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开发一种计算政策模型,用于比较工作场所伤害后康复的补偿方案政策的效果。

Development of a Computational Policy Model for Comparing the Effect of Compensation Scheme Policies on Recovery After Workplace Injury.

机构信息

Transport, Health and Urban Design Research Hub, The University of Melbourne, Melbourne, Australia.

出版信息

J Occup Rehabil. 2022 Jun;32(2):241-251. doi: 10.1007/s10926-022-10035-w. Epub 2022 May 10.

Abstract

Introduction The direct comparison of real-world workers' compensation scheme management policies and their impact on aspects of scheme performance such as health and return to work outcomes, financial sustainability, and client experience metrics is made difficult through existing differences in scheme design that go beyond the factors of interest to the researcher or policymaker. Disentangling effects that are due purely to the result of policy and structural differences between schemes or jurisdictions to determine 'what works' can be difficult. Method We present a prototype policy exploration tool, 'WorkSim', built using an agent-based model and designed to enable workers' compensation system managers to directly compare the effect of simulated policies on the performance of workers compensation systems constructed using agreed and transparent principles. Results The utility of the model is demonstrated through and case-study comparison of overall scheme performance metrics across 6 simple policy scenarios. Discussion Policy simulation models of the nature described can be useful tools for managers of workplace compensation and rehabilitation schemes for trialing policy and management options ahead of their real-world implementation.

摘要

简介 由于现实世界中的工人赔偿计划管理政策之间存在差异,这些差异超出了研究人员或政策制定者关注的因素,因此很难对其进行直接比较,并评估这些政策对计划绩效(如健康和重返工作岗位的结果、财务可持续性以及客户体验指标)方面的影响。要想确定“什么有效”,就必须理清纯粹是由于政策和计划或司法管辖区之间的结构差异所导致的影响。 我们提出了一种原型政策探索工具“WorkSim”,它是使用基于代理的模型构建的,旨在使工人赔偿系统管理人员能够直接比较模拟政策对使用商定和透明原则构建的工人赔偿系统性能的影响。 结果 通过对 6 种简单政策场景下的总体计划绩效指标进行案例研究比较,展示了模型的实用性。 讨论 描述性质的政策模拟模型可以成为工作场所赔偿和康复计划管理人员的有用工具,他们可以在实际实施之前试用政策和管理选项。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5eb2/9232456/7f61e6d65a3b/10926_2022_10035_Fig1_HTML.jpg

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