Royal Australian Navy, Canberra, BC, Australian Capital Territory, Australia.
Intern Med J. 2012 Aug;42(8):924-7. doi: 10.1111/j.1445-5994.2011.02639.x.
The research question is: is it possible to predict, at the time of workers' compensation claim lodgement, which workers will have a prolonged return to work (RTW) outcome? This paper illustrates how a traditional analytic approach to the analysis of an existing large database can be insufficient to answer the research question, and suggests an alternative data management and analysis approach.
This paper retrospectively analyses 9018 workers' compensation claims from two different workers' compensation jurisdictions in Australia (two data sets) over a 4-month period in 2007. De-identified data, submitted at the time of claim lodgement, were compared with RTW outcomes for up to 3 months. Analysis consisted of descriptive, parametric (analysis of variance and multiple regression), survival (proportional hazards) and data mining (partitioning) analysis.
No significant associations were found on parametric analysis. Multiple associations were found between the predictor variables and RTW outcome on survival analysis, with marked differences being found between some sub-groups on partitioning--where diagnosis was found to be the strongest discriminator (particularly neck and shoulder injuries). There was a consistent trend for female gender to be associated with a prolonged RTW outcome. The supplied data were not sufficient to enable the development of a predictive model.
If we want to predict early who will have a prolonged RTW in Australia, workers' compensation claim forms should be redesigned, data management improved and specialised analytic techniques used.
研究问题是：是否有可能在工人提出赔偿申请时预测哪些工人将有较长的重返工作岗位（RTW）结果？本文说明了传统的分析方法在分析现有大型数据库时可能存在不足，并提出了一种替代的数据管理和分析方法。
本研究回顾性分析了澳大利亚两个不同工人赔偿管辖区（两个数据集）在 2007 年 4 个月期间的 9018 例工人赔偿索赔。在提出索赔时提交的匿名数据与最多 3 个月的 RTW 结果进行了比较。分析包括描述性分析、参数分析（方差分析和多元回归分析）、生存分析（比例风险分析）和数据挖掘分析（分区分析）。
参数分析未发现显著关联。生存分析发现预测变量与 RTW 结果之间存在多种关联，分区分析发现一些亚组之间存在明显差异，其中诊断是最强的判别因素（特别是颈部和肩部损伤）。女性性别与延长 RTW 结果呈一致趋势相关。所提供的数据不足以开发预测模型。
如果我们要在澳大利亚早期预测谁将有较长的 RTW，就需要重新设计工人赔偿申请表、改进数据管理并使用专门的分析技术。
