Automated Substance Use Detection from Electronic Health Records in the Pediatric Setting

项目摘要 大多数患有物质使用障碍(SUD)的成年人报告说，在青少年时期就开始使用物质； 因此，青春期是筛选物质使用开始和实施的关键时期。 防止或减少使用的干预措施。医疗保健系统优先考虑物质使用筛查，包括 在青春期，目标是确定何时发生药物使用并监测使用情况 确定必要的干预措施。不幸的是，这些信息中的大部分都是以非结构化的形式记录的 临床记录，使提供者难以监测青少年在药物使用方面的变化 相遇。已发表的研究还表明，对药物使用筛查(如实验室测试)存在偏见 是存在的。这两个限制都阻止了电子健康记录(EHR)数据被用于研究上下文和 青少年人群中使用药物的后果。而不是改变临床医生的行为，这 这项研究可能具有挑战性，它利用自动人工智能算法来检测物质使用情况 在电子病历中筛选事件和结果。我们的工作可以允许当前供应商主导的偏好和 继续使用物质使用文件的做法，同时增加对文件的获取 信息和减轻筛查偏见，以避免医疗保健领域的种族主义和不公平永久化。结果, 这项研究有可能有助于长期努力，有针对性地预防、干预和转诊 在青春期进行治疗，并最终降低整个生命周期内的SUD风险。我们的工作将会完成 通过实现以下目标：目标1：检查自动物质使用的概括性 接受良好儿童和/或门诊专科治疗的约5,000名青少年患者的检测系统 查访，最大限度地扩大最有可能进行物质使用筛查的情况；和目标2：评估 按性别、保险类型划分的药物使用筛查和阳性筛查结果的差异 种族和民族状况，以及临床背景，评估是否在结构化数据中检测到偏见， 非结构化数据，或同时使用这两个数据源。此外，参与性研究原则将用于征集 来自临床医生和研究人员的关于将研究结果应用于临床护理的反馈。到年底的时候 在资助期内，我们将对自动化系统的性能进行验证，评估在确定偏差方面 物质使用筛查结果，并从临床医生对临床护理应用的反馈中获得见解。

Project Summary The majority of adults with substance use disorders (SUD) report beginning to use substances as adolescents; thus, adolescence represents a critical time for screening of substance use initiation and implementing interventions to prevent or reduce use. The healthcare system prioritizes substance use screening, including during adolescence, with the goal of identifying when substance use is occurring and monitoring use to determine necessary intervention. Unfortunately, the majority of this information is documented in unstructured clinical notes, making it difficult for providers to monitor change in substance use for an adolescent over encounters. Published studies also suggest bias around substance use screening such as laboratory tests exists. Both limitations prevent electronic health record (EHR) data from being used to study the contexts and consequences of substance use in populations of adolescents. Rather than changing clinician behavior, which can be challenging, this study utilizes automated artificial intelligence algorithms to detect substance use screening occurrences and results in the EHRs. Our work could allow current provider-led preferences and practices in substance use documentation to continue while simultaneously increasing access to documented information and mitigating screening bias to avoid perpetuating racism and inequity in healthcare. As a result, the study has the potential to aid in long-term efforts to target prevention, intervention, and referral for treatment in adolescence and ultimately reduce risk of SUD across the lifespan. Our work will be completed through accomplishing the following aims: Aim 1: Examine the generalizability of an automated substance use detection system in a sample of ~5,000 adolescent patients who receive well child and/or outpatient specialty visits, maximizing contexts where substance use screening is most likely to occur; and Aim 2: Assess differences in substance use screening and positive screening results by gender, insurance type, minoritized race and ethnicity status, and clinical context, evaluating whether bias is detected in structured data, unstructured data, or both data sources. In addition, participatory research principles will be used to solicit feedback from clinicians and researchers about the application of findings to clinical care. By the end of the funding period, we will have validated the performance of the automated system, assessed bias in identifying substance use screening results, and gained insights from clinician feedback about application to clinical care.