Optimum Workforce Research Articles

What is the Optimum Utilization of Cancer Surgery in High Income Settings? A National Population Based Analysis

Background: Estimating the optimum rate for utilization of surgery in the management of cancer helps to identify treatment gaps, estimate the survival impact of such gaps and to calculate the optimum workforce and other resources including budgets required to meet service needs. A population-based benchmark rate for optimum surgical utilization in high income settings has not been developed to inform policymakers and service provision but was recommended by the Lancet Oncology Commission into Global Cancer Surgery. Here we have developed and validated the first such instrument. Methods: The latest clinical guidelines were examined, and surgical treatment pathways were mapped for each cancer, broadly reflecting contemporary high income models of care. The optimum utilization of surgery was considered as an indication for surgery where surgery is the treatment of choice for a given clinical scenario. The population based epidemiological data such as stage of cancer, tumour characteristics, and fitness for surgery were derived from Australia and other comparable high-income settings. The probabilities across the clinical pathways of each cancer was multiplied and added together to estimate the optimum rates of cancer surgical utilization and compared with actual rates of utilization. Findings: Surgical treatment is indicated in 58% (95% CI 57% to 59%) of newly diagnosed cancer patients in Australia, at least once during the course of their treatment but varies between 22% and 99% for site specific cancers. The actual utilization was higher for some cancers including prostate, head &neck and cervix, whereas it was lower for other cancers such as lung, ovary and pancreas. Interpretation: There are discordances in modelled versus actual utilisation rates that require more in depth analysis. This approach provides a new template for other high income and emerging economies to rationally plan and assess their cancer surgery provision. Funding Statement: University of New South Wales Scientia Scholarship. Declaration of Interests: The authors declare no conflicts of interest. Ethics Approval Statement: The data on the actual surgical utilization from the South Western Sydney Clinical Cancer Registry was obtained with necessary ethical clearance.

Optimum workforce scheduling for multiple security gates

This article presents a two-stage workforce scheduling approach for security guards at motor traffic gates. In the first stage, staffing requirements are determined based on analyzing workload variations for each gate. In the second stage, an integer programming model is formulated to assign guards to different work shifts in order to satisfy the staffing requirements of each gate. The objective is to minimize the total labour cost of two categories of security employees: non-supervising (guards), and supervising (supervisors). The new model considers multiple employee types, multiple shifts, and multiple locations, where security employees are assigned to work groups. Moreover, to maximize flexibility, each employee can be assigned to work at different gates during different shifts. Compared to the currently used schedule, the model produced an optimum work schedule that reduced the workforce size by 23% and the labour cost by 26%. Computational experiments with 40 randomly generated test problems confirmed the high savings potential of the proposed scheduling approach.

Allocation of Australia's research dollars: does injury research funding reflect injury burden?

IntroductionBurden of disease estimates have been used to inform prioritisation of research needs. In Australia, National Health Priority Areas (NHPAs), of which injury prevention is one, have been identified as...

General Paediatric Surgery Provision

General Paediatric Surgery Provision

Optimum workforce strategy for production handling

The optimum workforce assignment for chip handling in computer–based manufacturing has been rebellious and crucial to industrial management. However, through OWS, Optimum Workforce Strategy, model proposed in this paper, this issue becomes realistically and concretely solvable. This study not only meditates the conception of balancing machine productivity and human ability into the objective, but also develops the step–by–step algorithm for optimizing the combinatorial problem to accomplish maximum profit. In addition, to extend the applicability of OWS model, the computerized decision tool written in VISUAL BASIC is comprehensively prepared in approaching the optimum solution of workforce allocation efficiently. Moreover, the versatility of OWS model is exemplified through a numerical study. This paper definitely contributes the applicable scheme of workforce allocation for production handling in manufacturing, and provides the valuable tool to conclusively optimize the profit of a machining project for operations research in today's machining industry with profound insight.

Optimum workforce scheduling under the (14, 21) days-off timetable

An efficient optimum solution is presented for a real-life employee day-soff scheduling problem with a three-week cycle. Over a given work cycle, each worker is given 14 successive workdays and 7 successive off days. This three-week days-off timetable is referred to as the (14, 21) schedule. Given different labor demands for each day of the week, the primary objective is to minimize the number of workers. The secondary objective is to reduce transportation cost by minimizing the number of active days-off patterns. The solution technique utilizes the dual LP solution to determine the minimum number of workers and feasible days-off assignments, without using linear or integer programming. The simple solution technique eliminates the need to use integer programming for this particular scheduling problem.

Optimum loading for GT/MRP manufacturing systems

A hierarchical planning procedure to utilize the potential advantages of coexistence of Group Technology (GT) and Material Requirement Planning (MRP) systems is presented. In addition, a multi-period linear programming model is proposed to determine the minimum cost loading schedule of manufacturing cells used in batch production environment. The proposed model provides the optimum work force for each cell over the planning horizon.

Sensitivity of Optimum Workforce Size to Employee Absenteeism in Stochastic Workload Situations

Abstract This paper presents the results of a simulation model developed to explore the relationship between unit cost and a number of primary production variables for a large warehouse operation of a major national retailer. The output of the simulation model includes a plot of total cost per completed unit for each combination of workforce size. Results indicate that under the conditions studied the total cost per completed unit is not particularly sensitive to workforce size and absenteeism patterns, and therefore insensitive to traditional managerial measures (such as over-staffing) to reduce these unit costs. This result is counter-intuitive and leads to the conclusion that the “fine turning” of staff levels as currently being attempted is perhaps not necessary.

Four Days, Forty Hours: A Case Study

In instances where the four-day/forty-hour workweek was adopted, it was done so largely by businessmen who failed to look at the new schedule critically—only to find that there was little theoretical or practical justification for it in most cases. Alternatives to the 4/40 schedule include flexible hours, optimum work force mix, and job enrichment.