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

Validation and utility of a computerized South Asian names and group recognition algorithm in ascertaining South Asian ethnicity in the national renal registry
Validation and utility of a computerized South Asian names and group recognition algorithm in ascertaining South Asian ethnicity in the national renal registry
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
1460-2725
865-872
Nitsch, D.
3ce6cece-9feb-48e1-909a-b5085bdf6ea7
Kadalayil, L.
e620b801-844a-45d9-acaf-e0a58acd7cf2
Mangtani, P.
d79dc093-109c-4cf6-99ff-3e59502d66ee
Steenkamp, R.
2747774c-cb75-4ea4-bf5f-fb10a6978ce6
Ansell, D.
4849c1d3-9ff9-46ac-91e5-b4c6d7a6b52f
Tomson, C.
bdf91cd6-4845-4f11-99e2-b9539c00c8d5
Dos Santos Silva, I.
42f12121-59b8-4c3f-a429-ba7f8b6a5141
Roderick, P.
dbb3cd11-4c51-4844-982b-0eb30ad5085a
Nitsch, D.
3ce6cece-9feb-48e1-909a-b5085bdf6ea7
Kadalayil, L.
e620b801-844a-45d9-acaf-e0a58acd7cf2
Mangtani, P.
d79dc093-109c-4cf6-99ff-3e59502d66ee
Steenkamp, R.
2747774c-cb75-4ea4-bf5f-fb10a6978ce6
Ansell, D.
4849c1d3-9ff9-46ac-91e5-b4c6d7a6b52f
Tomson, C.
bdf91cd6-4845-4f11-99e2-b9539c00c8d5
Dos Santos Silva, I.
42f12121-59b8-4c3f-a429-ba7f8b6a5141
Roderick, P.
dbb3cd11-4c51-4844-982b-0eb30ad5085a

Nitsch, D., Kadalayil, L., Mangtani, P., Steenkamp, R., Ansell, D., Tomson, C., Dos Santos Silva, I. and Roderick, P. (2009) Validation and utility of a computerized South Asian names and group recognition algorithm in ascertaining South Asian ethnicity in the national renal registry. QJM: An International Journal of Medicine, 102 (12), 865-872. (doi:10.1093/qjmed/hcp142).

Record type: Article

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

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Published date: December 2009

Identifiers

Local EPrints ID: 72935
URI: http://eprints.soton.ac.uk/id/eprint/72935
ISSN: 1460-2725
PURE UUID: b1dda863-cae7-4835-8e01-f5a81571a1ae
ORCID for P. Roderick: ORCID iD orcid.org/0000-0001-9475-6850

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Date deposited: 25 Feb 2010
Last modified: 14 Mar 2024 02:38

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Contributors

Author: D. Nitsch
Author: L. Kadalayil
Author: P. Mangtani
Author: R. Steenkamp
Author: D. Ansell
Author: C. Tomson
Author: I. Dos Santos Silva
Author: P. Roderick ORCID iD

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