scholarly journals Whole Disease Modeling to Inform Resource Allocation Decisions in Cancer: A Methodological Framework

2012 ◽  
Vol 15 (8) ◽  
pp. 1127-1136 ◽  
Author(s):  
Paul Tappenden ◽  
Jim Chilcott ◽  
Alan Brennan ◽  
Hazel Squires ◽  
Matthew Stevenson
Keyword(s):  
Resource Allocation ◽  
Disease Modeling ◽  
Methodological Framework ◽  
Allocation Decisions ◽  
Inform Resource Allocation ◽  
Resource Allocation Decisions

Unexpected Consequences: The Effects on Non-Accelerated Filers of an Accelerated Filing Deadline and SOX Section 404

2020 ◽  
Vol 34 (3) ◽  
pp. 87-112
Author(s):  
Bei Dong ◽  
Stefanie L. Tate ◽  
Le Emily Xu
Keyword(s):  
Resource Allocation ◽  
Financial Statements ◽  
Financial Statement ◽  
Negative Consequences ◽  
Section 404 ◽  
Auditor Change ◽  
Time Required ◽  
Allocation Decisions ◽  
Jel Classifications ◽  
Resource Allocation Decisions

SYNOPSIS Regulations implemented by the SEC in 2003 and 2004 simultaneously shortened the financial statement filing deadlines and increased the time required for both the preparation of financial statements and the related audit of accelerated filers (AFs). However, there were indirect, unintended negative consequences for companies not subject to the regulations, namely, non-accelerated filers (NAFs). The new regulations imposed strains on auditor resources requiring auditors to make resource allocation decisions that negatively affected NAFs. We find that NAFs with an auditor who had a high proportion of AF clients (high-AF) had longer audit delays after the regulations were implemented than NAFs of an auditor with a low proportion of AF clients (low-AF). Further, we document that NAFs with high-AF auditors were more likely to change auditors than NAFs with low-AF auditors. Finally, NAFs that switched to auditors with less AFs experienced shorter audit delays after the auditor change. JEL Classifications: M42; M48.

scholarly journals Balancing scarce hospital resources during the COVID-19 pandemic using discrete-event simulation

2021 ◽  
Author(s):  
G.J. Melman ◽  
A.K. Parlikad ◽  
E.A.B. Cameron
Keyword(s):  
Resource Allocation ◽  
Discrete Event Simulation ◽  
Elective Surgery ◽  
Discrete Event ◽  
Specific Patient ◽  
Event Simulation ◽  
The Impact ◽  
Allocation Decisions ◽  
Allocation Strategies ◽  
Resource Allocation Decisions

AbstractCOVID-19 has disrupted healthcare operations and resulted in large-scale cancellations of elective surgery. Hospitals throughout the world made life-altering resource allocation decisions and prioritised the care of COVID-19 patients. Without effective models to evaluate resource allocation strategies encompassing COVID-19 and non-COVID-19 care, hospitals face the risk of making sub-optimal local resource allocation decisions. A discrete-event-simulation model is proposed in this paper to describe COVID-19, elective surgery, and emergency surgery patient flows. COVID-19-specific patient flows and a surgical patient flow network were constructed based on data of 475 COVID-19 patients and 28,831 non-COVID-19 patients in Addenbrooke’s hospital in the UK. The model enabled the evaluation of three resource allocation strategies, for two COVID-19 wave scenarios: proactive cancellation of elective surgery, reactive cancellation of elective surgery, and ring-fencing operating theatre capacity. The results suggest that a ring-fencing strategy outperforms the other strategies, regardless of the COVID-19 scenario, in terms of total direct deaths and the number of surgeries performed. However, this does come at the cost of 50% more critical care rejections. In terms of aggregate hospital performance, a reactive cancellation strategy prioritising COVID-19 is no longer favourable if more than 7.3% of elective surgeries can be considered life-saving. Additionally, the model demonstrates the impact of timely hospital preparation and staff availability, on the ability to treat patients during a pandemic. The model can aid hospitals worldwide during pandemics and disasters, to evaluate their resource allocation strategies and identify the effect of redefining the prioritisation of patients.

A Common Approach to Risk Analysis Methodology

2003 ◽  
Author(s):  
J. Robert Sims
Keyword(s):  
Resource Allocation ◽  
Risk Analysis ◽  
Broad Spectrum ◽  
Analysis Methodology ◽  
Risk Ranking ◽  
Homeland Defense ◽  
Narrow Area ◽  
Allocation Decisions ◽  
Resource Allocation Decisions

Risk analysis has been used extensively to inform decisions throughout government and industry for many years. Many methodologies have been developed to perform these analyses, resulting in differences in terminology and approach that make it difficult to compare the results of an analysis in one field to that in another. In particular, many approaches result only in a risk ranking within a narrow area or field of interest, so the results cannot be compared to rankings in other areas or fields. However, dealing with terrorist threats requires prioritizing the allocation of homeland defense resources across a broad spectrum of possible targets. Therefore, a common approach is needed to allow comparison of risks. This presentation summarizes an approach that will allow the results of risk analyses based on using current methodologies to be expressed in a common format with common terminology to facilitate resource allocation decisions.

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