Lehna Carlee, Furmanek Stephen, Hanchette Carol
University of Louisville School of Nursing, Louisville, KY, United States.
University of Louisville Department of Geography and Geosciences, Louisville, KY, United States.
Burns. 2018 Sep;44(6):1585-1590. doi: 10.1016/j.burns.2018.02.002. Epub 2018 Mar 2.
We assessed whether a home fire safety intervention targeting families with newborn children in Jefferson County, Kentucky, reached those at severe risk using a cartographic model. Demographic and economic factors of 61 families were compared by census tract. Using geographic information systems (GIS), families were assigned a risk level (low, medium, high, or severe) based on the risk model. Families who participated differed from census tracts in that of being minority race (p=0.01). The median risk category of the families was medium risk. Sixty-five tracts were identified as high or severe risk and in need of future intervention. The model yielded a way to prioritize at-risk families. GIS is a useful tool for examining whether prevention interventions reached those in the severe risk category.
我们使用制图模型评估了一项针对肯塔基州杰斐逊县有新生儿家庭的家庭消防安全干预措施,是否覆盖了面临严重风险的家庭。按普查区比较了61个家庭的人口和经济因素。利用地理信息系统(GIS),根据风险模型为家庭分配了一个风险等级(低、中、高或严重)。参与干预的家庭与普查区的不同之处在于其为少数族裔(p=0.01)。这些家庭的风险类别中位数为中度风险。确定了65个普查区为高风险或严重风险,需要未来进行干预。该模型提供了一种对高危家庭进行优先排序的方法。GIS是一种用于检查预防干预措施是否覆盖严重风险类别的有用工具。