Cargando…

198. Chart Validation of an Algorithm for Identifying Patients with Intravenous Drug Use-Associated Endocarditis Using Administrative Code Data

BACKGROUND: Studies using administrative data have described increasing rates of intravenous drug use (IVDU)-associated infective endocarditis (IE) in the United States. These studies used International Classification of Disease (ICD) diagnosis codes to identify hospitalized patients with IE and any...

Descripción completa

Detalles Bibliográficos
Autores principales: Kobayashi, Takaaki, Beck, Brice, Miller, Aaron C, Polgreen, Philip M, Ohl, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6810013/
http://dx.doi.org/10.1093/ofid/ofz360.273
_version_ 1783462142723227648
author Kobayashi, Takaaki
Beck, Brice
Miller, Aaron C
Polgreen, Philip M
Ohl, Michael
author_facet Kobayashi, Takaaki
Beck, Brice
Miller, Aaron C
Polgreen, Philip M
Ohl, Michael
author_sort Kobayashi, Takaaki
collection PubMed
description BACKGROUND: Studies using administrative data have described increasing rates of intravenous drug use (IVDU)-associated infective endocarditis (IE) in the United States. These studies used International Classification of Disease (ICD) diagnosis codes to identify hospitalized patients with IE and any illicit drug use (i.e., opioid, amphetamine, cocaine or sedative), but were hindered by absence of specific ICD codes for IVDU. We reviewed charts to determine the positive predictive value (PPV) of ICD codes for identifying patients with IE and IVDU. METHODS: We examined national Veterans Affairs (VA) administrative data from January 2010 to December 2017 to identify patients hospitalized for a first episode of potential IVDU-associated IE based on inpatient ICD 9 and 10 codes for both IE and any illicit drug use, the algorithm used to identify IVDU-IE in most prior studies. We randomly selected 100 of these patients nationally and reviewed hospital charts to confirm clinical documentation of: (1) IE, (2) any illicit drug use, and (3) current or past IVDU. RESULTS: We identified 340 patients with concurrent ICD codes for IE and drug use, increasing from 28 in 2010 to 51 in 2017 (82% increase). In chart review of 100 randomly selected patients, the PPV of ICD codes was 93% (95% CI 88–98%) for a documented clinical diagnosis of IE; 96% (95% CI 92–100%) for documented drug use by any route; and 63% (95% CI 53–73%) for documented IVDU. Among the 37% of patients without clinically documented IVDU, 30% (i.e.,11% of total patients) had clinical documentation stating that drug use was only by non-IV routes, 59% (22% of total) had documented drug use without mention of route of use, and 11% (4% of total) had clinical documentation that patients denied any drug use. CONCLUSION: The incidence of first hospitalization for IE among patients with ICD codes for drug use increased by 82% from 2010 to 2017 in VA care. Concurrent ICD codes for illicit drug use had moderate PPV for identifying IVDU in setting of IE, largely due to identification of patients using drugs without documented intravenous use. There is a need to develop more accurate case-finding algorithms for identifying patients with IVDU-associated endocarditis, for both epidemiologic surveillance and quality improvement applications. DISCLOSURES: All authors: No reported disclosures.
format Online
Article
Text
id pubmed-6810013
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-68100132019-10-28 198. Chart Validation of an Algorithm for Identifying Patients with Intravenous Drug Use-Associated Endocarditis Using Administrative Code Data Kobayashi, Takaaki Beck, Brice Miller, Aaron C Polgreen, Philip M Ohl, Michael Open Forum Infect Dis Abstracts BACKGROUND: Studies using administrative data have described increasing rates of intravenous drug use (IVDU)-associated infective endocarditis (IE) in the United States. These studies used International Classification of Disease (ICD) diagnosis codes to identify hospitalized patients with IE and any illicit drug use (i.e., opioid, amphetamine, cocaine or sedative), but were hindered by absence of specific ICD codes for IVDU. We reviewed charts to determine the positive predictive value (PPV) of ICD codes for identifying patients with IE and IVDU. METHODS: We examined national Veterans Affairs (VA) administrative data from January 2010 to December 2017 to identify patients hospitalized for a first episode of potential IVDU-associated IE based on inpatient ICD 9 and 10 codes for both IE and any illicit drug use, the algorithm used to identify IVDU-IE in most prior studies. We randomly selected 100 of these patients nationally and reviewed hospital charts to confirm clinical documentation of: (1) IE, (2) any illicit drug use, and (3) current or past IVDU. RESULTS: We identified 340 patients with concurrent ICD codes for IE and drug use, increasing from 28 in 2010 to 51 in 2017 (82% increase). In chart review of 100 randomly selected patients, the PPV of ICD codes was 93% (95% CI 88–98%) for a documented clinical diagnosis of IE; 96% (95% CI 92–100%) for documented drug use by any route; and 63% (95% CI 53–73%) for documented IVDU. Among the 37% of patients without clinically documented IVDU, 30% (i.e.,11% of total patients) had clinical documentation stating that drug use was only by non-IV routes, 59% (22% of total) had documented drug use without mention of route of use, and 11% (4% of total) had clinical documentation that patients denied any drug use. CONCLUSION: The incidence of first hospitalization for IE among patients with ICD codes for drug use increased by 82% from 2010 to 2017 in VA care. Concurrent ICD codes for illicit drug use had moderate PPV for identifying IVDU in setting of IE, largely due to identification of patients using drugs without documented intravenous use. There is a need to develop more accurate case-finding algorithms for identifying patients with IVDU-associated endocarditis, for both epidemiologic surveillance and quality improvement applications. DISCLOSURES: All authors: No reported disclosures. Oxford University Press 2019-10-23 /pmc/articles/PMC6810013/ http://dx.doi.org/10.1093/ofid/ofz360.273 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of Infectious Diseases Society of America. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Abstracts
Kobayashi, Takaaki
Beck, Brice
Miller, Aaron C
Polgreen, Philip M
Ohl, Michael
198. Chart Validation of an Algorithm for Identifying Patients with Intravenous Drug Use-Associated Endocarditis Using Administrative Code Data
title 198. Chart Validation of an Algorithm for Identifying Patients with Intravenous Drug Use-Associated Endocarditis Using Administrative Code Data
title_full 198. Chart Validation of an Algorithm for Identifying Patients with Intravenous Drug Use-Associated Endocarditis Using Administrative Code Data
title_fullStr 198. Chart Validation of an Algorithm for Identifying Patients with Intravenous Drug Use-Associated Endocarditis Using Administrative Code Data
title_full_unstemmed 198. Chart Validation of an Algorithm for Identifying Patients with Intravenous Drug Use-Associated Endocarditis Using Administrative Code Data
title_short 198. Chart Validation of an Algorithm for Identifying Patients with Intravenous Drug Use-Associated Endocarditis Using Administrative Code Data
title_sort 198. chart validation of an algorithm for identifying patients with intravenous drug use-associated endocarditis using administrative code data
topic Abstracts
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6810013/
http://dx.doi.org/10.1093/ofid/ofz360.273
work_keys_str_mv AT kobayashitakaaki 198chartvalidationofanalgorithmforidentifyingpatientswithintravenousdruguseassociatedendocarditisusingadministrativecodedata
AT beckbrice 198chartvalidationofanalgorithmforidentifyingpatientswithintravenousdruguseassociatedendocarditisusingadministrativecodedata
AT milleraaronc 198chartvalidationofanalgorithmforidentifyingpatientswithintravenousdruguseassociatedendocarditisusingadministrativecodedata
AT polgreenphilipm 198chartvalidationofanalgorithmforidentifyingpatientswithintravenousdruguseassociatedendocarditisusingadministrativecodedata
AT ohlmichael 198chartvalidationofanalgorithmforidentifyingpatientswithintravenousdruguseassociatedendocarditisusingadministrativecodedata