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      Validating Use of Electronic Health Data to Identify Patients with Urinary Tract Infections in Outpatient Settings

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          Abstract

          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.

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          Most cited references 27

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          Antibiotic prescribing for adults in ambulatory care in the USA, 2007-09.

          To determine patterns of ambulatory antibiotic prescribing in US adults, including the use of broad-spectrum versus narrow-spectrum agents, to provide a description of the diagnoses for which antibiotics are prescribed and to identify patient and physician factors associated with broad-spectrum antibiotic prescribing.
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            National Hospital Ambulatory Medical Care Survey: 2007 emergency department summary.

            This report presents data on U.S. emergency department (ED) visits in 2007, with statistics on hospital, patient, and visit characteristics. Data are from the 2007 National Hospital Ambulatory Medical Care Survey, which uses a national probability sample of visits to emergency departments of nonfederal general and short-stay hospitals in the United States. Sample data were weighted to produce annual national estimates. In 2007, there were about 117 million ED visits in the United States. About 25 percent of visits were covered by Medicaid or the State Children's Health Insurance Program (SCHIP). About one-fifth of ED visits by children younger than 15 years of age were to pediatric EDs. There were 121 ED visits for asthma per 10,000 children under 5 years of age. The leading injury-related cause of ED visits was unintentional falls. Two percent of visits resulted in admission to an observation unit. Electronic medical records were used in 62 percent of EDs.
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              Review: electronic health records and the reliability and validity of quality measures: a review of the literature.

              Previous reviews of research on electronic health record (EHR) data quality have not focused on the needs of quality measurement. The authors reviewed empirical studies of EHR data quality, published from January 2004, with an emphasis on data attributes relevant to quality measurement. Many of the 35 studies reviewed examined multiple aspects of data quality. Sixty-six percent evaluated data accuracy, 57% data completeness, and 23% data comparability. The diversity in data element, study setting, population, health condition, and EHR system studied within this body of literature made drawing specific conclusions regarding EHR data quality challenging. Future research should focus on the quality of data from specific EHR components and important data attributes for quality measurement such as granularity, timeliness, and comparability. Finally, factors associated with poor or variability in data quality need to be better understood and effective interventions developed.
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                Author and article information

                Journal
                Antibiotics (Basel)
                Antibiotics (Basel)
                antibiotics
                Antibiotics
                MDPI
                2079-6382
                25 August 2020
                September 2020
                : 9
                : 9
                Affiliations
                [1 ]Department of Family and Community Medicine, Baylor College of Medicine, Houston, TX 77030, USA; george@ 123456germanos.md (G.G.); roger.zoorob@ 123456bcm.edu (R.Z.); jsalemi@ 123456usf.edu (J.S.); fareed.khan@ 123456bcm.edu (F.K.); grigorya@ 123456bcm.edu (L.G.)
                [2 ]Baylor College of Medicine, Houston, TX 77030, USA; patrick.light@ 123456bcm.edu
                [3 ]Section of Infectious Diseases, Department of Medicine, Boston Veterans Affairs Healthcare System and Boston University School of Medicine, Boston, MA 02118, USA; kalpana.gupta@ 123456va.gov
                [4 ]Houston VA Center for Innovations in Quality, Effectiveness and Safety (IQuESt), Michael E. DeBakey Veterans Affairs Medical Center, Houston, TX 77030, USA; trautner@ 123456bcm.edu
                [5 ]Section of Infectious Diseases, Departments of Medicine and Surgery, Baylor College of Medicine, Houston, TX 77030, USA
                Author notes
                [* ]Correspondence: mahansen@ 123456bcm.edu ; Tel.: +1-(713)-798-0114
                Article
                antibiotics-09-00536
                10.3390/antibiotics9090536
                7558992
                32854205
                © 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/).

                Categories
                Article

                ppv, cystitis, outpatient, urinary tract infection, icd, validation

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