Lin Fong-Ci, Wang Chen-Yu, Shang Rung Ji, Hsiao Fei-Yuan, Lin Mei-Shu, Hung Kuan-Yu, Wang Jui, Lin Zhen-Fang, Lai Feipei, Shen Li-Jiuan, Huang Chih-Fen
Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan.
Department of Pharmacy, National Taiwan University Hospital, Taipei, Taiwan.
J Med Internet Res. 2018 Apr 24;20(4):e142. doi: 10.2196/jmir.9477.
Traditional clinical surveillance relied on the results from clinical trials and observational studies of administrative databases. However, these studies not only required many valuable resources but also faced a very long time lag.
This study aimed to illustrate a practical application of the National Taiwan University Hospital Clinical Surveillance System (NCSS) in the identification of patients with an osteoporotic fracture and to provide a high reusability infrastructure for longitudinal clinical data.
The NCSS integrates electronic medical records in the National Taiwan University Hospital (NTUH) with a data warehouse and is equipped with a user-friendly interface. The NCSS was developed using professional insight from multidisciplinary experts, including clinical practitioners, epidemiologists, and biomedical engineers. The practical example identifying the unmet treatment needs for patients encountering major osteoporotic fractures described herein was mainly achieved by adopting the computerized workflow in the NCSS.
We developed the infrastructure of the NCSS, including an integrated data warehouse and an automatic surveillance workflow. By applying the NCSS, we efficiently identified 2193 patients who were newly diagnosed with a hip or vertebral fracture between 2010 and 2014 at NTUH. By adopting the filter function, we identified 1808 (1808/2193, 82.44%) patients who continued their follow-up at NTUH, and 464 (464/2193, 21.16%) patients who were prescribed anti-osteoporosis medications, within 3 and 12 months post the index date of their fracture, respectively.
The NCSS systems can integrate the workflow of cohort identification to accelerate the survey process of clinically relevant problems and provide decision support in the daily practice of clinical physicians, thereby making the benefit of evidence-based medicine a reality.
传统的临床监测依赖于临床试验结果以及行政数据库的观察性研究。然而，这些研究不仅需要大量宝贵资源，而且面临很长的时间延迟。
本研究旨在阐明台湾大学附属医院临床监测系统（NCSS）在识别骨质疏松性骨折患者中的实际应用，并为纵向临床数据提供高可重用性的基础设施。
NCSS将台湾大学附属医院（NTUH）的电子病历与数据仓库集成，并配备了用户友好的界面。NCSS是利用包括临床医生、流行病学家和生物医学工程师在内的多学科专家的专业见解开发的。本文所述的识别主要骨质疏松性骨折患者未满足治疗需求的实际案例主要通过采用NCSS中的计算机化工作流程来实现。
我们开发了NCSS的基础设施，包括集成数据仓库和自动监测工作流程。通过应用NCSS，我们有效地识别出2010年至2014年期间在NTUH新诊断为髋部或椎体骨折的2193例患者。通过采用筛选功能，我们分别识别出在骨折索引日期后的3个月和12个月内继续在NTUH进行随访的1808例患者（1808/2193，82.44%）以及接受抗骨质疏松药物治疗的464例患者（464/2193，21.16%）。
NCSS系统可以整合队列识别工作流程，以加速临床相关问题的调查过程，并在临床医生的日常实践中提供决策支持，从而使循证医学的益处成为现实。
