Accepted for/Published in: JMIR Human Factors
Date Submitted: May 29, 2023
Open Peer Review Period: May 29, 2023 - Jun 12, 2023
Date Accepted: Aug 17, 2023
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Design and Evaluation of an Intensive Care Unit Dashboard Built in Response to COVID-19 Pandemic: Semi-structured Interview Study
ABSTRACT
Background:
Dashboards and interactive displays are becoming increasingly present in most healthcare settings and have the potential to streamline access to information, consolidate disparate data sources and deliver new insights such as trends and aggregate patient metrics. In particular, we focus on Intensive Care Units (ICUs) that are heavily instrumented, critical care environments that generate vast amounts of data and frequently require individualised support for each of the patients. As a result, clinicians experience a high cognitive load, which can translate to suboptimal performance. The global COVID-19 Pandemic exacerbated this problem by generating a high number of additional hospitalisations, which necessitated a new tool that would help manage the ICU’s census. In a previous study, we conducted interviews with clinicians at the University Hospitals Bristol and Weston NHS Foundation Trust (UHBW) to capture the requirements for bespoke dashboards that would alleviate this problem.
Objective:
The objective of this study was 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, as those seen during the COVID-19 pandemic.
Methods:
Building upon the previously gathered design requirements, we developed a dashboard, integrated it within the ICU of an NHS 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 semi-structured interviews followed a topic guide aimed at capturing the usability and usefulness of the dashboard, which was supplemented with additional questions asked post-hoc to probe themes established during the interview. All interviews were transcribed and analysed using a thematic analysis framework which combined inductive and deductive approaches and integrated the Technology Acceptance Model (TAM).
Results:
A total of 10 participants with 4 different roles in the ICU (6 Consultants, 2 Junior Doctors, 1 Nurse and 1 Advanced Clinical Practitioner) took part in the interviews. Our analysis generated 4 key topics that prevailed across the data: (1) our dashboard met the usability requirements of the participants and was found useful and intuitive; (2) participants perceived that it impacted their delivery of patient care - in particular by improving the access to the information and better equipping them to do their job; (3) the tool was used in a variety of ways and for different reasons and tasks; (4) there were barriers to integration of our dashboard into practice, including familiarity with existing systems, which stifled the adoption of our tool.
Conclusions:
The findings of our study show that the perceived utility of the dashboard had a positive impact on the workflows of the clinicians 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.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.