Looking Forward to Cuts: A Simulation Decision Tool for Cutback Management

2019 ◽  
Vol 40 (1) ◽  
pp. 3-21
Author(s):  
Spencer T. Brien ◽  
Philip J. Candreva ◽  
Stephen C. Hansen ◽  
Mina Pizzini
Keyword(s):  
Decision Tool ◽  
Cutback Management

Looking Forward to Cuts: A Simulation Decision Tool for Cutback Management

2019 ◽  
Author(s):  
Spencer Brien ◽  
Philip J. Candreva ◽  
Stephen C. Hansen ◽  
Mina Pizzini
Keyword(s):  
Decision Tool ◽  
Cutback Management

A practical overview and decision tool for analyzing recurrent events in mental illness: A review

2021 ◽  
Vol 137 ◽  
pp. 7-13
Author(s):  
Tyler S. Kaster ◽  
Simone N. Vigod ◽  
Tara Gomes ◽  
Duminda N. Wijeysundera ◽  
Daniel M. Blumberger ◽  
...  
Keyword(s):  
Mental Illness ◽  
Recurrent Events ◽  
Decision Tool

Threshold Value for Chlorophyll Meter as Decision Tool for Nitrogen Management of Potato

2006 ◽  
Vol 98 (3) ◽  
pp. 496-506 ◽  
Author(s):  
Marguerite Olivier ◽  
Jean-Pierre Goffart ◽  
Jean-François Ledent
Keyword(s):  
Threshold Value ◽  
Nitrogen Management ◽  
Decision Tool ◽  
Chlorophyll Meter

scholarly journals 31 Head home: a prospective cohort study of a nurse led paediatric head injury clinical decision tool at a district general hospital

2020 ◽  
Vol 37 (12) ◽  
pp. 853-854
Author(s):  
Patrick Aldridge ◽  
Heather Castle ◽  
Emma Russell ◽  
Clare Phillips ◽  
Richard Guerrero-Luduena ◽  
...  
Keyword(s):  
Head Injury ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Head Injuries ◽  
Clinical Decision ◽  
Decision Tool ◽  
Intracranial Injury ◽  
Multi Centre Study ◽  
Paediatric Head Injury ◽  
Published Evidence

Aims/Objectives/BackgroundObjectivesTo assess if application of a nurse-led paediatric head injury clinical decision tool would be safe compared to current practice.Background>700,000 children attend UK hospitals’ each year with a head injury. Research indicates <1% undergo neurosurgical intervention. No published evidence for nurse-led discharge of paediatric head injuries exists.Methods/DesignMethods – All paediatric (<17 years) patients with head injuries presenting to our Emergency department (ED) 1st May to 31st October 2018 were prospectively screened by a nurse using a mandated electronic ‘Head Injury Discharge At Triage’ questionnaire (HIDATq). We determined which patients underwent computed tomography (CT) brain and whether there was a clinically important intracranial injury or re-presentation to ED. The negative predictive value of the screening tool was assessed. We determined what proportion of patients could have been sent home from triage using HIDATq.Results/ConclusionsResults - Of 1739 patients screened; 61 had CTs performed due to head injury (6 abnormal) with a CT rate of 3.5% and 2% re-presentations. Of the entire cohort, 1052 screened negative. 1 CT occurred in this group showing no abnormalities. Of those screened negative: 349/1052 (33%) had ‘no other injuries’ and 543/1052 (52%) had ‘abrasions or lacerations’. HIDATq’s negative predictive value for CT was 99.9% (95% Confidence interval (CI) 99.4–99.9%) and 100% (CI 99.0–100%) for intracranial injury. The positive predictive value of the tool was low. Five patients screened negative and re-presented within 72hrs but did not require CT imaging.Conclusion - A negative HIDATq appears safe in our ED. Potentially 20% (349/1739) of all patients with head injuries presenting to our department could be discharged by nurses at triage with adequate safety netting advice. This increases to 50% (543/1739) if patients with lacerations or abrasions were treated and discharged at triage. A large multi-centre study is required to validate the tool.

Decision Tool for Selecting the Optimal Techniques for Cost and Schedule Reduction in Capital Projects

2011 ◽  
Vol 137 (9) ◽  
pp. 645-655 ◽  
Author(s):  
Mehmet Emre Bayraktar ◽  
Makarand Hastak ◽  
Sanjiv Gokhale ◽  
Bhavin Safi
Keyword(s):  
Decision Tool ◽  
Capital Projects

scholarly journals Visualization-Based Decision Tool for Urban Meteorological Modeling

2013 ◽  
Vol 40 (2) ◽  
pp. 271-288 ◽  
Author(s):  
Daniel G Aliaga ◽  
Carlo Vanegas ◽  
Ming Lei ◽  
Dev Niyogi
Keyword(s):  
Decision Tool ◽  
Meteorological Modeling
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