Suppr超能文献

验证和利用一种计算机化的南亚姓名和群体识别算法,以确定国家肾脏登记处中南亚裔族群的身份。

Validation and utility of a computerized South Asian names and group recognition algorithm in ascertaining South Asian ethnicity in the national renal registry.

机构信息

Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK.

出版信息

QJM. 2009 Dec;102(12):865-72. doi: 10.1093/qjmed/hcp142. Epub 2009 Oct 14.

Abstract

BACKGROUND

The UK Renal Registry (UKRR) reports on equity and quality of renal replacement therapy (RRT). Ethnic origin is a key variable, but it is only recorded for 76% patients overall in the UKRR and there is wide variation in the degree of its completeness between renal centres. Most South Asians have distinctive names.

AIM

To test the relative performance of a computerized name recognition algorithm (SANGRA) in identifying South Asian names using the UKRR database.

DESIGN

Cross-sectional study of patients (n = 27 832) starting RRT in 50 renal centres in England and Wales from 1997 to 2005.

METHODS

Kappa statistics were used to assess the degree of agreement of SANGRA coding with existing ethnicity information in UKRR centres.

RESULTS

In 12 centres outside London (number of patients = 7555) with 11% (n = 747) self-ascribed South Asian ethnicity, the level of agreement between SANGRA and self-ascribed ethnicity was high (kappa=0.91, 95% CI 0.90-0.93). In two London centres (n = 779) with 21% (n = 165) self-ascribed South Asian ethnicity, SANGRA's agreement with self-ascribed ethnicity was lower (kappa=0.60, 95% CI 0.54-0.67), primarily due to difficulties in distinguishing between South Asian ethnicity and other non-White ethnic minorities. Use of SANGRA increased numbers defined as South Asian from 1650 to 2076 with no overall change in percentage of South Asians. Kappa values showed no obvious association with degree of missing data returns to the UKRR.

CONCLUSION

SANGRA's use, taking into account its lower validity in London, allows increased power and generalizability for both ethnic specific analyses and for analyses where adjustment for ethnic origin is important.

摘要

背景

英国肾脏注册处(UKRR)报告了肾脏替代治疗(RRT)的公平性和质量。种族是一个关键变量,但 UKRR 仅记录了总体上 76%的患者的种族信息,而且各肾脏中心对种族信息的完整程度存在很大差异。大多数南亚人都有独特的名字。

目的

测试计算机化姓名识别算法(SANGRA)在使用 UKRR 数据库识别南亚姓名时的相对性能。

设计

对 1997 年至 2005 年间在英格兰和威尔士的 50 个肾脏中心开始接受 RRT 的 27832 名患者(n=27832)进行的横断面研究。

方法

使用 Kappa 统计评估 SANGRA 编码与 UKRR 中心现有种族信息的一致性程度。

结果

在伦敦以外的 12 个中心(患者人数=7555 人)中,有 11%(n=747)自认为是南亚裔,SANGRA 与自报种族之间的一致性程度很高(kappa=0.91,95%置信区间 0.90-0.93)。在伦敦的两个中心(n=779 人)中,有 21%(n=165 人)自认为是南亚裔,SANGRA 与自报种族的一致性较低(kappa=0.60,95%置信区间 0.54-0.67),主要是因为难以区分南亚裔和其他非白人少数民族。使用 SANGRA 将被定义为南亚裔的人数从 1650 人增加到 2076 人,而南亚裔的比例没有总体变化。Kappa 值与返回 UKRR 的数据缺失程度没有明显关联。

结论

考虑到 SANGRA 在伦敦的有效性较低,使用 SANGRA 可以提高特定种族分析的效能和普遍性,以及调整种族来源重要性的分析的效能和普遍性。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验