Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD 21201-1595, USA.
Radiographics. 2009 Nov;29(7):1897-906. doi: 10.1148/rg.297095701. Epub 2009 Sep 4.
Radiology departments today are faced with many challenges to improve operational efficiency, performance, and quality. Many organizations rely on antiquated, paper-based methods to review their historical performance and understand their operations. With increased workloads, geographically dispersed image acquisition and reading sites, and rapidly changing technologies, this approach is increasingly untenable. A Web-based dashboard was constructed to automate the extraction, processing, and display of indicators and thereby provide useful and current data for twice-monthly departmental operational meetings. The feasibility of extracting specific metrics from clinical information systems was evaluated as part of a longer-term effort to build a radiology business intelligence architecture. Operational data were extracted from clinical information systems and stored in a centralized data warehouse. Higher-level analytics were performed on the centralized data, a process that generated indicators in a dynamic Web-based graphical environment that proved valuable in discussion and root cause analysis. Results aggregated over a 24-month period since implementation suggest that this operational business intelligence reporting system has provided significant data for driving more effective management decisions to improve productivity, performance, and quality of service in the department.
放射科目前面临着提高运营效率、性能和质量的诸多挑战。许多组织依赖过时的、基于纸质的方法来审查其历史绩效并了解其运营情况。随着工作量的增加、地理上分散的图像采集和阅读站点以及快速变化的技术，这种方法越来越不可行。构建了一个基于 Web 的仪表板，以自动提取、处理和显示指标，从而为每月两次的部门运营会议提供有用且最新的数据。作为构建放射科商业智能架构的长期努力的一部分，评估了从临床信息系统中提取特定指标的可行性。从临床信息系统中提取运营数据并存储在集中的数据仓库中。对集中数据进行高级分析，这一过程在动态的基于 Web 的图形环境中生成指标，这在讨论和根本原因分析中非常有价值。自实施以来 24 个月的汇总结果表明，该运营商业智能报告系统为做出更有效的管理决策提供了重要数据，以提高部门的生产力、绩效和服务质量。
