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Evaluation of first information reports of Delhi police for injury surveillance: Data extraction tool development & validation

机译:德里警察对伤害监测的第一条信息报告评估:数据提取工具开发与验证

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Background & objectives: Policymakers and health professionals need to know the distribution, patterns, trends and risk factors of injury occurrence to develop strategies that reduce the incidence of injuries. The first information report (FIR) of Indian police is one potential source of this information. The aims of this study were to identify the minimum data set (MDS) recommended for injury surveillance, to develop a tool for data extraction from FIRs, to evaluate whether FIRs contain this MDS and to assess the inter-rater reliability of the tool. Methods: This was a cross-sectional study of incidents reported to Delhi Police in 2017. A systematic literature search was conducted to identify the MDS recommended for injury surveillance. A tool was designed for extraction of data, and its inter-rater reliability was assessed using Cohen's kappa and the percentage availability of each MDS data item in the FIRs, was calculated. Results: The literature review identified 24 reports that recommended 12 MDS for injury surveillance. The FIRs contained complete information on the following five MDS: sex/gender (100%), date of injury (100%), time of injury (100%), place of injurious event (100%) and intent (100%). For the following seven MDS, information was not complete: name (93.1%), age (67.2%), occupation (32.8%), residence (86.2%), activity of the injured person (86.2%), cause of the injury (93.1%) and nature of the injury (41.4%). The inter-rater reliability of the data extraction tool was found to be almost perfect. Interpretation & conclusions: Information on injuries can be reliably extracted from FIRs. Although FIRs do not always contain complete information on the MDS, if missing data are imputed, these could form the basis of an injury surveillance system. However, use of FIRs for injury surveillance could be limited by the representativeness of injuries ascertained by FIRs to the population. FIRs thus have the potential to become an important component of an integrated injury surveillance system.
机译:背景和目标:政策制定者和卫生专业人士需要了解伤害发生的分配,模式,趋势和危险因素,以发展减少损伤发病率的策略。印度警察的第一个信息报告(FIR)是此信息的一个潜在来源。本研究的目的是识别推荐用于伤害监测的最小数据集(MDS),用于开发来自FIR的数据提取工具,以评估FIR是否包含此MDS并评估该工具的帧间间可靠性。方法:这是2017年对德里警察报告的事件的横断面研究。进行了系统文献搜索,以确定推荐伤害监测的MDS。设计用于提取数据的工具,并使用Cohen的Kappa评估其帧间间可靠性,并计算了冷杉中每个MDS数据项的百分比可用性。结果:文献综述确定了24个报告,推荐12 MDS伤害监测。 FIRS包含以下五个MDS的完整信息:性/性别(100%),伤害日期(100%),受伤时间(100%),有害事件的地方(100%)和意图(100%)。对于以下七个MD,信息未完成:姓名(93.1%),年龄(67.2%),占用(32.8%),居住(86.2%),受伤者的活动(86.2%),损伤原因( 93.1%)和损伤的性质(41.4%)。发现数据提取工具的帧间间可靠性几乎完美。解释与结论:有关伤害的信息可以从冷杉可靠地提取。虽然FIRS并不总是包含关于MDS的完整信息,但如果缺失数据,则可以构成伤害监视系统的基础。然而,对伤害监测的冷杉可能受到在杉木对人口确定的伤害的代表性的限制。因此,FIR有可能成为综合伤害监测系统的重要组成部分。

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