Clinical information displays to improve ICU outcomes

Effken, Judith A.; Loeb, Robert G.; Kang, Youngmi; Lin, Zu Chun

doi:10.1016/j.ijmedinf.2008.05.004

Cited by 70 publications

(73 citation statements)

References 44 publications

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“…A time-in-motion analysis was performed in conjunction to the execution of the NASA-TLX questionnaire, in the context of an emergency department, to study the behaviour of faculty and resident physicians in the presence of an electronic whiteboard [16]. The NASA-TLX and a primary task performance measure were used in the context of intensive care to quantify the workload associated to the use of a prototype ecological display and two bar graph displays [15]. The goal was to analyse which display imposed less mental workload on nurses while identifying and treating oxygenation problems in an experimental laboratory simulation.…”

Section: Applications In Medical Domainsmentioning

confidence: 99%

“…Moreover, analysis of data gathered by these tools is a non-trivial process, requiring well-trained experts. A minority of reviewed research studies have employed at least two measurement approaches [51,50,26,16,15,8,45,60,46] while only three recent papers made use of all the three measurement techniques [52,25,19]. The reasons behind this are hidden in the complexity required by executing experiments, the difficulty in recruiting a significant enough amount of participants in clinical settings as well as the time and equipments required to perform such experiments.…”

Section: Open Problemsmentioning

confidence: 99%

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Mental Workload in Medicine: Foundations, Applications, Open Problems, Challenges and Future Perspectives

Longo¹

2016

2016 IEEE 29th International Symposium on Computer-Based Medical Systems (CBMS)

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Abstract-Mental workload is a design concept borrowed from Ergonomics with a significant adoption in the aviation and automobile industries. Nowadays, the consideration of this construct is also taking place in many modern clinical working environments for designing interacting and complex systems that impose ever greater cognitive demand on operators and less physical load. Measuring mental workload is essential for improving the interaction human-system, enhancing performance, reducing the operator's error and increasing safety. However, defining, measuring, assessing mental workload and understanding how this impinges on performance are still open problems. This secondary research is firstly aimed at introducing the construct of mental workload, its foundations, measurements techniques as well as applications in medicine.It then discusses open problems for applied research and eventually, it concludes with a list of challenges for scholars and practitioners. The goal is to provide the reader with a picture of the state of the science of mental workload in medicine and clinical domains with an eye towards future research.

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Section: Applications In Medical Domainsmentioning

confidence: 99%

Section: Open Problemsmentioning

confidence: 99%

Mental Workload in Medicine: Foundations, Applications, Open Problems, Challenges and Future Perspectives

Longo¹

2016

2016 IEEE 29th International Symposium on Computer-Based Medical Systems (CBMS)

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“…By contrast, graphical displays and integrated patient summaries that display all the information on a single screen can enhance speed and quality of clinical decision making [21]. Graphical displays also can improve recall and user satisfaction, whereas use of timeline displays helps find connections between events [22,23].…”

Section: Data Display and Visualizationmentioning

confidence: 99%

“…Furthermore, physiological data are dense because of its volume and high dimensionality. Combining too many elements in a single display can reduce critical event detection [23] and where there are multiple data streams computational algorithms can outperform clinicians [24]. Hence data visualization development needs to follow an iterative, human-centered design methodology to arrange information to support clinicians' the cognitive process but not aggravate clinical decision making [25].…”

Section: Data Display and Visualizationmentioning

confidence: 99%

Data Collection and Interpretation

et al. 2015

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Patient monitoring is routinely performed in all patients who receive neurocritical care. The combined use of monitors, including the neurologic examination, laboratory analysis, imaging studies, and physiological parameters, is common in a platform called multi-modality monitoring (MMM). However, the full potential of MMM is only beginning to be realized since for the most part, decision making historically has focused on individual aspects of physiology in a largely threshold-based manner. The use of MMM now is being facilitated by the evolution of bio-informatics in critical care including developing techniques to acquire, store, retrieve, and display integrated data and new analytic techniques for optimal clinical decision making. In this review, we will discuss the crucial initial steps toward data and information management, which in this emerging era of data-intensive science is already shifting concepts of care for acute brain injury and has the potential to both reshape how we do research and enhance cost-effective clinical care.

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“…Subjective workload was measured with either the NASA TLX form (9,11,14,17,19,25,26,28,(32)(33)(34)(35)(36)(37), the Borg workload score (20)(21)(22), or other paper-based, unvalidated forms (13,15,23,24,38). The conclusions of these studies suggest that mental workload is reduced by using speech-input records compared to written records (13), with experience (15,21,23,26,27,29,30), using a mixed graphical-numeric interface (11), using drug administration devices that provide feedback (14), with an improved electronic interface (17,37), with the addition of instruction to training, (25) with increased practice (28), and with digital rather than hard-copy x-rays (35).…”

Section: Published Evidencementioning

confidence: 99%

Measurement of Mental Workload in Clinical Medicine: A Review Study

Byrne

2011

Anesth Pain

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A B S T R A C TBackground: Measures of mental workload are now commonly used in industries to identify sources of error and to improve performance. Objectives: This study aimed to review the evidence for the use of this technique within medicine. Patients and Methods:We used search engines and the internet to identify experimental studies that included a measure of mental workload in medical practitioners or trainees/students. Studies that aimed to measure mental "stress" as a disorder, or "productivity" were excluded. Each abstract and then the full paper were appraised prior to inclusion. Results: Thirty-three studies were identified that matched the inclusion criteria. Although these covered a variety of settings, common methods were identifiable. The results support the concept of mental workload measurement as an important factor in medical performance. Conclusions: The limited number of studies and the variety of definitions and measurement techniques used in these studies, make direct comparisons difficult. However, the utility of this methodology in medical education appears to have been established, and guidelines for further research methods are proposed. Please cite this paper as: Implication for health policy/practice/research/medical education:Excessive mental workload is associated with poor performance and error in practice and poor learning in the teaching environment. Strategies to limit workload have been used successfully in other industries and could be applied to medicine.

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Clinical information displays to improve ICU outcomes

Cited by 70 publications

References 44 publications

Mental Workload in Medicine: Foundations, Applications, Open Problems, Challenges and Future Perspectives

Mental Workload in Medicine: Foundations, Applications, Open Problems, Challenges and Future Perspectives

Data Collection and Interpretation

Measurement of Mental Workload in Clinical Medicine: A Review Study

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