From the Department of Anesthesiology, Perioperative and Pain Medicine, The Icahn School of Medicine at Mount Sinai, New York, New York.
Anesth Analg. 2022 Nov 1;135(5):1057-1063. doi: 10.1213/ANE.0000000000006175. Epub 2022 Sep 6.
Visual analytics is the science of analytical reasoning supported by interactive visual interfaces called dashboards. In this report, we describe our experience addressing the challenges in visual analytics of anesthesia electronic health record (EHR) data using a commercially available business intelligence (BI) platform. As a primary outcome, we discuss some performance metrics of the dashboards, and as a secondary outcome, we outline some operational enhancements and financial savings associated with deploying the dashboards.
Data were transferred from the EHR to our departmental servers using several parallel processes. A custom structured query language (SQL) query was written to extract the relevant data fields and to clean the data. Tableau was used to design multiple dashboards for clinical operation, performance improvement, and business management.
Before deployment of the dashboards, detailed case counts and attributions were available for the operating rooms (ORs) from perioperative services; however, the same level of detail was not available for non-OR locations. Deployment of the yearly case count dashboards provided near-real-time case count information from both central and non-OR locations among multiple campuses, which was not previously available. The visual presentation of monthly data for each year allowed us to recognize seasonality in case volumes and adjust our supply chain to prevent shortages. The dashboards highlighted the systemwide volume of cases in our endoscopy suites, which allowed us to target these supplies for pricing negotiations, with an estimated annual cost savings of $250,000. Our central venous pressure (CVP) dashboard enabled us to provide individual practitioner feedback, thus increasing our monthly CVP checklist compliance from approximately 92% to 99%.
The customization and visualization of EHR data are both possible and worthwhile for the leveraging of information into easily comprehensible and actionable data for the improvement of health care provision and practice management. Limitations inherent to EHR data presentation make this customization necessary, and continued open access to the underlying data set is essential.
可视化分析是一门科学，它通过交互式可视化界面（称为仪表板）支持分析推理。在本报告中，我们描述了使用商业上可用的商业智能 (BI) 平台解决麻醉电子健康记录 (EHR) 数据可视化分析挑战的经验。作为主要结果，我们讨论了仪表板的一些性能指标，作为次要结果，我们概述了与部署仪表板相关的一些运营增强和财务节省。
使用多个并行进程将数据从 EHR 传输到我们的部门服务器。编写了一个自定义结构化查询语言 (SQL) 查询，以提取相关数据字段并清理数据。Tableau 用于设计多个仪表板，用于临床运营、绩效改进和业务管理。
在部署仪表板之前，手术室 (OR) 可从围手术期服务获得详细的病例计数和归因；然而，非 OR 地点则没有提供相同级别的详细信息。部署年度病例计数仪表板为多个校区的中央和非 OR 地点提供了近乎实时的病例计数信息，这是以前无法获得的。每年每月数据的可视化呈现使我们能够识别病例量的季节性，并调整我们的供应链以防止短缺。仪表板突出显示了我们内镜套房系统范围内的病例量，这使我们能够针对这些供应品进行定价谈判，估计每年节省 25 万美元。我们的中心静脉压 (CVP) 仪表板使我们能够为个体从业者提供反馈，从而将我们每月 CVP 检查表的合规性从大约 92%提高到 99%。
对 EHR 数据进行定制和可视化处理都是可行的，并且值得将信息转化为易于理解和可操作的数据，以改善医疗服务提供和实践管理。EHR 数据呈现所固有的限制使得这种定制是必要的，并且持续开放对基础数据集的访问是至关重要的。
