The impact of COVID-19 on child maltreatment-related medical encounters and system responses using linked administrative data

项目概要/摘要： 随着学校和日托设施关闭，失业率因新冠肺炎而飙升- 19大流行，专家们担心不仅虐待儿童的发生率增加， 新发生或一再发生的虐待案件没有被发现，因为三分之二的 向儿童保护服务机构报告的工作由专业人员负责。链接的行政数据 (i.e.,为提供服务（包括卫生和儿童保护）而收集的记录可 通过将CPS数据库与 医疗记录医疗记录已被确定为一个有用的数据源， 虐待儿童。本申请旨在确定COVID-19是否以及如何 大流行影响了与虐待儿童有关的医疗遭遇的发生率， 系统对确诊的虐待案件作出反应。理由是虐待 对儿童的重大影响，如果在此期间虐待增加， 重要的是分配资源来解决这种有害的创伤形式。拟议 研究将利用自然实验的优势，专注于两个特定的目标：1）比较 COVID-19之前和期间儿童虐待相关医疗事件的发生率; 和2）确定社会和法律的干预/系统对诊断的医疗 在大流行病之前和期间遭遇虐待儿童的情况。对于第一个目标， 中断的时间序列将被用来确定频率的诊断虐待， 初级保健、急诊科和住院医疗接触。第二 目的，中断时间序列和逻辑回归将用于确定百分比， 向CPS报告诊断的虐待相关医疗遭遇的可能性。的 拟议的研究是创新的，因为它使用了来自多个来源的数据，包括 几种医疗事故。这项拟议的研究意义重大，因为 虐待的后果很严重，但难以衡量。结果将与稳健性一致 经验证据表明，COVID-19大流行是否增加了儿童的发病率和严重程度 与虐待相关的医疗遭遇，并改变了社会和法律的干预措施 对这种医疗事故的反应。最终，这些知识有可能识别 社区一级的事件如何影响虐待儿童，为公共政策提供信息， 分配、专业培训和未来研究。

Project Summary/Abstract: With schools and daycare facilities closed and unemployment rates soaring due to the COVID- 19 pandemic, experts worry not only that the incidence of child maltreatment has increased but that that new or recurrent cases of maltreatment have gone undetected because two-thirds of reports to child protective services (CPS) are made by professionals. Linked administrative data (i.e., records collected for the provision of services, including health and child protection) can overcome the challenges of relying solely on CPS reports by joining the CPS database with medical records. Medical records have been identified as a useful data source for measuring child maltreatment. The objective of this application is to determine if and how the COVID-19 pandemic has impacted the incidence of child maltreatment-related medical encounters and the system responses to diagnosed cases of maltreatment. The rationale is maltreatment has significant identified impacts on children and if maltreatment has increased during this time, it will be important to allocate resources to address this detrimental form of trauma. The proposed study will take advantage of a natural experiment to focus on two specific aims: 1) Compare the incidence rates of child maltreatment-related medical encounters, before and during COVID-19; and 2) Determine the social and legal interventions/system responses to diagnosed medical encounters of child maltreatment before and during the pandemic. For the first aim, an interrupted time series will be used to identify the frequency of diagnosed maltreatment in primary care, emergency department, and hospitalization medical encounters. For the second aim, interrupted time series and logistic regression will be used to determine the percentage and likelihood of diagnosed maltreatment-related medical encounters being reported to CPS. The proposed research is innovative because it uses data from multiple sources and includes several types of medical encounters. The proposed research is significant because maltreatment is highly consequential but difficult to measure. Results will identify with robust empirical evidence if the pandemic COVID-19 has increased the incidence and severity of child maltreatment-related medical encounters and changed the social and legal interventions in response to such medical encounters. Ultimately, such knowledge has the potential to identify how community-level events impact child maltreatment, informing public policy, resource allocation, professional training, and future research.