伤害统计数据质量:挑战与对策  

Quality of Injury Data:Challenges and Solutions

作　　者：胡国清[1] HU Guo-qing(Department of Epidemiology and Health Statistics,Xiangya School of Public Health,Central South University Changsha 410013,China)

机构地区：[1]中南大学湘雅公共卫生学院流行病与卫生统计学系,长沙410013

出　　处：《伤害医学(电子版)》2025年第1期59-62,共4页Injury Medicine(Electronic Edition)

基　　金：国家重点研发计划(2022YFC3603000)。

摘　　要：数据质量直接影响到研究结果的准确性和干预措施效果的评价。高质量的数据可以帮助准确地识别伤害风险因素,客观评估预防措施的效果,而低质量数据可能会导致错误的分析结果,进而对伤害预防决策及其实践工作产生负面影响。目前伤害预防与控制领域使用的数据主要包括官方统计数据、研究数据和非结构化数据三种,本文针对当前伤害统计数据质量存在的十个突出挑战予以简要介绍,并提出相应的应对策略。The quality of collected data directly affects the accuracy of research results and the evaluation of intervention effectiveness.High-quality data can be used to accurately identify injury risk factors and to objectively evaluate effectiveness of preventive measures,while low-quality data can lead to incorrect results,which will have a negative impact on decision-making and practice.At present,there are mainly three types of data used in injury prevention and control:official statistics,research,and unstructured data.This study introduces nine major challenges concerning the quality of injury data and proposes ten strategies to address the challenges.

关 键 词：伤害 统计数据 数据质量 

分 类 号：R195[医药卫生—卫生统计学]