Characterization of Chronic Pain and its Biopsychosocial Mechanisms in Lupus using Electronic Health Records

多达1亿美国人生活在持续的疼痛中，每年花费6350亿美元。在美国 超过20万人患有SLE，这是一种多器官慢性炎症性风湿性疾病， 对女性和少数民族造成不成比例影响的参与。患有慢性疾病，如 SLE带来了多重挑战。疼痛是SLE患者自我报告的常见症状， 疾病的症状。尽管治疗进展，疼痛仍然是最突出的，未解决的病人 投诉SLE疼痛的管理最近变得更具挑战性，因为令人担忧的是， 滥用阿片类药物造成的成瘾流行和死亡率。估计31-46%的SLE患者使用 处方阿片类药物在一项研究中，70%的阿片类药物使用者使用时间≥1年， 同时服用≥2种阿片类药物。SLE患者的发病率几乎是一般患者的两倍。 阿片类药物相关过量住院治疗的人群。然而，减少阿片类药物滥用的努力不能 如果没有对潜在的临床研究的详细了解和持续投资， 产生和维持慢性疼痛的机制。描述SLE慢性疼痛负担的特征是 至少有两项罪名首先，我们缺乏关于SLE慢性疼痛的患病率和负担的数据， 部分原因是缺乏可靠的方法来识别电子设备中具有临床显著疼痛的患者， 健康记录（EHR）。其次，迫切需要了解生物心理社会机制， 与SLE患者疼痛体验的相关性。在这个指导职业发展奖（K 01），博士蒂蒂洛拉 Falasinnu将使用计算方法来增加对临床管理慢性 使用EHR的SLE疼痛。在目标1中，Falasinnu博士将开发一种计算慢性疼痛表型 使用从EHR中提取的诊断代码、疼痛评分、叙述性临床记录和药物的算法 两个大型医疗保健系统（n~ 2，400）。然后她将使用该算法来估计慢性疼痛的患病率 在基于人群的登记研究中（n~ 76，000）。在目标2中，Falasinnu博士将全面表型 慢性疼痛的生物心理社会相关性，使用现有的约500例SLE患者登记， 多学科疼痛中心在整个奖项中，Falasinnu博士将以她的博士培训为基础， 流行病学家和生物统计学家，以发展生物医学信息学的新技能， 医学研究。这些技能将包括使用EHR和注册表数据，机器学习和自然 语言处理，疼痛科学，资助写作和科学交流。通过课程，临床 在疼痛医学诊所观察，指导，以及外部会议和研讨会，Falasinnu博士将 获得申请她的第一个R 01所需的技能，并追求终身制首席研究员的职业生涯。

Up to 100 million Americans live with ongoing pain, costing $635 billion annually. In the United States, there are more than 200,000 people living with SLE, a chronic inflammatory rheumatic disease with multi-organ involvement that disproportionately affects females and racial minorities. Living with a chronic disease such as SLE confers multiple challenges. Pain is a frequent self-reported symptom in SLE and is often one of the first symptoms of the disease. Despite treatment advances, pain remains the most prominent, unaddressed patient complaint. The management of pain in SLE has recently become more challenging because of the alarming epidemic of addiction and mortality attributed to opioid misuse. An estimated 31-46% of patients with SLE use prescription opioids. In one study, 70% of individuals using opioids used them for ≥1 year, and 22% were taking ≥2 opioid medications at the same time. Patients with SLE are nearly twice as likely as the general population to have opioid-related overdose hospitalizations. However, efforts to mitigate opioid misuse cannot be achieved without a detailed understanding and sustained investment in clinical research on the underlying mechanisms that produce and maintain chronic pain. Characterizing the burden of chronic pain in SLE is challenging on at least two counts. First, we lack data on the prevalence and burden of chronic pain in SLE, partly due to the absence of reliable approaches to identify patients with clinically significant pain in electronic health records (EHR). Second, there is a critical need to understand the biopsychosocial mechanisms and correlates that drive the pain experience in SLE. In this mentored career development award (K01), Dr. Titilola Falasinnu will use computational methods to increase the understanding of the clinical management chronic pain in SLE using EHR. In Aim 1, Dr. Falasinnu will develop a computational chronic pain phenotyping algorithm using diagnostic codes, pain scores, narrative clinic notes and medications extracted from the EHRs of two large healthcare systems (n~2,400). She will then use the algorithm to estimate chronic pain prevalence in a population-based registry (n~76,000). In Aim 2, Dr. Falasinnu will comprehensively phenotype biopsychosocial correlates of chronic pain using an existing registry of ~500 patients with SLE attending a multi-disciplinary pain center. Throughout the award, Dr. Falasinnu will build on her doctoral training as an epidemiologist and biostatistician to develop new skills in biomedical informatics to conduct impactful pain medicine research. These skills will include working with EHR and registry data, machine learning and natural language processing, pain science, grant-writing, and scientific communication. Through coursework, clinical observation in pain medicine clinics, mentorship, and external conferences and workshops, Dr. Falasinnu will gain the skills needed to apply for her first R01 and pursue a career as a tenure-track principal investigator.