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Validating Use of Electronic Health Data to Identify Patients with Urinary Tract Infections in Outpatient Settings
Objective: To validate the use of electronic algorithms based on International Classification of Diseases (ICD)-10 codes to identify outpatient visits for urinary tract infections (UTI), one of the most common reasons for antibiotic prescriptions. Methods: ICD-10 symptom codes (e.g., dysuria) alone...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7558992/ https://www.ncbi.nlm.nih.gov/pubmed/32854205 http://dx.doi.org/10.3390/antibiotics9090536 |
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author | Germanos, George Light, Patrick Zoorob, Roger Salemi, Jason Khan, Fareed Hansen, Michael Gupta, Kalpana Trautner, Barbara Grigoryan, Larissa |
author_facet | Germanos, George Light, Patrick Zoorob, Roger Salemi, Jason Khan, Fareed Hansen, Michael Gupta, Kalpana Trautner, Barbara Grigoryan, Larissa |
author_sort | Germanos, George |
collection | PubMed |
description | Objective: To validate the use of electronic algorithms based on International Classification of Diseases (ICD)-10 codes to identify outpatient visits for urinary tract infections (UTI), one of the most common reasons for antibiotic prescriptions. Methods: ICD-10 symptom codes (e.g., dysuria) alone or in addition to UTI diagnosis codes plus prescription of a UTI-relevant antibiotic were used to identify outpatient UTI visits. Chart review (gold standard) was performed by two reviewers to confirm diagnosis of UTI. The positive predictive value (PPV) that the visit was for UTI (based on chart review) was calculated for three different ICD-10 code algorithms using (1) symptoms only, (2) diagnosis only, or (3) both. Results: Of the 1087 visits analyzed, symptom codes only had the lowest PPV for UTI (PPV = 55.4%; 95%CI: 49.3–61.5%). Diagnosis codes alone resulted in a PPV of 85% (PPV = 84.9%; 95%CI: 81.1–88.2%). The highest PPV was obtained by using both symptom and diagnosis codes together to identify visits with UTI (PPV = 96.3%; 95%CI: 94.5–97.9%). Conclusions: ICD-10 diagnosis codes with or without symptom codes reliably identify UTI visits; symptom codes alone are not reliable. ICD-10 based algorithms are a valid method to study UTIs in primary care settings. |
format | Online Article Text |
id | pubmed-7558992 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75589922020-10-26 Validating Use of Electronic Health Data to Identify Patients with Urinary Tract Infections in Outpatient Settings Germanos, George Light, Patrick Zoorob, Roger Salemi, Jason Khan, Fareed Hansen, Michael Gupta, Kalpana Trautner, Barbara Grigoryan, Larissa Antibiotics (Basel) Article Objective: To validate the use of electronic algorithms based on International Classification of Diseases (ICD)-10 codes to identify outpatient visits for urinary tract infections (UTI), one of the most common reasons for antibiotic prescriptions. Methods: ICD-10 symptom codes (e.g., dysuria) alone or in addition to UTI diagnosis codes plus prescription of a UTI-relevant antibiotic were used to identify outpatient UTI visits. Chart review (gold standard) was performed by two reviewers to confirm diagnosis of UTI. The positive predictive value (PPV) that the visit was for UTI (based on chart review) was calculated for three different ICD-10 code algorithms using (1) symptoms only, (2) diagnosis only, or (3) both. Results: Of the 1087 visits analyzed, symptom codes only had the lowest PPV for UTI (PPV = 55.4%; 95%CI: 49.3–61.5%). Diagnosis codes alone resulted in a PPV of 85% (PPV = 84.9%; 95%CI: 81.1–88.2%). The highest PPV was obtained by using both symptom and diagnosis codes together to identify visits with UTI (PPV = 96.3%; 95%CI: 94.5–97.9%). Conclusions: ICD-10 diagnosis codes with or without symptom codes reliably identify UTI visits; symptom codes alone are not reliable. ICD-10 based algorithms are a valid method to study UTIs in primary care settings. MDPI 2020-08-25 /pmc/articles/PMC7558992/ /pubmed/32854205 http://dx.doi.org/10.3390/antibiotics9090536 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Germanos, George Light, Patrick Zoorob, Roger Salemi, Jason Khan, Fareed Hansen, Michael Gupta, Kalpana Trautner, Barbara Grigoryan, Larissa Validating Use of Electronic Health Data to Identify Patients with Urinary Tract Infections in Outpatient Settings |
title | Validating Use of Electronic Health Data to Identify Patients with Urinary Tract Infections in Outpatient Settings |
title_full | Validating Use of Electronic Health Data to Identify Patients with Urinary Tract Infections in Outpatient Settings |
title_fullStr | Validating Use of Electronic Health Data to Identify Patients with Urinary Tract Infections in Outpatient Settings |
title_full_unstemmed | Validating Use of Electronic Health Data to Identify Patients with Urinary Tract Infections in Outpatient Settings |
title_short | Validating Use of Electronic Health Data to Identify Patients with Urinary Tract Infections in Outpatient Settings |
title_sort | validating use of electronic health data to identify patients with urinary tract infections in outpatient settings |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7558992/ https://www.ncbi.nlm.nih.gov/pubmed/32854205 http://dx.doi.org/10.3390/antibiotics9090536 |
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