Improving identification of crash injuries: Statewide integration of hospital discharge and crash report data.
Improving identification of crash injuries: Statewide integration of hospital discharge and crash report data.
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DOI：
10.1080/15389588.2022.2083612
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发表时间：
2022
影响因子：
2
通讯作者：
Curry, Allison E.
中科院分区：
文献类型：
--
作者：
Lombardi, Leah R.;Pfeiffer, Melissa R.;Metzger, Kristina B.;Myers, Rachel K.;Curry, Allison E.
关键词：
提供完整和准确的碰撞伤害数据对于预防和干预工作至关重要。仅仅依靠医院出院数据或警方的事故报告可能会导致对受伤人数的片面低估。将医院数据与事故报告联系起来，可以更有力地识别受伤情况，并了解在分析一个来源时可能遗漏哪些人群。我们使用新泽西安全和健康结果（NJ-SHO）数据仓库来检查两个数据源中确定的整个车祸受伤人口的比例，总体和年龄，种族/民族，性别，受伤严重程度和道路使用者类型。我们使用了来自NJ-SHO仓库的2016-2017年数据。我们通过应用ICD-10-CM损伤的外部原因矩阵，在出院数据中识别出涉及车祸的个体。在涉及碰撞的个人中，我们确定那些与受伤或疼痛相关的诊断代码为受伤。我们还通过事故报告数据确定了涉及事故的个人，并使用KABCO量表确定了受伤情况。我们联合检查了这两个来源;如果事故报告的日期比入院日期早不超过两天，则医院出院数据中的伤害被记录为与事故报告数据中发现的伤害相同。在研究期间，共有262，338名涉及碰撞的个人在医院出院数据或碰撞报告中记录了受伤;根据医院出院数据，168，874人受伤，164，158人在碰撞报告数据中受伤。只有70，694人（26.9%）在两种来源中受伤。我们观察到年龄，种族/民族，受伤严重程度和道路使用者类型的差异：出院数据捕获了65岁以上，黑人或西班牙裔，严重程度较高的受伤者以及骑自行车或骑摩托车的人的更大份额。每个数据源单独收集了大约三分之二的车祸受伤人口;仅一个数据源就遗漏了大约三分之一的受伤人员。每个来源都低估了某些群体的人数，因此仅依靠一个来源可能无法进行有针对性的预防和干预工作。
The availability of complete and accurate crash injury data is critical to prevention and intervention efforts. Relying solely on hospital discharge data or police crash reports may result in a biased undercount of injuries. Linking hospital data with crash reports may allow for a more robust identification of injuries and an understanding of which populations may be missed in an analysis of one source. We used the New Jersey Safety and Health Outcomes (NJ-SHO) data warehouse to examine the share of the entire crash-injured population identified in each of the two data sources, overall and by age, race/ethnicity, sex, injury severity, and road user type. We utilized 2016-2017 data from the NJ-SHO warehouse. We identified crash-involved individuals in hospital discharge data by applying the ICD-10-CM external cause of injury matrix. Among crash-involved individuals, we identified those with injury- or pain-related diagnosis codes as being injured. We also identified crash-involved individuals via crash report data and identified injuries using the KABCO scale. We jointly examined the two sources; injuries in the hospital discharge data were documented as being related to the same crash as injuries found in the crash report data if the date of the crash report preceded the date of hospital admission by no more than two days. In total, there were 262,338 crash-involved individuals with a documented injury in the hospital discharge data or on the crash report during the study period; 168,874 had an injury according to hospital discharge data, and 164,158 had an injury in crash report data. Only 70,694 (26.9%) had an injury in both sources. We observed differences by age, race/ethnicity, injury severity, and road user type: hospital discharge data captured a larger share of those ages 65+, those who were Black or Hispanic, those with higher severity injuries, and those who were bicyclists or motorcyclists. Each data source in isolation captures approximately two-thirds of the entire crash-injured population; one source alone misses approximately one-third of injured individuals. Each source undercounts people in certain groups, so relying on one source alone may not allow for tailored prevention and intervention efforts.
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DOI：
10.1080/17457300.2018.1476385
发表时间：
2019-01-02
影响因子：
2.3
作者：
Kamaluddin, Noor Azreena;Abd Rahman, Mohd Faizal;Varhelyi, Andras
通讯作者：
Varhelyi, Andras
影响因子：
3.7
作者：
Glerum, Kimberly M.;Zonfrillo, Mark R.
通讯作者：
Zonfrillo, Mark R.
影响因子：
2
作者：
Loftis, Kathryn L.;Price, Janet P.;Brennan, Maureen
通讯作者：
Brennan, Maureen
影响因子：
4.5
作者：
Hamann C;Peek-Asa C;Butcher B
通讯作者：
Butcher B
DOI：
10.1097/ede.0000000000001314
发表时间：
2021-03-01
期刊：
Epidemiology (Cambridge, Mass.)
影响因子：
--
作者：
Labgold K;Hamid S;Shah S;Gandhi NR;Chamberlain A;Khan F;Khan S;Smith S;Williams S;Lash TL;Collin LJ
通讯作者：
Collin LJ