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收集疼痛经历信息在预测背痛受伤工人领取福利时间方面的附加价值。

The Added Value of Collecting Information on Pain Experience When Predicting Time on Benefits for Injured Workers with Back Pain.

作者信息

Steenstra Ivan A, Franche Renée-Louise, Furlan Andrea D, Amick Ben, Hogg-Johnson Sheilah

机构信息

Institute for Work & Health, 481 University Ave., Suite 800, Toronto, ON, M5G 2E9, Canada.

Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.

出版信息

J Occup Rehabil. 2016 Jun;26(2):117-24. doi: 10.1007/s10926-015-9592-3.

Abstract

Objectives Some injured workers with work-related, compensated back pain experience a troubling course in return to work. A prediction tool was developed in an earlier study, using administrative data only. This study explored the added value of worker reported data in identifying those workers with back pain at higher risk of being on benefits for a longer period of time. Methods This was a cohort study of workers with compensated back pain in 2005 in Ontario. Workplace Safety and Insurance Board (WSIB) data was used. As well, we examined the added value of patient-reported prognostic factors obtained from a prospective cohort study. Improvement of model fit was determined by comparing area under the curve (AUC) statistics. The outcome measure was time on benefits during a first workers' compensation claim for back pain. Follow-up was 2 years. Results Among 1442 workers with WSIB data still on full benefits at 4 weeks, 113 were also part of the prospective cohort study. Model fit of an established rule in the smaller dataset of 113 workers was comparable to the fit previously established in the larger dataset. Adding worker rating of pain at baseline improved the rule substantially (AUC = 0.80, 95 % CI 0.68, 0.91 compared to benefit status at 180 days, AUC = 0.88, 95 % CI 0.74, 1.00 compared to benefits status at 360 days). Conclusion Although data routinely collected by workers' compensation boards show some ability to predict prolonged time on benefits, adding information on experienced pain reported by the worker improves the predictive ability of the model from 'fairly good' to 'good'. In this study, a combination of prognostic factors, reported by multiple stakeholders, including the worker, could identify those at high risk of extended duration on disability benefits and in potentially in need of additional support at the individual level.

摘要

目的 一些患有与工作相关的、已获赔偿的背痛的受伤工人在重返工作岗位时经历了令人困扰的过程。在早期研究中仅使用行政数据开发了一种预测工具。本研究探讨了工人报告的数据在识别那些背痛工人中处于较长时间领取福利更高风险的附加价值。方法 这是一项对2005年安大略省患有已获赔偿背痛的工人的队列研究。使用了 Workplace Safety and Insurance Board(WSIB)的数据。此外,我们检查了从一项前瞻性队列研究中获得的患者报告的预后因素的附加价值。通过比较曲线下面积(AUC)统计量来确定模型拟合的改善情况。结局指标是首次因背痛提出工伤赔偿申请期间领取福利的时间。随访时间为2年。结果 在1442名在4周时仍享有WSIB全额福利的工人中,113人也是前瞻性队列研究的一部分。在113名工人的较小数据集中,既定规则的模型拟合与先前在较大数据集中建立的拟合相当。在基线时加入工人的疼痛评分显著改善了该规则(与180天时的福利状态相比,AUC = 0.80,95%CI 0.68,0.91;与360天时的福利状态相比,AUC = 0.88,95%CI 0.74,1.00)。结论 尽管工人赔偿委员会常规收集的数据显示出一定的预测长时间领取福利的能力,但加入工人报告的经历性疼痛信息可将模型的预测能力从“相当好”提高到“好”。在本研究中,包括工人在内的多个利益相关者报告的预后因素组合可识别出残疾福利领取时间延长且可能在个人层面需要额外支持的高风险人群。

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