德里警方伤害监测第一信息报告评估：数据提取工具的开发与验证。
Evaluation of first information reports of Delhi police for injury surveillance: Data extraction tool development & validation.
机构信息
Department of Expenditure, Ministry of Finance, Government of India, New Delhi, India; Department of Global Health & Development, London School of Hygiene & Tropical Medicine, London, England.
Department of Population Health, London School of Hygiene & Tropical Medicine, London, England.
出版信息
Indian J Med Res. 2020 Oct;152(4):410-416. doi: 10.4103/ijmr.IJMR_442_20.
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.
背景与目的
政策制定者和卫生专业人员需要了解伤害发生的分布、模式、趋势和危险因素，以便制定减少伤害发生率的策略。印度警方的第一份信息报告（FIR）是获取此类信息的潜在来源。本研究的目的是确定推荐用于伤害监测的最小数据集（MDS），开发从 FIR 中提取数据的工具，评估 FIR 是否包含该 MDS，并评估该工具的评分者间可靠性。
方法
这是一项对 2017 年向德里警方报告的事件进行的横断面研究。进行了系统的文献检索，以确定推荐用于伤害监测的 MDS。设计了一个用于数据提取的工具，并使用 Cohen's kappa 和 FIR 中每个 MDS 数据项的可用百分比来评估其评分者间可靠性。
结果
文献综述确定了 24 份推荐 12 个 MDS 用于伤害监测的报告。FIR 中完整记录了以下五个 MDS 的信息：性别/性别（100%）、受伤日期（100%）、受伤时间（100%）、伤害事件地点（100%）和意图（100%）。对于以下七个 MDS，信息不完整：姓名（93.1%）、年龄（67.2%）、职业（32.8%）、住所（86.2%）、受伤人员的活动（86.2%）、伤害原因（93.1%）和伤害性质（41.4%）。数据提取工具的评分者间可靠性被发现几乎是完美的。
解释与结论
可以从 FIR 中可靠地提取伤害信息。尽管 FIR 并不总是包含 MDS 的完整信息，但如果可以推断出缺失的数据，这些数据可以成为伤害监测系统的基础。然而，使用 FIR 进行伤害监测可能会受到 FIR 确定的伤害人群代表性的限制。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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