Li Dan-Dan, Yu Ya-Ni, Sun Zhi-Jun, Liu Chang-Fu, Chen Tao, Shan Dong-Kai, Tuo Xiao-Dan, Guo Jun, Chen Yun-Dai
Department of Cardiology, the Sixth Medical Center of PLA General Hospital, Beijing, China.
School of Medicine, Nankai University, No.94 Weijin Road, Nankai District, Tianjin, China.
J Geriatr Cardiol. 2025 Jul 28;22(7):678-689. doi: 10.26599/1671-5411.2025.07.006.
Medical informatics accumulated vast amounts of data for clinical diagnosis and treatment. However, limited access to follow-up data and the difficulty in integrating data across diverse platforms continue to pose significant barriers to clinical research progress. In response, our research team has embarked on the development of a specialized clinical research database for cardiology, thereby establishing a comprehensive digital platform that facilitates both clinical decision-making and research endeavors.
The database incorporated actual clinical data from patients who received treatment at the Cardiovascular Medicine Department of Chinese PLA General Hospital from 2012 to 2021. It included comprehensive data on patients' basic information, medical history, non-invasive imaging studies, laboratory test results, as well as peri-procedural information related to interventional surgeries, extracted from the Hospital Information System. Additionally, an innovative artificial intelligence (AI)-powered interactive follow-up system had been developed, ensuring that nearly all myocardial infarction patients received at least one post-discharge follow-up, thereby achieving comprehensive data management throughout the entire care continuum for high-risk patients.
This database integrates extensive cross-sectional and longitudinal patient data, with a focus on higher-risk acute coronary syndrome patients. It achieves the integration of structured and unstructured clinical data, while innovatively incorporating AI and automatic speech recognition technologies to enhance data integration and workflow efficiency. It creates a comprehensive patient view, thereby improving diagnostic and follow-up quality, and provides high-quality data to support clinical research. Despite limitations in unstructured data standardization and biological sample integrity, the database's development is accompanied by ongoing optimization efforts.
The cardiovascular specialty clinical database is a comprehensive digital archive integrating clinical treatment and research, which facilitates the digital and intelligent transformation of clinical diagnosis and treatment processes. It supports clinical decision-making and offers data support and potential research directions for the specialized management of cardiovascular diseases.
医学信息学积累了大量用于临床诊断和治疗的数据。然而，随访数据获取有限以及跨不同平台整合数据的困难，仍然是临床研究进展的重大障碍。作为回应，我们的研究团队着手开发一个专门的心脏病学临床研究数据库，从而建立一个全面的数字平台，以促进临床决策和研究工作。
该数据库纳入了2012年至2021年在中国人民解放军总医院心血管内科接受治疗的患者的实际临床数据。它包括从医院信息系统中提取的患者基本信息、病史、无创影像学检查、实验室检查结果以及与介入手术相关的围手术期信息等综合数据。此外，还开发了一种创新的人工智能（AI）驱动的交互式随访系统，确保几乎所有心肌梗死患者都接受了至少一次出院后随访，从而在高危患者的整个护理连续过程中实现了全面的数据管理。
该数据库整合了广泛的横断面和纵向患者数据，重点关注高危急性冠状动脉综合征患者。它实现了结构化和非结构化临床数据的整合，同时创新性地融入了人工智能和自动语音识别技术，以提高数据整合和工作流程效率。它创建了全面的患者视图，从而提高了诊断和随访质量，并提供高质量数据以支持临床研究。尽管在非结构化数据标准化和生物样本完整性方面存在局限性，但数据库的开发仍伴随着持续的优化努力。
心血管专科临床数据库是一个整合临床治疗和研究的综合数字档案，有助于临床诊断和治疗过程的数字化和智能化转型。它支持临床决策，并为心血管疾病的专科管理提供数据支持和潜在的研究方向。
