2018
DOI: 10.1111/ajag.12525
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e‐Screening revolution: A novel approach to developing a delirium screening tool in the intensive care unit

Abstract: e-Screening for delirium requires a novel approach to instrument design but may revolutionise recognition of delirium in ICU.

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Cited by 9 publications
(6 citation statements)
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“…13 Despite this limitation, it should be acknowledged that consumer engagement has been sought in earlier phases of development of the original tool. 1,3 The revised pictorial questions are currently being reviewed against Color Universal Design principles and some changes in the semantics of in-app diagnosis are being eveluated. 14 In the optimised form, clinical testing is anticipated.…”
Section: Number Of Itemsmentioning
confidence: 99%
See 1 more Smart Citation
“…13 Despite this limitation, it should be acknowledged that consumer engagement has been sought in earlier phases of development of the original tool. 1,3 The revised pictorial questions are currently being reviewed against Color Universal Design principles and some changes in the semantics of in-app diagnosis are being eveluated. 14 In the optimised form, clinical testing is anticipated.…”
Section: Number Of Itemsmentioning
confidence: 99%
“…Our group developed an electronic delirium screening tool (eDIS-ICU) designed for use in the intensive care setting. 1 Comprised of multiple questions that relate to delirium diagnostic criteria, eDIS-ICU is designed to select at random a small number of these to the patient. Repeated incorrect responses then default to an in-appgenerated diagnosis of delirium.…”
Section: Introductionmentioning
confidence: 99%
“…5 For these reasons, authors EE, OT, DF and and a multidisciplinary research group (Critical Care Research Group) have previously developed an electronic delirium screening tool [eDIS-ICU] that we successfully tested in the intensive care setting. 6,7 eDIS-ICU incorporates user-centred, delirium-specific and technological advantages. Firstly, a large bank of potential questions is randomised after each test, thus avoiding re-test error.…”
Section: Introductionmentioning
confidence: 99%
“…In response to this common and serious challenge, we designed an algorithm that would capture the representative and multifactorial cause(s) of delirium that could be used to identify clinical causes within a medical setting. The Aetiology in Delirium -Diagnostic Support Tool (AiD-DST) algorithm was developed from first principles by a multiprofessional team with a track record of innovation and cognitive tool development in delirium [13][14][15] (see appendix 1). The algorithm intended to follow the clinical flow of assessment by the physician, capture common causes with the greatest yield and use Bayesian principles of probability to improve efficiency.…”
Section: Introductionmentioning
confidence: 99%