Department of Pathology & Cell Biology, Columbia University, New York, New York 10032, USA.
Arch Pathol Lab Med. 2013 Aug;137(8):1129-40. doi: 10.5858/arpa.2012-0362-RA. Epub 2012 Dec 5.
Laboratory information systems (LIS) are critical components of the operation of clinical laboratories. However, the functionalities of LIS have lagged significantly behind the capacities of current hardware and software technologies, while the complexity of the information produced by clinical laboratories has been increasing over time and will soon undergo rapid expansion with the use of new, high-throughput and high-dimensionality laboratory tests. In the broadest sense, LIS are essential to manage the flow of information between health care providers, patients, and laboratories and should be designed to optimize not only laboratory operations but also personalized clinical care.
To list suggestions for designing LIS with the goal of optimizing the operation of clinical laboratories while improving clinical care by intelligent management of laboratory information.
Literature review, interviews with laboratory users, and personal experience and opinion.
Laboratory information systems can improve laboratory operations and improve patient care. Specific suggestions for improving the function of LIS are listed under the following sections: (1) Information Security, (2) Test Ordering, (3) Specimen Collection, Accessioning, and Processing, (4) Analytic Phase, (5) Result Entry and Validation, (6) Result Reporting, (7) Notification Management, (8) Data Mining and Cross-sectional Reports, (9) Method Validation, (10) Quality Management, (11) Administrative and Financial Issues, and (12) Other Operational Issues.
实验室信息系统（LIS）是临床实验室运作的关键组成部分。然而，LIS 的功能远远落后于当前硬件和软件技术的能力，而临床实验室所产生的信息的复杂性也在随着时间的推移而不断增加，并且随着新的高通量和高维度实验室测试的使用，这种复杂性将很快迅速扩大。从最广泛的意义上讲，LIS 对于管理医疗保健提供者、患者和实验室之间的信息流动至关重要，并且应该设计为不仅优化实验室操作，而且优化个性化临床护理。
列出设计 LIS 的建议，旨在通过对实验室信息的智能管理来优化临床实验室的运作，同时改善临床护理。
文献综述、与实验室用户的访谈以及个人经验和意见。
实验室信息系统可以改善实验室操作并改善患者护理。在以下各节中列出了改进 LIS 功能的具体建议：（1）信息安全，（2）检验订单，（3）标本采集、登录和处理，（4）分析阶段，（5）结果录入和验证，（6）结果报告，（7）通知管理，（8）数据挖掘和横断报告，（9）方法验证，（10）质量管理，（11）行政和财务问题，以及（12）其他运营问题。
