Bonney Wilfred, Price Sandy F, Miramontes Roque
Data Management, Statistics and Evaluation Branch, Division of Tuberculosis Elimination, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Office of Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Public Health Informatics Fellowship Program, Division of Scientific Education and Professional Development, Center for Surveillance, Epidemiology, and Laboratory Services, Centers for Disease Control and Prevention, Atlanta, GA, USA.
AMIA Jt Summits Transl Sci Proc. 2019 May 6;2019:686-695. eCollection 2019.
Drug-resistant tuberculosis (TB) remains a public health threat to the United States and worldwide control of TB. Rapid and reliable drug susceptibility testing (DST) is essential for aiding clinicians in selecting an optimal treatment regimen for TB patients and to prevent ongoing transmission. Growth-based DST results for culture-confirmed cases are routinely reported to the U.S. Centers for Disease Control and Prevention through the National TB Surveillance System (NTSS). However, the NTSS currently lacks the capacity and functionality to accept laboratory results from advanced molecular methods that detect mutations associated with drug resistance. The objective of this study is to design and implement novel comprehensive data exchange formats that utilize the Health Level Seven (HL7) version 2.5.1 messaging hierarchy to capture, store, and monitor molecular DST data, thereby, improving the quality of data, specifications and exchange formats within the NTSS as well as ensuring full reporting of drug-resistant TB.
耐多药结核病（TB）仍然是对美国及全球结核病控制的公共卫生威胁。快速且可靠的药敏试验（DST）对于帮助临床医生为结核病患者选择最佳治疗方案以及防止疾病持续传播至关重要。通过国家结核病监测系统（NTSS），针对培养确诊病例的基于生长的DST结果会定期上报给美国疾病控制与预防中心。然而，NTSS目前缺乏接收来自先进分子方法的实验室结果的能力和功能，这些先进分子方法用于检测与耐药性相关的突变。本研究的目的是设计并实施新颖的综合数据交换格式，利用卫生信息交换标准（HL7）版本2.5.1消息层次结构来捕获、存储和监测分子DST数据，从而提高NTSS内数据、规范和交换格式的质量，并确保耐多药结核病的全面报告。
