Samsung Medical Center, Seoul, Korea
- Department of Gastroenterology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Won Chul Cha
- Department of Digital Health, Samsung Advanced Institute for Health Science & Technology (SAIHST), Sungkyunkwan University, Seoul, Korea
- Health Information and Strategy Center, Samsung Medical Center, Seoul, Korea
- Department of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
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18
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Westphal M, Yom-Tov GB, Parush A, Carmeli N, Shaulov A, Shapira C, Rafaeli A. A Patient-Centered Information System (myED) for Emergency Care Journeys: Design, Development, and Initial Adoption. JMIR Form Res 2020; 4:e16410. [PMID: 32130144 PMCID: PMC7064965 DOI: 10.2196/16410] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Revised: 12/15/2019] [Accepted: 12/15/2019] [Indexed: 02/06/2023] Open
Abstract
Background Medical care is highly complex in that it addresses patient-centered health goals that require the coordination of multiple care providers. Emergency department (ED) patients currently lack a sense of predictability about ED procedures. This increases frustration and aggression. Herein, we describe a system for providing real-time information to ED patients regarding the procedures in their ED medical journey. Objective This study aimed to develop a system that provides patients with dynamically updated information about the specific procedures and expected waiting times in their personal ED journey, and to report initial evaluations of this system. Methods To develop the myED system, we extracted information from hospital databases and translated it using process mining and user interface design into a language that is accessible and comprehensible to patients. We evaluated the system using a mixed methods approach that combined observations, interviews, and online records. Results Interviews with patients, accompanying family members, and health care providers (HCPs) confirmed patients’ needs for information about their personal ED journey. The system developed enables patients to access this information on their personal mobile phones through a responsive website. In the third month after deployment, 492 of 1614 (30.48%) patients used myED. Patients’ understanding of their ED journey improved significantly (F8,299=2.519; P=.01), and patients showed positive reactions to the system. We identified future challenges, including achieving quick engagement without delaying medical care. Salient reasons for poor system adoption were patients’ medical state and technological illiteracy. HCPs confirmed the potential of myED and identified means that could improve patient experience and staff cooperation. Conclusions Our iterative work with ED patients, HCPs, and a multidisciplinary team of developers yielded a system that provides personal information to patients about their ED journey in a secure, effective, and user-friendly way. MyED communicates this information through mobile technology. This improves health care by addressing patients’ psychological needs for information and understanding, which are often overlooked. We continue to test and refine the system and expect to find positive effects of myED on patients’ ED experience and hospital operations.
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Affiliation(s)
| | | | - Avi Parush
- Technion - Israel Institute of Technology, Haifa, Israel
| | - Nitzan Carmeli
- Technion - Israel Institute of Technology, Haifa, Israel
| | - Alina Shaulov
- Technion - Israel Institute of Technology, Haifa, Israel
| | - Chen Shapira
- Technion - Israel Institute of Technology, Haifa, Israel
| | - Anat Rafaeli
- Technion - Israel Institute of Technology, Haifa, Israel
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19
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Boillat T, Siebert JN, Alduaij N, Ehrler F. GOFlow: Smartwatch app to deliver laboratory results in emergency departments - A feasibility study. Int J Med Inform 2019; 134:104034. [PMID: 31790858 DOI: 10.1016/j.ijmedinf.2019.104034] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2019] [Revised: 11/18/2019] [Accepted: 11/19/2019] [Indexed: 10/25/2022]
Abstract
PURPOSE Information Technology (IT) plays a critical role in supporting emergency physicians' (EPs) routines. Pagers, personal computers, and smartphones offer fast access to patient data, such as laboratory results. However, due to the inherent features of specimen processing and laboratory instruments, the turnaround time from test ordering to availability of results can be long. Lack of follow-up of abnormal results can lead to missed information that could impact patient care and safety. Despite the increasing use of ubiquitous technologies, a third of physicians remains devoid of reliable methods for ensuring that results have been received. In this feasibility study, we report the potential of using a smartwatch to deliver laboratory results to EPs at the point-of-care and to support efficiency in emergency care. Unlike mobile devices that are increasingly used by EPs, smartwatches are always accessible, even during hands-on procedures. METHOD Two EPs and four experts in human-computer interaction designed the smartwatch application following the Design Science Research Methodology (DSRM). The application was then evaluated in a pediatric emergency department through semi-simulated scenarios by eleven EPs. The primary outcome was to measure both the app perceived usability and satisfaction scores by the aim of the System Usability Scale (SUS), and the perceived usefulness and intention of its use by the aim of the Unified Theory of Acceptance and Use of Technology (UTAUT) scale. Secondary outcomes were to assess the application's efficiency by measuring the delay between the reception of the notification and 1) the access to its details and 2) the visit to the patient. Finally, open questions about the positive and negative aspects of the prototype as well as potential improvements were asked and evaluated qualitatively. RESULTS The prototype obtained a score of 81.4 out of 100 (good) on the SUS and a score of 5.96 out of 7 on the UTAUT scale. EPs using the smartwatch visited patients within 30 seconds receiving the laboratory results. CONCLUSIONS This study demonstrates the capacity of smartwatches to speed up the point-of-care delivery of laboratory results in the ED.
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Affiliation(s)
- Thomas Boillat
- Mohammed Bin Rashid University of Medicine and Health Sciences, Design Lab, Dubai, United Arab Emirates.
| | - Johan N Siebert
- Department of Pediatric Emergency Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Nadim Alduaij
- Department of Emergency Medicine, Dar Al Shifa Hospital, Hawally, Kuwait
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