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Efficiency of International Classification of Diseases, Ninth Revision, Billing Code Searches to Identify Emergency Department Visits for Blood or Body Fluid Exposures through a Statewide Multicenter Database

Published online by Cambridge University Press:  02 January 2015

Lisa M. Rosen ,
Tao Liu  and
Roland C. Merchant
Lisa M. Rosen
Affiliation:
Department of Community Health, Alpert Medical School of Brown University, Providence, Rhode Island Department of Emergency Medicine, Alpert Medical School of Brown University, Providence, Rhode Island
Tao Liu
Affiliation:
Department of Community Health, Alpert Medical School of Brown University, Providence, Rhode Island
Roland C. Merchant*
Affiliation:
Department of Community Health, Alpert Medical School of Brown University, Providence, Rhode Island Department of Emergency Medicine, Alpert Medical School of Brown University, Providence, Rhode Island
*
Department of Emergency Medicine, Rhode Island Hospital, 593 Eddy Street, Claverick Building, Providence, RI 02903 (rmerchant@lifespan.org)
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Abstract

Background.

Blood and body fluid exposures are frequently evaluated in emergency departments (EDs). However, efficient and effective methods for estimating their incidence are not yet established.

Objective.

Evaluate the efficiency and accuracy of estimating statewide ED visits for blood or body fluid exposures using International Classification of Diseases, Ninth Revision (ICD-9), code searches.

Design.

Secondary analysis of a database of ED visits for blood or body fluid exposure.

Setting.

EDs of 11 civilian hospitals throughout Rhode Island from January 1, 1995, through June 30, 2001.

Patients.

Patients presenting to the ED for possible blood or body fluid exposure were included, as determined by prespecified ICD-9 codes.

Methods.

Positive predictive values (PPVs) were estimated to determine the ability of 10 ICD-9 codes to distinguish ED visits for blood or body fluid exposure from ED visits that were not for blood or body fluid exposure. Recursive partitioning was used to identify an optimal subset of ICD-9 codes for this purpose. Random-effects logistic regression modeling was used to examine variations in ICD-9 coding practices and styles across hospitals. Cluster analysis was used to assess whether the choice of ICD-9 codes was similar across hospitals.

Results.

The PPV for the original 10 ICD-9 codes was 74.4% (95% confidence interval [CI], 73.2%–75.7%), whereas the recursive partitioning analysis identified a subset of 5 ICD-9 codes with a PPV of 89.9% (95% CI, 88.9%–90.8%) and a misclassification rate of 10.1%. The ability, efficiency, and use of the ICD-9 codes to distinguish types of ED visits varied across hospitals.

Conclusions.

Although an accurate subset of ICD-9 codes could be identified, variations across hospitals related to hospital coding style, efficiency, and accuracy greatly affected estimates of the number of ED visits for blood or body fluid exposure.

Type
Original Article
Information
Infection Control & Hospital Epidemiology , Volume 33 , Issue 6 , June 2012 , pp. 581 - 588
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2012 

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