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1696. The Black Box of Using Health Claims-Based Analyses to Estimate UTI Prevalence in Community-Dwelling Women

BACKGROUND: Urinary tract infections (UTIs) are common in women but most epidemiology studies occurred in specialized settings (university health clinics) or used outdated methods (random digit dialing). Currently, women receive UTI care in systems with electronic health records (EHR), thus document...

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Autores principales: Stapleton, Ann E, Wolfson, Julian, Zhang, Jianqiu, Smith, Ariana, Newman, Diane, Talley, Kristine, Wyman, Jean
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7777928/
http://dx.doi.org/10.1093/ofid/ofaa439.1874
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author Stapleton, Ann E
Wolfson, Julian
Zhang, Jianqiu
Smith, Ariana
Newman, Diane
Talley, Kristine
Wyman, Jean
author_facet Stapleton, Ann E
Wolfson, Julian
Zhang, Jianqiu
Smith, Ariana
Newman, Diane
Talley, Kristine
Wyman, Jean
author_sort Stapleton, Ann E
collection PubMed
description BACKGROUND: Urinary tract infections (UTIs) are common in women but most epidemiology studies occurred in specialized settings (university health clinics) or used outdated methods (random digit dialing). Currently, women receive UTI care in systems with electronic health records (EHR), thus documenting care of a wider female demographic in real-world settings. We estimated the prevalence of acute, uncomplicated UTIs in community-dwelling women in a health claims database using various operational definitions of UTI. METHODS: We conducted a retrospective analysis of claims data from the OptumLabs® Data Warehouse (OLDW), a de-identified claims and clinical information repository for privately insured and Medicare Advantage enrollees in a large, private US health plan. Non-pregnant female patients ≥ 15 years of age with two years of continuous enrollment between 2007-2015 and a visit encounter in an outpatient office, urgent care, or emergency department were included. Women with lower urinary tract disease/abnormalities, neurological disease, urological treatment, procedures or urinary catheter use, cancer or HIV treatment were excluded. Decision rules for identifying UTIs were derived using one or more combinations of: relevant ICD-9 codes, UTI symptom diagnosis codes, positive urine test results, and/or antibiotic prescription recorded in the EHR and claims. Prevalence rates were calculated for each decision rule. RESULTS: Of the 7,337,700 females in the claims database, 947,041 (12.97%) had an index UTI diagnosis or symptoms and met eligibility criteria. The table below illustrates prevalence rates according to each decision rule. As shown, applying decision rules based on common UTI definitions resulted in large differences in prevalence rates. Table [Image: see text] CONCLUSION: Using common definitions for UTI to analyze claims data from an insurer of large proportions of the US, we obtained significantly different prevalence rates. This study highlights major limitations in using EHR and claims data for UTI quality initiatives such as tracking of practices associated with antimicrobial stewardship and lends credibility to proposals to track these infections as a reportable disease. DISCLOSURES: All Authors: No reported disclosures
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spelling pubmed-77779282021-01-07 1696. The Black Box of Using Health Claims-Based Analyses to Estimate UTI Prevalence in Community-Dwelling Women Stapleton, Ann E Wolfson, Julian Zhang, Jianqiu Smith, Ariana Newman, Diane Talley, Kristine Wyman, Jean Open Forum Infect Dis Poster Abstracts BACKGROUND: Urinary tract infections (UTIs) are common in women but most epidemiology studies occurred in specialized settings (university health clinics) or used outdated methods (random digit dialing). Currently, women receive UTI care in systems with electronic health records (EHR), thus documenting care of a wider female demographic in real-world settings. We estimated the prevalence of acute, uncomplicated UTIs in community-dwelling women in a health claims database using various operational definitions of UTI. METHODS: We conducted a retrospective analysis of claims data from the OptumLabs® Data Warehouse (OLDW), a de-identified claims and clinical information repository for privately insured and Medicare Advantage enrollees in a large, private US health plan. Non-pregnant female patients ≥ 15 years of age with two years of continuous enrollment between 2007-2015 and a visit encounter in an outpatient office, urgent care, or emergency department were included. Women with lower urinary tract disease/abnormalities, neurological disease, urological treatment, procedures or urinary catheter use, cancer or HIV treatment were excluded. Decision rules for identifying UTIs were derived using one or more combinations of: relevant ICD-9 codes, UTI symptom diagnosis codes, positive urine test results, and/or antibiotic prescription recorded in the EHR and claims. Prevalence rates were calculated for each decision rule. RESULTS: Of the 7,337,700 females in the claims database, 947,041 (12.97%) had an index UTI diagnosis or symptoms and met eligibility criteria. The table below illustrates prevalence rates according to each decision rule. As shown, applying decision rules based on common UTI definitions resulted in large differences in prevalence rates. Table [Image: see text] CONCLUSION: Using common definitions for UTI to analyze claims data from an insurer of large proportions of the US, we obtained significantly different prevalence rates. This study highlights major limitations in using EHR and claims data for UTI quality initiatives such as tracking of practices associated with antimicrobial stewardship and lends credibility to proposals to track these infections as a reportable disease. DISCLOSURES: All Authors: No reported disclosures Oxford University Press 2020-12-31 /pmc/articles/PMC7777928/ http://dx.doi.org/10.1093/ofid/ofaa439.1874 Text en © The Author 2020. 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 Poster Abstracts
Stapleton, Ann E
Wolfson, Julian
Zhang, Jianqiu
Smith, Ariana
Newman, Diane
Talley, Kristine
Wyman, Jean
1696. The Black Box of Using Health Claims-Based Analyses to Estimate UTI Prevalence in Community-Dwelling Women
title 1696. The Black Box of Using Health Claims-Based Analyses to Estimate UTI Prevalence in Community-Dwelling Women
title_full 1696. The Black Box of Using Health Claims-Based Analyses to Estimate UTI Prevalence in Community-Dwelling Women
title_fullStr 1696. The Black Box of Using Health Claims-Based Analyses to Estimate UTI Prevalence in Community-Dwelling Women
title_full_unstemmed 1696. The Black Box of Using Health Claims-Based Analyses to Estimate UTI Prevalence in Community-Dwelling Women
title_short 1696. The Black Box of Using Health Claims-Based Analyses to Estimate UTI Prevalence in Community-Dwelling Women
title_sort 1696. the black box of using health claims-based analyses to estimate uti prevalence in community-dwelling women
topic Poster Abstracts
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7777928/
http://dx.doi.org/10.1093/ofid/ofaa439.1874
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