何时重新订购实验室检测？了解实验室检测的有效期。
When to re-order laboratory tests? Learning laboratory test shelf-life.
机构信息
Department of Biomedical Informatics, Columbia University, 622 W. 168th Street, New York, NY, USA.
Department of Biomedical Informatics, Columbia University, 622 W. 168th Street, New York, NY, USA.
出版信息
J Biomed Inform. 2018 Sep;85:21-29. doi: 10.1016/j.jbi.2018.07.019. Epub 2018 Jul 20.
Abstract
Most laboratory results are valid for only a certain time period (laboratory tests shelf-life), after which they are outdated and the test needs to be re-administered. Currently, laboratory test shelf-lives are not centrally available anywhere but the implicit knowledge of doctors. In this work we propose an automated method to learn laboratory test-specific shelf-life by identifying prevalent laboratory test order patterns in electronic health records. The resulting shelf-lives performed well in the evaluation of internal validity, clinical interpretability, and external validity.
摘要
大多数实验室结果的有效期仅为一段时间（实验室测试保质期），之后结果就会过期，需要重新进行测试。目前，实验室测试保质期并没有集中在任何地方，而只是医生的隐性知识。在这项工作中，我们通过识别电子健康记录中常见的实验室测试订单模式，提出了一种自动学习实验室测试特定保质期的方法。所得到的保质期在内部有效性、临床可解释性和外部有效性的评估中表现良好。
相似文献
1
When to re-order laboratory tests? Learning laboratory test shelf-life.何时重新订购实验室检测？了解实验室检测的有效期。
J Biomed Inform. 2018 Sep;85:21-29. doi: 10.1016/j.jbi.2018.07.019. Epub 2018 Jul 20.
2
Estimating summary statistics for electronic health record laboratory data for use in high-throughput phenotyping algorithms.估算电子健康记录实验室数据的汇总统计信息，用于高通量表型分析算法。
J Biomed Inform. 2018 Feb;78:87-101. doi: 10.1016/j.jbi.2018.01.004. Epub 2018 Jan 31.
3
The Impact of an Electronic Medical Record on Repeat Laboratory Test Ordering Across Four Australian Hospitals.电子病历对澳大利亚四家医院重复实验室检查医嘱的影响。
Stud Health Technol Inform. 2015;216:917.
4
Evaluation of patient re-identification using laboratory test orders and mitigation via latent space variables.使用实验室检查医嘱评估患者重新识别情况及通过潜在空间变量进行缓解
Pac Symp Biocomput. 2019;24:415-426.
5
Improving physician practice efficiency by learning lab test ordering pattern.通过了解实验室检查的开单模式提高医生的诊疗效率。
Stud Health Technol Inform. 2013;192:988.
6
Biases in electronic health record data due to processes within the healthcare system: retrospective observational study.由于医疗体系内的流程而导致电子健康记录数据出现偏差：回顾性观察性研究。
BMJ. 2018 Apr 30;361:k1479. doi: 10.1136/bmj.k1479.
7
The effect of defaults in an electronic health record on laboratory test ordering practices for pediatric patients.电子健康记录中的默认设置对儿科患者的实验室检测医嘱实践的影响。
Health Psychol. 2013 Sep;32(9):995-1002. doi: 10.1037/a0032925.
8
Analyzing laboratory test utilization trends in belgian primary care: a decade of insights with international perspectives.分析比利时初级保健中的实验室检测利用趋势：具有国际视野的十年洞察。
BMC Prim Care. 2024 Jul 25;25(1):270. doi: 10.1186/s12875-024-02536-9.
9
Comparison of several point-of-care testing (POCT) glucometers with an established laboratory procedure for the diagnosis of type 2 diabetes using the discordance rate. A new statistical approach.使用不一致率，比较几种即时检验（POCT）血糖仪与既定实验室程序在2型糖尿病诊断中的应用。一种新的统计方法。
Clin Chem Lab Med. 2003 Jun;41(6):809-20. doi: 10.1515/CCLM.2003.123.
10
Effect of a Price Transparency Intervention in the Electronic Health Record on Clinician Ordering of Inpatient Laboratory Tests: The PRICE Randomized Clinical Trial.电子健康记录中的价格透明度干预对临床医生开具住院实验室检查医嘱的影响：PRICE随机临床试验
JAMA Intern Med. 2017 Jul 1;177(7):939-945. doi: 10.1001/jamainternmed.2017.1144.
引用本文的文献
1
Building the Model.建立模型。
Arch Pathol Lab Med. 2023 Jul 1;147(7):826-836. doi: 10.5858/arpa.2021-0635-RA.
2
Predictive analytics in health care: how can we know it works?医疗保健中的预测分析：我们如何知道它是否有效？
J Am Med Inform Assoc. 2019 Dec 1;26(12):1651-1654. doi: 10.1093/jamia/ocz130.
本文引用的文献
1
Using statistical anomaly detection models to find clinical decision support malfunctions.使用统计异常检测模型发现临床决策支持故障。
J Am Med Inform Assoc. 2018 Jul 1;25(7):862-871. doi: 10.1093/jamia/ocy041.
2
Decaying relevance of clinical data towards future decisions in data-driven inpatient clinical order sets.临床数据对数据驱动的住院临床医嘱集未来决策的相关性正在衰减。
Int J Med Inform. 2017 Jun;102:71-79. doi: 10.1016/j.ijmedinf.2017.03.006. Epub 2017 Mar 18.
3
Towards Better Test Utilization - Strategies to Improve Physician Ordering and Their Impact on Patient Outcomes.迈向更好的检查利用——改善医生开单的策略及其对患者结局的影响。
EJIFCC. 2015 Jan 27;26(1):15-30. eCollection 2015 Jan.
4
Predicting inpatient clinical order patterns with probabilistic topic models vs conventional order sets.使用概率主题模型与传统医嘱集预测住院患者临床医嘱模式。
J Am Med Inform Assoc. 2017 May 1;24(3):472-480. doi: 10.1093/jamia/ocw136.
5
Anomaly Detection in Host Signaling Pathways for the Early Prognosis of Acute Infection.宿主信号通路中的异常检测用于急性感染的早期预后评估。
PLoS One. 2016 Aug 17;11(8):e0160919. doi: 10.1371/journal.pone.0160919. eCollection 2016.
6
An unsupervised learning method to identify reference intervals from a clinical database.一种从临床数据库中识别参考区间的无监督学习方法。
J Biomed Inform. 2016 Feb;59:276-84. doi: 10.1016/j.jbi.2015.12.010. Epub 2015 Dec 19.
7
Learning probabilistic phenotypes from heterogeneous EHR data.从异构电子健康记录数据中学习概率性表型。
J Biomed Inform. 2015 Dec;58:156-165. doi: 10.1016/j.jbi.2015.10.001. Epub 2015 Oct 14.
8
OrderRex: clinical order decision support and outcome predictions by data-mining electronic medical records.OrderRex：通过数据挖掘电子病历实现临床医嘱决策支持与结果预测。
J Am Med Inform Assoc. 2016 Mar;23(2):339-48. doi: 10.1093/jamia/ocv091. Epub 2015 Jul 21.
9
Intercepting wrong-patient orders in a computerized provider order entry system.在计算机化医嘱录入系统中拦截错误患者医嘱。
Ann Emerg Med. 2015 Jun;65(6):679-686.e1. doi: 10.1016/j.annemergmed.2014.11.017. Epub 2014 Dec 18.
10
Temporal trends of hemoglobin A1c testing.糖化血红蛋白检测的时间趋势。
J Am Med Inform Assoc. 2014 Nov-Dec;21(6):1038-44. doi: 10.1136/amiajnl-2013-002592. Epub 2014 Jun 13.
Zotero 插件