ARCH PATHOL LAB MED:使用数据仓库和结构化的多学科流程识别分析前和分析后实验室质量差距

2019-05-09 不详 网络

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实验室全面测试过程包括分析前、分析后和分析后阶段,但大多数实验室质量改进工作都针对分析阶段。通过使用医疗数据仓库(包括临床、利用和管理数据)将质量改进扩展到分析前和分析后阶段,可以通过确保适当的测试利用来改进患者护理。跨部门、多学科合作,以解决差距和改善患者和系统的结果是有益的。演示医疗数据仓库的实用功能,以表征实验室相关的质量差距,可用于分析前或分析后干预。

研究人员通过多学科小组确定了质量差距。对医疗数据仓库数据进行查询,以确定差距。组织领导就质量改进的优先事项接受了采访。为每一个差距完成了一项包括国家指导方针、地方和国家重要性以及可衡量成果在内的决策援助。

研究确认的缺陷包括(1)测试顺序;(2)诊断、检测和记录;(3)高危药物监测。在检查包括登记、诊断、实验室、药房和基线表现程序的医疗数据仓库数据后,选择高危药物监测,特别是在接受疾病修饰抗风湿药物治疗的患者中,丙氨酸氨基转移酶、天冬氨酸氨基转移酶、全血计数和肌酐检测。检测使用的差异在于监测的及时性(>60%的患者监测间隔超过指南建议的频率)。选择这一差距的其他因素包括组织积极性、法规标签以及实验室在解决这一差距方面发挥重要作用的可行性。

研究表明,多学科程序有助于鉴定和选择实验室药物质量差距。医疗数据仓库数据在描述差距方面发挥了重要作用。

原始出处:

Marsha A. Raebel, PharmD; LeeAnn M. Quintana, MSW;Identifying Preanalytic and Postanalytic Laboratory Quality Gaps Using a Data Warehouse and Structured Multidisciplinary Process

本文系梅斯医学(MedSci)原创编译整理,转载需授权!


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