Evidence map›Paper›PMID 37751239›Full record

ArticleJMIR human factors2023

Design and Evaluation of an Intensive Care Unit Dashboard Built in Response to the COVID-19 Pandemic: Semistructured Interview Study.

Marceli Wac, Ian Craddock, Sofia Chantziara, Tabitha Campbell, Raul Santos-Rodriguez, Brittany Davidson, Chris McWilliams

Abstract read
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Article in JMIR human factors, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Marceli WacFaculty of Engineering, University of Bristol, Bristol, United Kingdom.ORCID 0000-0002-1986-0401
Ian CraddockFaculty of Engineering, University of Bristol, Bristol, United Kingdom.ORCID 0000-0001-6552-8541
Sofia ChantziaraFaculty of Engineering, University of Bristol, Bristol, United Kingdom.ORCID 0000-0001-9698-6983
Tabitha CampbellUniversity Hospitals Bristol and Weston NHS Foundation Trust, Bristol, United Kingdom.ORCID 0009-0007-0349-2468
Raul Santos-RodriguezFaculty of Engineering, University of Bristol, Bristol, United Kingdom.ORCID 0000-0001-9576-3905
Brittany DavidsonFaculty of Engineering, University of Bristol, Bristol, United Kingdom.ORCID 0000-0001-9886-9043
Chris McWilliamsFaculty of Engineering, University of Bristol, Bristol, United Kingdom.ORCID 0000-0003-3816-5217

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDashboards and interactive displays are becoming increasingly prevalent in most health care settings and have the potential to streamline access to information, consolidate disparate data sources and deliver new insights. Our research focuses on intensive care units (ICUs) which are heavily instrumented, critical care environments that generate vast amounts of data and frequently require individualized support for each patient. Consequently, clinicians experience a high cognitive load, which can translate to suboptimal performance. The global COVID-19 pandemic exacerbated this problem by generating a large number of additional hospitalizations, which necessitated a new tool that would help manage ICUs' census. In a previous study, we interviewed clinicians at the University Hospitals Bristol and Weston National Health Service Foundation Trust to capture the requirements for bespoke dashboards that would alleviate this problem.

objectiveThis study aims to design, implement, and evaluate an ICU dashboard to allow for monitoring of the high volume of patients in need of critical care, particularly tailored to high-demand situations, such as those seen during the COVID-19 pandemic.

methodsBuilding upon the previously gathered requirements, we developed a dashboard, integrated it within the ICU of a National Health Service trust, and allowed all staff to access our tool. For evaluation purposes, participants were recruited and interviewed following a 25-day period during which they were able to use the dashboard clinically. The semistructured interviews followed a topic guide aimed at capturing the usability of the dashboard, supplemented with additional questions asked post hoc to probe themes established during the interview. Interview transcripts were analyzed using a thematic analysis framework that combined inductive and deductive approaches and integrated the Technology Acceptance Model.

resultsA total of 10 participants with 4 different roles in the ICU (6 consultants, 2 junior doctors, 1 nurse, and 1 advanced clinical practitioner) participated in the interviews. Our analysis generated 4 key topics that prevailed across the data: our dashboard met the usability requirements of the participants and was found useful and intuitive; participants perceived that it impacted their delivery of patient care by improving the access to the information and better equipping them to do their job; the tool was used in a variety of ways and for different reasons and tasks; and there were barriers to integration of our dashboard into practice, including familiarity with existing systems, which stifled the adoption of our tool.

conclusionsOur findings show that the perceived utility of the dashboard had a positive impact on the clinicians' workflows in the ICU. Improving access to information translated into more efficient patient care and transformed some of the existing processes. The introduction of our tool was met with positive reception, but its integration during the COVID-19 pandemic limited its adoption into practice.

Indexed as

COVID-19Critical CareIntensive Care UnitsHumansInterviews as TopicPandemicsSARS-CoV-2CISclinical information systemCOVID-19critical caredashboarddesignEHRelectronic health recordelectronic patient recordEPRhealthhuman-centered designICUintensive careintensive care unitinteractive displayinterviewparticipatory designsoftware engineeringthematic analysis

Identifiers

PMID37751239
PMCPMC10565627

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.