Spittal Matthew J, Grant Genevieve, O'Donnell Meaghan, McFarlane Alexander C, Studdert David M
Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia.
Law Faculty, Monash University, Melbourne, Victoria, Australia.
BMJ Open. 2018 Apr 28;8(4):e020803. doi: 10.1136/bmjopen-2017-020803.
We sought to develop prognostic risk scores for compensation-related stress and long-term disability using markers collected within 3 months of a serious injury.
Cohort study. Predictors were collected at baseline and at 3 months postinjury. Outcome data were collected at 72 months postinjury.
Hospitalised patients with serious injuries recruited from four major trauma hospitals in Australia.
332 participants who made claims for compensation for their injuries to a transport accident scheme or a workers' compensation scheme.
12-item WHO Disability Assessment Schedule and 6 items from the Claims Experience Survey.
Our model for long-term disability had four predictors (unemployed at the time of injury, history of a psychiatric disorder at time of injury, post-traumatic stress disorder symptom severity at 3 months and disability at 3 months). This model had good discrimination (R=0.37) and calibration. The disability risk score had a score range of 0-180, and at a threshold of 80 had sensitivity of 56% and specificity of 86%. Our model for compensation-related stress had five predictors (intensive care unit admission, discharged to home, number of traumatic events prior to injury, depression at 3 months and not working at 3 months). This model also had good discrimination (area under the curve=0.83) and calibration. The compensation-related stress risk score had score range of 0-220 and at a threshold of 100 had sensitivity of 74% and specificity of 75%. By combining these two scoring systems, we were able to identify the subgroup of claimants at highest risk of experiencing both outcomes.
The ability to identify at an early stage claimants at high risk of compensation-related stress and poor recovery is potentially valuable for claimants and the compensation agencies that serve them. The scoring systems we developed could be incorporated into the claims-handling processes to guide prevention-oriented interventions.
我们试图利用重伤后3个月内收集的指标，制定与赔偿相关压力和长期残疾的预后风险评分。
队列研究。预测指标在基线时和受伤后3个月收集。结局数据在受伤后72个月收集。
从澳大利亚四家主要创伤医院招募的重伤住院患者。
332名向交通事故赔偿计划或工伤赔偿计划提出受伤赔偿申请的参与者。
12项世界卫生组织残疾评定量表和索赔经验调查中的6项。
我们的长期残疾模型有四个预测指标（受伤时失业、受伤时患有精神疾病史、3个月时创伤后应激障碍症状严重程度和3个月时残疾情况）。该模型具有良好的区分度（R=0.37）和校准度。残疾风险评分范围为0至180，阈值为80时，灵敏度为56%，特异度为86%。我们的与赔偿相关压力模型有五个预测指标（入住重症监护病房、出院回家、受伤前创伤事件数量、3个月时抑郁和3个月时未工作）。该模型也具有良好的区分度（曲线下面积=0.83）和校准度。与赔偿相关压力风险评分范围为0至220，阈值为100时，灵敏度为74%，特异度为75%。通过结合这两个评分系统，我们能够识别出经历两种结局风险最高的索赔者亚组。
早期识别出面临与赔偿相关压力和恢复不佳高风险的索赔者的能力，对索赔者及其服务的赔偿机构可能具有重要价值。我们开发的评分系统可纳入索赔处理流程，以指导预防导向的干预措施。
