Evaluation of a visual analytics decision support tool for wind farm placement planning in Alberta: Findings from a focus group study

2017 ◽  
Vol 117 ◽  
pp. 70-83 ◽  
Author(s):  
Ovo Adagha ◽  
Richard M. Levy ◽  
Sheelagh Carpendale ◽  
Cormack Gates ◽  
Mark Lindquist
Keyword(s):  
Decision Support ◽  
Focus Group ◽  
Visual Analytics ◽  
Wind Farm ◽  
Decision Support Tool ◽  
Focus Group Study ◽  
Support Tool

scholarly journals Implementing a digital clinical decision support tool for side effects of antipsychotics: a focus group study

2019 ◽  
Vol 22 (2) ◽  
pp. 56-60 ◽  
Author(s):  
Catherine Henshall ◽  
Andrea Cipriani ◽  
David Ruvolo ◽  
Orla Macdonald ◽  
Leona Wolters ◽  
...  
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Side Effects ◽  
Side Effect ◽  
Decision Support Tool ◽  
Psychiatric Medication ◽  
Focus Group Study ◽  
Patient Decision Making ◽  
Support Tool ◽  
Patient Decision

BackgroundIn medicine, algorithms can inform treatment decisions by combining the most up-to-date evidence about side effect profiles of medications, which are comparable in efficacy. Their use provides opportunities for improved shared clinician–patient decision-making when initiating therapy. We designed a decision support tool (DST) that incorporated the latest evidence regarding antipsychotic side effects. The tool allowed patients to select one side effect commonly associated with antipsychotics that they wished to avoid; the tool then provided a list of suggested medications and ones to avoid.ObjectiveTo explore qualitatively the acceptability and usefulness of the DST from the perspectives of patients and psychiatrists.MethodsThis qualitative study took place at a mental health and community hospital in Oxford, UK, in 2018. Four patients/carers and four psychiatrists were recruited to two focus groups to explore their perceptions of the tool. Data were thematically analysed.FindingsFindings demonstrated a high degree of acceptability and potential usability of the DST for patients and psychiatrists. The main themes to emerge relating to the DST were ‘prescribing preferences and practices’, ‘consideration and awareness of side effects’, ‘app content, layout and accessibility’, ‘influence on clinical practice’ and ‘role in decision-making’.ConclusionsA proof-of-concept clinical study will incorporate the recommendations produced from the findings into the tool’s design.Clinical implicationsDigital DSTs provide opportunities for the most up-to-date information on medication side effects to be used as the basis for shared clinician–patient decision-making. This tool has the potential to improve adherence to psychiatric medication, with benefits to clinical outcomes and healthcare resourcing.

A Decision Support Tool for Evaluating Big Data Investment in Transport: Empirical evidence from European use cases of NOESIS project

2020 ◽  
Author(s):  
Christos Katrakazas ◽  
Natalia Sobrino ◽  
Ilias Trochidis ◽  
Jose Manuel Vassallo ◽  
Stratos Arampatzis ◽  
...  
Keyword(s):  
Big Data ◽  
Decision Support ◽  
Empirical Evidence ◽  
Decision Support Tool ◽  
Use Cases ◽  
Support Tool
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