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Use of a data warehouse at an academic medical center for clinical pathology quality improvement, education, and research

机译:在学术医学中心使用数据仓库进行临床病理质量改善,教育和研究

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Background:Pathology data contained within the electronic health record (EHR), and laboratory information system (LIS) of hospitals represents a potentially powerful resource to improve clinical care. However, existing reporting tools within commercial EHR and LIS software may not be able to efficiently and rapidly mine data for quality improvement and research applications.Materials and Methods:We present experience using a data warehouse produced collaboratively between an academic medical center and a private company. The data warehouse contains data from the EHR, LIS, admission/discharge/transfer system, and billing records and can be accessed using a self-service data access tool known as Starmaker. The Starmaker software allows users to use complex Boolean logic, include and exclude rules, unit conversion and reference scaling, and value aggregation using a straightforward visual interface. More complex queries can be achieved by users with experience with Structured Query Language. Queries can use biomedical ontologies such as Logical Observation Identifiers Names and Codes and Systematized Nomenclature of Medicine.Result:We present examples of successful searches using Starmaker, falling mostly in the realm of microbiology and clinical chemistry/toxicology. The searches were ones that were either very difficult or basically infeasible using reporting tools within the EHR and LIS used in the medical center. One of the main strengths of Starmaker searches is rapid results, with typical searches covering 5 years taking only 1–2 min. A “Run Count” feature quickly outputs the number of cases meeting criteria, allowing for refinement of searches before downloading patient-identifiable data. The Starmaker tool is available to pathology residents and fellows, with some using this tool for quality improvement and scholarly projects.Conclusion:A data warehouse has significant potential for improving utilization of clinical pathology testing. Software that can access data warehouse using a straightforward visual interface can be incorporated into pathology training programs.
机译:背景:医院电子健康记录(EHR)和实验室信息系统(LIS)中包含的病理数据代表了改善临床护理的潜在强大资源。但是,商业EHR和LIS软件中现有的报告工具可能无法高效,快速地挖掘数据以进行质量改进和研究应用。材料和方法:我们展示了使用学术医学中心和私营公司之间共同生产的数据仓库的经验。数据仓库包含来自EHR,LIS,准入/卸载/转移系统和计费记录的数据,可以使用称为Starmaker的自助数据访问工具进行访问。 Starmaker软件允许用户使用简单的可视界面使用复杂的布尔逻辑,包括和排除规则,单位转换和参考缩放以及值聚合。拥有结构化查询语言经验的用户可以实现更复杂的查询。查询可以使用生物医学本体,例如逻辑观察标识符的名称和代码以及医学的系统术语。结果:我们提供了使用Starmaker成功进行搜索的示例,这些示例主要属于微生物学和临床化学/毒理学领域。使用医疗中心使用的EHR和LIS中的报告工具,搜索要么非常困难,要么根本不可行。 Starmaker搜索的主要优势之一是快速的搜索结果,典型的搜索范围为5年,仅需1-2分钟。 “运行计数”功能可以快速输出符合条件的病例数,从而可以在下载可识别患者的数据之前优化搜索范围。 Starmaker工具可供病理学住院医师和研究人员使用,其中一些人使用此工具进行质量改进和学术项目。结论:数据仓库在提高临床病理学检验利用率方面具有巨大潜力。可以将使用直观直观界面访问数据仓库的软件集成到病理学训练程序中。

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