ArticleAntibiotics (Basel, Switzerland)2020
Validating Use of Electronic Health Data to Identify Patients with Urinary Tract Infections in Outpatient Settings.
Article in Antibiotics (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 26 citations in OpenAlex.
- Increased risk of incident and recurrent urinary tract infection in autosomal dominant polycystic kidney disease: a contemporary propensity score-matched cohort study.Internal and emergency medicine · 2026Article
- Active surveillance of drug safety in healthcare data: Sequential monitoring of bacterial and serious urinary tract infection risk in sodium-glucose cotransporter 2 inhibitor users.British journal of clinical pharmacology · 2026Article
- Comparative effectiveness of oral antibiotics to treat uncomplicated urinary tract infections in male outpatients.Journal of comparative effectiveness research · 2026Article
- Clinical factors and diagnoses associated with inappropriate urine culture ordering in primary care.Infection control and hospital epidemiology · 2026Article
- Risk Factors and Development of a Predictive Model for In-Hospital Mortality in Hemodynamically Stable Older Adults with Urinary Tract Infection.Medicina (Kaunas, Lithuania) · 2025Article
- The comparative effectiveness of telehealth versus primary care and collection of urine cultures on outcome in urinary tract infection.Medicine · 2025Observational
- Urine Testing in Children with Viral Symptoms: A Nationwide Analysis of Ambulatory Visits, 2014-2019.The Journal of pediatrics · 2025Article
- Evaluation of a new model of care for bladder management in a statewide spinal cord service.Spinal cord · 2025Article
- Interpretable Machine Learning Models for Predicting Critical Outcomes in Patients with Suspected Urinary Tract Infection with Positive Urine Culture.Diagnostics (Basel, Switzerland) · 2024Article
- Comparative Genitourinary Safety of In-class Sodium-Glucose Cotransporter-2 Inhibitors among Patients with Heart Failure with Preserved Ejection Fraction: A Cohort Study.American journal of cardiovascular drugs : drugs, devices, and other interventions · 2024Article
- Antibiotic prescription patterns in patients with suspected urinary tract infections in Ecuador.PloS one · 2023Article
- Examining Nursing Home Information Technology Maturity and Antibiotic Use Among Long-Term Care Residents.Journal of the American Medical Directors Association · 2022Article
- A Real-world Data Analysis of Intermittent Catheterization, Showing the Impact of Prelubricated Versus Hydrophilic Catheter Use on the Occurrence of Symptoms Suggestive of Urinary Tract Infections.European urology open science · 2022Article
- Case-based audit and feedback around a decision aid improved antibiotic choice and duration for uncomplicated cystitis in primary care clinics.Family medicine and community health · 2021Article
- Frailty increases the risk for developing urinary tract infection among 79,887 patients with diabetic mellitus and chronic kidney disease.BMC geriatrics · 2021Article
- Trends in Pediatric Primary Care Visits During the Coronavirus Disease of 2019 Pandemic.Academic pediatricsArticle
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo 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.
methodsICD-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.
resultsOf 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%).
conclusionsICD-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.
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