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Development and evaluation of a categorization methodology for occupational back and shoulder injuries using claims data

机译:使用索赔数据开发和评估职业性背部和肩膀损伤的分类方法

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摘要

Administrative claims datasets have great potential for health services researchers who wish to evaluate patient care on a large scale across providers, but categorizing patients' primary health conditions from these data can be challenging. The goal of this work is to describe and evaluate a methodology to assign workers compensation claimants to meaningful groups within back and shoulder injuries using claims data. Claims data from a large multi-state workers compensation insurance dataset were used to assign eligible claimants to condition and subcondition groups using available ICD9 codes. Assignments were evaluated against body part indicators, severity indicators, resource utilization, and specific clinical interventions. Of the 575,967 claimants who met inclusion criteria, 54,066 claimants were designated as shoulder injuries and 118,772 were designated as back injuries. Within back and shoulder injuries, claimants were assigned to more specific groups known as subconditions. For both back and shoulder injuries, there were statistically significant differences between subconditions in several categories of resource utilization (p < 0.01 for all). For each of nine specific clinical interventions, the hypothesized corresponding subcondition had statistically significantly higher utilization than other subconditions (p < 0.01). This methodology could be an important tool to health services researchers who wish to target interventions or examine trends in cost and service utilization among meaningful groups of claimants.
机译:行政申索数据集对于希望在提供者之间大规模评估患者护理的卫生服务研究人员具有巨大的潜力,但是根据这些数据对患者的主要健康状况进行分类可能是一项挑战。这项工作的目的是描述和评估一种使用索赔数据将工伤赔偿索赔人分配到背部和肩膀受伤内有意义的群体的方法。来自大型多州工人补偿保险数据集的索赔数据用于使用可用的ICD9代码将合格的索赔人分配给条件组和子条件组。根据身体部位指标,严重程度指标,资源利用和特定的临床干预措施评估作业。在符合纳入标准的575,967名索赔人中,有54,066名索赔人被指定为肩伤,而118,772名被指定为背伤。在背部和肩部受伤中,索赔人被分配到称为子条件的更具体的组中。对于背部和肩部受伤,在几种资源利用类别中,子状况之间在统计学上均存在显着差异(所有p均<0.01)。对于九种具体的临床干预措施中的每一项,假设的相应子条件在统计学上均比其他子条件具有更高的利用率(p <0.01)。对于希望针对干预措施或研究有意义的索赔人群体中的成本和服务利用趋势的卫生服务研究人员而言,该方法可能是一种重要的工具。

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