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Deriving Cost-Efficient Strategies for Observational Assessments of Postural Loads | OMICS International | Abstract
ISSN: 2329-6879

Occupational Medicine & Health Affairs
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Research Article

Deriving Cost-Efficient Strategies for Observational Assessments of Postural Loads

Mahmoud Rezagholi*

Department of Business and Economic Studies, Division of Economics, University of Gävle, SE-801 76 Gävle, Sweden

*Corresponding Author:
Mahmoud Rezagholi
Division of Economics
Department of Business and Economic Studies
University of Gävle, SE-801 76 Gävle, Sweden
Tel: +46(0)26648757
Fax: +46(0)26648686
E-mail: [email protected]

Received date: June 03, 2014; Accepted date: August 25, 2014; Published date: August 28, 2014

Citation: Rezagholi M (2014) Deriving Cost-Efficient Strategies for Observational Assessments of Postural Loads. Occup Med Health Aff 2:174. doi: 10.4172/2329-6879.1000174

Copyright: © 2014 Rezagholi M. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Studies aimed at optimizing resource allocation between different sampling stages are characterized by both simplicity and incompleteness in optimization and economic analysis. The aim of this study was therefore to completely resolve the allocation problem for a four-stage strategy devoted to observational assessment of workrelated postural loads with the precision of the mean estimate considered as ‘output’. The derived demand functions for inputs to the four stages were used to derive functions for the minimized cost and the maximized precision of the assessment strategy. The application of the theoretical results to a working posture assessment study led to increased cost efficiency of the assessment strategy investigated in the study. Under the additional constraint that the optimal values must be integers, optimization of this strategy would result in either a 12% reduction in cost or a 7% increase in precision.

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