1 Department of Neurosurgery, New York University Langone Medical Center , New York, New York.
2 Department of Radiation Oncology, New York University Langone Medical Center , New York, New York.
Big Data. 2015 Jun;3(2):80-9. doi: 10.1089/big.2014.0069.
Physicians are being challenged to obtain data for outcomes research and measures of quality practice in medicine. We developed a prospective data collection system (registry) that provides data points across all elements of a neurosurgical stereotactic radiosurgery practice. The registry architecture is scalable and suitable for any aspect of neurosurgical practice. Our purpose was to outline the challenges in creating systems for high quality data acquisition and describe experiences in initial testing and use. Over a two year period, a multicenter team working with software engineers developed a comprehensive radiosurgery registry based on a MS-Sequel® server platform. Three neurosurgeons at one center were responsible for final editing. Alpha testing began in September 2012 and server-based beta testing began in February 2013. The major elements included demographics, disease-based items (47 categories for different brain tumors, vascular malformations, and functional disorders) with relevant clinical grading systems, treatment-based items (imaging, physics, clinical), and follow-up data (clinical, imaging, subsequent therapeutics). Nine hundred patients were entered into the registry at one test center, with new entries and follow-up data entered daily at the point of contact. With experience, the mean time for one new entry was 6 minutes. Mean time for one follow-up entry was 45 seconds. The system was made secure for individual use and amenable for both data entry and research. Analytics used different filters to create customized outcomes charts as selected by the user (e.g., survival, neurologic function, complications). A local or multicenter prospective data collection registry was created for use across 47 clinical indications for stereotactic cranial radiosurgery. Further refinement of fields and logic is ongoing. The system is reliable, robust, and allows use of rapid analytical tools. Large medical registries will become widely used for collection and analysis of large data sets and should have broad applicability to many other elements of neurosurgical and medical practice.
医生们面临着获取医学成果研究数据和质量实践措施的挑战。我们开发了一个前瞻性数据收集系统（注册系统），可以提供神经外科立体定向放射外科实践各个方面的数据点。该注册系统的架构具有可扩展性，适用于神经外科实践的任何方面。我们的目的是概述创建高质量数据采集系统所面临的挑战，并描述初始测试和使用的经验。在两年的时间里，一个由软件工程师组成的多中心团队开发了一个基于 MS-Sequel®服务器平台的全面放射外科注册系统。一个中心的三位神经外科医生负责最终编辑。2012 年 9 月开始进行阿尔法测试，2013 年 2 月开始进行基于服务器的贝塔测试。主要内容包括人口统计学、基于疾病的项目（47 个不同脑肿瘤、血管畸形和功能障碍的类别）以及相关的临床分级系统、基于治疗的项目（影像学、物理学、临床）和随访数据（临床、影像学、后续治疗）。在一个测试中心，有 900 名患者被纳入注册系统，新患者和随访数据每天在联系点输入。随着经验的积累，输入一个新病例的平均时间为 6 分钟，输入一次随访的平均时间为 45 秒。该系统为个人使用而安全，并便于数据输入和研究。分析使用不同的筛选器根据用户选择创建定制的结果图表（例如，生存、神经功能、并发症）。创建了一个用于 47 种立体定向颅放射外科临床适应证的本地或多中心前瞻性数据收集注册系统。目前正在对字段和逻辑进行进一步细化。该系统可靠、强大，并允许使用快速分析工具。大型医疗注册系统将广泛用于收集和分析大型数据集，并应广泛适用于神经外科和医疗实践的许多其他方面。
