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1
Developing and validating natural language processing algorithms for radiology reports compared to ICD-10 codes for identifying venous thromboembolism in hospitalized medical patients.开发和验证放射学报告的自然语言处理算法,以与国际疾病分类第 10 版编码相比,用于识别住院医疗患者中的静脉血栓栓塞症。
Thromb Res. 2022 Jan;209:51-58. doi: 10.1016/j.thromres.2021.11.020. Epub 2021 Nov 27.
2
Using routinely recorded data in a UK RCT: a comparison to standard prospective data collection methods.在英国 RCT 中使用常规记录数据:与标准前瞻性数据收集方法的比较。
Trials. 2021 Jul 5;22(1):429. doi: 10.1186/s13063-021-05294-6.
3
Realising the full potential of data-enabled trials in the UK: a call for action.挖掘英国数据驱动型试验的全部潜力:行动呼吁。
BMJ Open. 2021 Jun 16;11(6):e043906. doi: 10.1136/bmjopen-2020-043906.
4
Which is the best model to assess risk for venous thromboembolism in hospitalised patients?评估住院患者静脉血栓栓塞风险的最佳模型是什么?
BMJ. 2021 May 27;373:n1106. doi: 10.1136/bmj.n1106.
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Accessing routinely collected health data to improve clinical trials: recent experience of access.获取常规健康数据以改善临床试验:近期获取经验。
Trials. 2021 May 10;22(1):340. doi: 10.1186/s13063-021-05295-5.
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Accuracy of identifying hospital acquired venous thromboembolism by administrative coding: implications for big data and machine learning research.通过行政编码识别医院获得性静脉血栓栓塞的准确性:对大数据和机器学习研究的影响。
J Clin Monit Comput. 2022 Apr;36(2):397-405. doi: 10.1007/s10877-021-00664-6. Epub 2021 Feb 8.
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Development and implementation of common data elements for venous thromboembolism research: on behalf of SSC Subcommittee on official Communication from the SSC of the ISTH.静脉血栓栓塞症研究常用数据元素的制定和实施:代表 ISTH 的 SSC 下属静脉血栓栓塞症工作组委员会向 SSC 正式传达的信息。
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Administrative codes inaccurately identify recurrent venous thromboembolism: The CVRN VTE study.行政代码不准确地识别复发性静脉血栓栓塞症:CVRN VTE 研究。
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Use of Medicare Claims to Identify Adverse Clinical Outcomes After Mitral Valve Repair.利用医疗保险索赔数据识别二尖瓣修复术后的不良临床结局。
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External Validation of ASPECT (Algorithm for Suspected Pulmonary Embolism Confirmation and Treatment).ASPECT(疑似肺栓塞确认和治疗算法)的外部验证。
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高效数据方法在确定医、外科住院患者院内血栓和大出血发生率中的准确性:英国四家医院的一项多中心观察性队列研究。

Accuracy of efficient data methods to determine the incidence of hospital-acquired thrombosis and major bleeding in medical and surgical inpatients: a multicentre observational cohort study in four UK hospitals.

机构信息

Emergency Department, Northern Care Alliance NHS Foundation Trust, Salford, Manchester, UK

Division of Infection, Immunity and Respiratory Medicine, The University of Manchester, Manchester, UK.

出版信息

BMJ Open. 2023 Feb 6;13(2):e069244. doi: 10.1136/bmjopen-2022-069244.

DOI:10.1136/bmjopen-2022-069244
PMID:36746545
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9906300/
Abstract

OBJECTIVES

We evaluated the accuracy of using routine health service data to identify hospital-acquired thrombosis (HAT) and major bleeding events (MBE) compared with a reference standard of case note review.

DESIGN

A multicentre observational cohort study.

SETTING

Four acute hospitals in the UK.

PARTICIPANTS

A consecutive unselective cohort of general medical and surgical patients requiring hospitalisation for a period of >24 hours during the calendar year 2021. We excluded paediatric, obstetric and critical care patients due to differential risk profiles.

INTERVENTIONS

We compared preidentified sources of routinely collected information (using hospital coding data and local contractually mandated thrombosis datasets) to data extracted from case notes using a predesigned workflow methodology.

PRIMARY AND SECONDARY OUTCOME MEASURES

We defined HAT as objectively confirmed venous thromboembolism occurring during hospital stay or within 90 days of discharge and MBE as per international consensus.

RESULTS

We were able to source all necessary routinely collected outcome data for 87% of 2008 case episodes reviewed. The sensitivity of hospital coding data (International Classification of Diseases 10th Revision, ICD-10) for the diagnosis of HAT and MBE was 62% (95% CI, 54 to 69) and 38% (95% CI, 27 to 50), respectively. Sensitivity improved to 81% (95% CI, 75 to 87) when using local thrombosis data sets.

CONCLUSIONS

Using routinely collected data appeared to miss a substantial proportion of outcome events, when compared with case note review. Our study suggests that currently available routine data collection methods in the UK are inadequate to support efficient study designs in venous thromboembolism research.

TRIAL REGISTRATION NUMBER

NIHR127454.

摘要

目的

我们评估了使用常规卫生服务数据识别医院获得性血栓形成(HAT)和主要出血事件(MBE)的准确性,与病例记录审查的参考标准相比。

设计

一项多中心观察性队列研究。

设置

英国的四家急性医院。

参与者

需要住院治疗 24 小时以上的连续非选择性一般内科和外科患者队列,2021 年全年。由于风险概况不同,我们排除了儿科、产科和重症监护患者。

干预措施

我们将预识别的常规收集信息源(使用医院编码数据和当地合同规定的血栓数据集)与使用预设计工作流程方法从病例记录中提取的数据进行比较。

主要和次要结果测量

我们将 HAT定义为在住院期间或出院后 90 天内确诊的静脉血栓栓塞症,MBE 按照国际共识定义。

结果

我们能够为审查的 2008 个病例事件中的 87%获取所有必要的常规收集结局数据。医院编码数据(国际疾病分类第 10 版,ICD-10)对 HAT 和 MBE 的诊断灵敏度分别为 62%(95%CI,54 至 69)和 38%(95%CI,27 至 50)。当使用本地血栓数据集时,灵敏度提高到 81%(95%CI,75 至 87)。

结论

与病例记录审查相比,使用常规收集的数据似乎错过了相当一部分结局事件。我们的研究表明,英国目前可用的常规数据收集方法不足以支持静脉血栓栓塞症研究中的高效研究设计。

试验注册编号

NIHR127454。