Do coder characteristics influence validity of ICD-10 hospital discharge data?

<p>Abstract</p> <p>Background</p> <p>Administrative data are widely used to study health systems and make important health policy decisions. Yet little is known about the influence of coder characteristics on administrative data validity in these studies. Our goal was t...

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Main Authors: Beck Cynthia A, Faris Peter D, Quan Hude, Hennessy Deirdre A
Format: Article
Language:English
Published: BMC 2010-04-01
Series:BMC Health Services Research
Online Access:http://www.biomedcentral.com/1472-6963/10/99
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spelling doaj-2faac7fba7594d5c84e8375fd8ba78172020-11-25T00:37:13ZengBMCBMC Health Services Research1472-69632010-04-011019910.1186/1472-6963-10-99Do coder characteristics influence validity of ICD-10 hospital discharge data?Beck Cynthia AFaris Peter DQuan HudeHennessy Deirdre A<p>Abstract</p> <p>Background</p> <p>Administrative data are widely used to study health systems and make important health policy decisions. Yet little is known about the influence of coder characteristics on administrative data validity in these studies. Our goal was to describe the relationship between several measures of validity in coded hospital discharge data and 1) coders' volume of coding (≥13,000 vs. <13,000 records), 2) coders' employment status (full- vs. part-time), and 3) hospital type.</p> <p>Methods</p> <p>This descriptive study examined 6 indicators of face validity in ICD-10 coded discharge records from 4 hospitals in Calgary, Canada between April 2002 and March 2007. Specifically, mean number of coded diagnoses, procedures, complications, Z-codes, and codes ending in 8 or 9 were compared by coding volume and employment status, as well as hospital type. The mean number of diagnoses was also compared across coder characteristics for 6 major conditions of varying complexity. Next, kappa statistics were computed to assess agreement between discharge data and linked chart data reabstracted by nursing chart reviewers. Kappas were compared across coder characteristics.</p> <p>Results</p> <p>422,618 discharge records were coded by 59 coders during the study period. The mean number of diagnoses per record decreased from 5.2 in 2002/2003 to 3.9 in 2006/2007, while the number of records coded annually increased from 69,613 to 102,842. Coders at the tertiary hospital coded the most diagnoses (5.0 compared with 3.9 and 3.8 at other sites). There was no variation by coder or site characteristics for any other face validity indicator. The mean number of diagnoses increased from 1.5 to 7.9 with increasing complexity of the major diagnosis, but did not vary with coder characteristics. Agreement (kappa) between coded data and chart review did not show any consistent pattern with respect to coder characteristics.</p> <p>Conclusions</p> <p>This large study suggests that coder characteristics do not influence the validity of hospital discharge data. Other jurisdictions might benefit from implementing similar employment programs to ours, e.g.: a requirement for a 2-year college training program, a single management structure across sites, and rotation of coders between sites. Limitations include few coder characteristics available for study due to privacy concerns.</p> http://www.biomedcentral.com/1472-6963/10/99
collection DOAJ
language English
format Article
sources DOAJ
author Beck Cynthia A
Faris Peter D
Quan Hude
Hennessy Deirdre A
spellingShingle Beck Cynthia A
Faris Peter D
Quan Hude
Hennessy Deirdre A
Do coder characteristics influence validity of ICD-10 hospital discharge data?
BMC Health Services Research
author_facet Beck Cynthia A
Faris Peter D
Quan Hude
Hennessy Deirdre A
author_sort Beck Cynthia A
title Do coder characteristics influence validity of ICD-10 hospital discharge data?
title_short Do coder characteristics influence validity of ICD-10 hospital discharge data?
title_full Do coder characteristics influence validity of ICD-10 hospital discharge data?
title_fullStr Do coder characteristics influence validity of ICD-10 hospital discharge data?
title_full_unstemmed Do coder characteristics influence validity of ICD-10 hospital discharge data?
title_sort do coder characteristics influence validity of icd-10 hospital discharge data?
publisher BMC
series BMC Health Services Research
issn 1472-6963
publishDate 2010-04-01
description <p>Abstract</p> <p>Background</p> <p>Administrative data are widely used to study health systems and make important health policy decisions. Yet little is known about the influence of coder characteristics on administrative data validity in these studies. Our goal was to describe the relationship between several measures of validity in coded hospital discharge data and 1) coders' volume of coding (≥13,000 vs. <13,000 records), 2) coders' employment status (full- vs. part-time), and 3) hospital type.</p> <p>Methods</p> <p>This descriptive study examined 6 indicators of face validity in ICD-10 coded discharge records from 4 hospitals in Calgary, Canada between April 2002 and March 2007. Specifically, mean number of coded diagnoses, procedures, complications, Z-codes, and codes ending in 8 or 9 were compared by coding volume and employment status, as well as hospital type. The mean number of diagnoses was also compared across coder characteristics for 6 major conditions of varying complexity. Next, kappa statistics were computed to assess agreement between discharge data and linked chart data reabstracted by nursing chart reviewers. Kappas were compared across coder characteristics.</p> <p>Results</p> <p>422,618 discharge records were coded by 59 coders during the study period. The mean number of diagnoses per record decreased from 5.2 in 2002/2003 to 3.9 in 2006/2007, while the number of records coded annually increased from 69,613 to 102,842. Coders at the tertiary hospital coded the most diagnoses (5.0 compared with 3.9 and 3.8 at other sites). There was no variation by coder or site characteristics for any other face validity indicator. The mean number of diagnoses increased from 1.5 to 7.9 with increasing complexity of the major diagnosis, but did not vary with coder characteristics. Agreement (kappa) between coded data and chart review did not show any consistent pattern with respect to coder characteristics.</p> <p>Conclusions</p> <p>This large study suggests that coder characteristics do not influence the validity of hospital discharge data. Other jurisdictions might benefit from implementing similar employment programs to ours, e.g.: a requirement for a 2-year college training program, a single management structure across sites, and rotation of coders between sites. Limitations include few coder characteristics available for study due to privacy concerns.</p>
url http://www.biomedcentral.com/1472-6963/10/99
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