Bentivegna Kathryn, Durante Amanda, Livingston Nina, Hunter Amy A
Department of Community Medicine and Healthcare, University of Connecticut, Farmington, Connecticut.
Department of Pediatrics, University of Connecticut School of Medicine, Connecticut Children's Medical Center, Hartford, Connecticut.
J Emerg Med. 2019 Jun;56(6):719-726. doi: 10.1016/j.jemermed.2019.03.022. Epub 2019 Apr 22.
Child sexual abuse (CSA) is poorly identified due to its hidden nature and difficulty surrounding disclosure. Surveillance using emergency department (ED) data may identify victims and provide information on their demographic profile.
Study aims were to calculate the prevalence of visits assigned an explicit or suggestive medical diagnosis code (International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM]) for CSA and compare the demographic profile of ED visits by coding type.
This study examined ED data for children < 10 years of age in Connecticut from 2011 to 2014. Cases involving CSA were identified using explicit and suggestive ICD-9-CM codes and age qualifiers previously established in the literature, and compared across visit characteristics (age, race/ethnicity, sex, and primary insurance payer, and town group).
ICD-9-CM codes for explicit CSA were identified in 110 ED visits, or 1.7 per 10,000 total ED visits. Inclusion of ICD-9-CM codes for suggestive CSA identified an additional 630 visits (9.7 per 10,000 visits). Suggestive codes identified proportionally more visits of younger (50% vs. 38%) and male (35% vs. 22%) children, compared with the explicit code (p < 0.05).
This study demonstrates one method for identifying CSA cases, which has the potential to increase surveillance of victims in the ED. Results imply that explicit codes alone may overlook most cases, whereas use of suggestive codes may identify additional cases, and proportionally more young and male victims. As the health consequences of CSA are severe, innovative forms of surveillance must be explored to detect a higher number of cases and improve the clinical care of patients.
儿童性虐待(CSA)因其隐蔽性以及披露方面的困难而难以被识别。利用急诊科(ED)数据进行监测可能会识别出受害者,并提供有关其人口统计学特征的信息。
研究目的是计算被分配明确或暗示性医学诊断代码(《国际疾病分类,第九版,临床修订本》[ICD-9-CM])的CSA就诊患病率,并按编码类型比较急诊科就诊的人口统计学特征。
本研究检查了2011年至2014年康涅狄格州10岁以下儿童的急诊科数据。使用文献中先前确定的明确和暗示性ICD-9-CM代码及年龄限定词来识别涉及CSA的病例,并对就诊特征(年龄、种族/民族、性别、主要保险支付方和城镇分组)进行比较。
在110次急诊科就诊中识别出明确CSA的ICD-9-CM代码,即每10000次急诊科就诊中有1.7次。纳入暗示性CSA的ICD-9-CM代码又识别出630次就诊(每10000次就诊中有9.7次)。与明确代码相比,暗示性代码识别出的年龄较小(50%对38%)和男性(35%对22%)儿童就诊比例更高(p<0.05)。
本研究展示了一种识别CSA病例的方法,该方法有可能加强对急诊科受害者的监测。结果表明,仅使用明确代码可能会忽略大多数病例,而使用暗示性代码可能会识别出更多病例,且年龄较小和男性受害者的比例相对更高。由于CSA对健康造成严重后果,必须探索创新形式的监测,以发现更多病例并改善患者的临床护理。