Using data science to measure the impact of opioid agonist therapy in patients admitted with Staphylococcus aureus bloodstream infections

使用数据科学测量阿片类激动剂治疗对金黄色葡萄球菌血流感染患者的影响

• 批准号: 10408760
• 负责人: David Goodman
• 金额: $ 20.3万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-06-15 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10408760
• 关键词: Acute suppurative arthritis due to bacteria; Address; Admission activity; Algorithms; Area; Award; Bacteremia; Bacteria; Bacterial Infections; Behavior; Blood; Brain; Buprenorphine; Cessation of life; Clinical Research; Coagulation Process; Communicable Diseases; Data; Data Science; Development; Diagnosis; Disease Outcome; Distant; Drug usage; Economic Burden; Electronic Health Record; Embolism; Endocarditis; Epidemic; Equipment; Evidence based practice; Future; Geography; Goals; Gold; HIV risk; Head; Health; Health Expenditures; Heart; Hepatitis C; Hepatitis C Transmission; Hospitalization; Hospitals; Immunosuppression; Incidence; Individual; Infection; Injecting drug user; International Classification of Disease Codes; Investigation; Joints; K-Series Research Career Programs; Kidney; Life; Location; Lung; Machine Learning; Measures; Medical; Medicine; Mentors; Methadone; Methods; Natural Language Processing; Outcome; Outpatients; Patient-Focused Outcomes; Patients; Performance; Persons; Pharmaceutical Preparations; Phenotype; Physicians; Population; Practice Guidelines; Predisposition; Recording of previous events; Records; Research; Research Personnel; Research Training; Science; Scientist; Sepsis; Services; Staphylococcus aureus; Statistical Methods; Stream; Testing; Thrombus; Time; Training Programs; Travel; United States; United States National Institutes of Health; Veterans Health Administration; Water; Work; addiction; base; biomedical data science; blood treatment; career; classification algorithm; cohort; data format; data repository; efficacy testing; electronic data; experience; heroin use; hospital readmission; improved; injection drug use; innovation; machine learning framework; mortality; multidisciplinary; novel; opioid agonist therapy; opioid epidemic; opioid injection; opioid misuse; opioid use; opioid use disorder; opioid user; overdose death; pathogenic bacteria; pathogenic virus; prescription opioid; responsible research conduct; screening; skin microbiota; substance use treatment; time interval; treatment services; trend; viral transmission

PROJECT SUMMARY/ABSTRACT This career development award will provide early career support for investigation of the management of infec- tious diseases in the setting of addiction in hospitals. The award will provide support for the candidate to develop expertise in the following areas: 1) addiction science research; 2) natural language processing; 3) machine learn- ing; 4) professional development; and 5) responsible conduct of research. For this, Dr. Goodman-Meza will be mentored by a multidisciplinary, cross-institutional team with expertise in addiction, infectious diseases, and data science. His primary mentor, Dr. Steve Shoptaw, has an extensive track record in addiction-related research and training of future independent investigators. His co-mentors include Dr. Alex Bui and Dr. Matthew B. Goetz. Dr. Bui is an expert in biomedical data science and heads NIH training programs in this field. Dr. Goetz has broad experience of productive infectious diseases clinical research within the Veterans Health Administration (VHA). The current opioid epidemic in the United States has been associated with an increase in infections, in particular hepatitis C and bacterial infections. Bacterial infections are the leading infectious diagnosis leading to hospitali- zation in individuals with an opioid use disorder (OUD), and incur significant healthcare expenditures. Despite the availability of opioid agonist therapy (OAT) in the form of methadone or buprenorphine, less than 20% of people with OUD actually receive OAT. Hospitalization for a bacterial infection may be an ideal time to initiate OAT, but the benefits of this practice are unknown. In this proposal, the candidate will assess the impact of initiating OAT in people who inject opioids admitted to the VHA due to a Staphylococcus aureus blood stream infection (bacteremia) – the most common bacterial pathogen among people who inject opioids. Using data already collected for 36,868 cases of S. aureus bacteremia (SAB) from the VHA electronic data repository, the candidate will address three research questions: 1) is a natural language processing algorithm (NLP) more ac- curate than a standard International Classification of Diseases (ICD) code-based approach at screening records to correctly identify individuals who inject opioids in a cohort of patients admitted with SAB; 2) what are the temporal and geographic trends of SAB in people who inject opioids and those who receive OAT at the facility- level; and 3) using a machine learning framework, what are the estimated impacts of OAT on patient centered outcomes – death, readmissions, leaving against medical advice, and subsequent outpatient engagement in OAT. These formative data will help the candidate to establish a productive early career as a physician-scientist and advise development of an OAT-delivery strategy to mitigate infectious complications of injection opioid use. Through this award, Dr. Goodman-Meza will establish himself as an expert physician-scientist at the intersection of infectious disease and addiction, poised to make significant contributions to this important area of medicine.

项目总结/摘要 这个职业发展奖将提供早期的职业支持，调查的管理infec- 在医院的成瘾环境中治疗各种疾病。该奖项将为候选人提供支持， 在以下领域的专业知识：1）成瘾科学研究; 2）自然语言处理; 3）机器学习- 4）专业发展; 5）负责任的研究行为。为此，古德曼-梅扎博士将 由一个多学科，跨机构的团队指导，该团队具有成瘾，传染病和数据方面的专业知识 科学他的主要导师史蒂夫·肖普托博士在成瘾相关研究方面有着广泛的记录， 培训未来的独立调查员。他的共同导师包括Alex Bui博士和Matthew B博士。戈茨博士 Bui是生物医学数据科学方面的专家，并领导NIH在该领域的培训项目。Goetz博士有广泛的 在退伍军人健康管理局（VHA）的生产性传染病临床研究的经验。 美国目前的阿片类药物流行与感染增加有关，特别是 丙型肝炎和细菌感染。细菌感染是导致住院的主要感染性诊断- 阿片类药物使用障碍（OUD）的个体中，并产生大量的医疗保健支出。尽管 美沙酮或丁丙诺啡形式的阿片类激动剂治疗（OAT）的可用性， OUD患者实际上接受OAT。细菌感染住院治疗可能是一个理想的时间开始 OAT，但这种做法的好处是未知的。在这份建议书中，候选人将评估 在因金黄色葡萄球菌血流而进入VHA的注射阿片类药物的患者中启动OAT 感染（菌血症）-注射阿片类药物的人中最常见的细菌病原体。使用数据 已经收集了36,868例S.金黄色葡萄球菌菌血症（SAB）从VHA电子数据库， 候选人将解决三个研究问题：1）是一个自然语言处理算法（NLP）更快- 在筛查记录时， 正确识别SAB患者队列中注射阿片类药物的个体; 2） 注射阿片类药物的人和在设施接受OAT的人中SAB的时间和地理趋势- 3）使用机器学习框架，OAT对以患者为中心的 结果-死亡，再入院，违背医嘱离开，以及随后的门诊参与， 燕麦。这些形成性的数据将帮助候选人建立一个富有成效的早期职业生涯作为一个医生科学家 并建议制定OAT输送策略，以减轻注射阿片类药物使用的感染性并发症。 通过这个奖项，古德曼-梅扎博士将确立自己作为一个专家的医学科学家在交叉点 传染病和成瘾，准备为这一重要的医学领域做出重大贡献。