Publications by authors named "Sharon Tsay"

We performed a scoping review of articles published from 1 January 2000 to 4 January 2022 to characterize inequities in antibiotic prescribing and use across healthcare settings in the United States to inform antibiotic stewardship interventions and research. We included 34 observational studies, 21 cross-sectional survey studies, 4 intervention studies, and 2 systematic reviews. Most studies (55 of 61 [90%]) described the outpatient setting, 3 articles were from dentistry, 2 were from long-term care, and 1 was from acute care.

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Objective: Urgent care (UC) clinicians frequently prescribe inappropriate antibiotics for upper respiratory illnesses. In a national survey, pediatric UC clinicians reported family expectations as a primary driver for prescribing inappropriate antibiotics. Communication strategies effectively reduce unnecessary antibiotics while increasing family satisfaction.

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The distributions of antibiotic prescriptions by geography, antibiotic class, and prescriber specialty are similar in the US Centers for Medicare and Medicaid Services (CMS) Part D Prescriber Public Use Files and IQVIA Xponent dataset. Public health organizations and healthcare systems can use these data to track antibiotic use and guide antibiotic stewardship interventions for older adults.

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Background: Studies have shown that the Southern United States has higher rates of outpatient antibiotic prescribing rates compared with other regions in the country, but the reasons for this variation are unclear. We aimed to determine whether the regional variability in outpatient antibiotic prescribing for respiratory diagnoses can be explained by differences in prescriber clinical factors found in a commercially insured population.

Methods: We analyzed the 2017 IBM MarketScan Commercial Database of commercially insured individuals aged <65 years.

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Healthcare disparities and inequities exist in a variety of environments and manifest in diagnostic and therapeutic measures. In this commentary, we highlight our experience examining our organization's urgent care respiratory encounter antibiotic prescribing practices. We identified differences in prescribing based on several individual characteristics including patient age, race, ethnicity, preferred language, and patient and/or clinician gender.

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Objectives: The objective of the study was to compare the antibiotic treatment failure and recurrence rates between antibiotic agents (amoxicillin, amoxicillin-clavulanate, cefdinir, and azithromycin) for children with uncomplicated acute otitis media (AOM).

Study Design: We completed a retrospective cohort study of children 6 months-12 years of age with uncomplicated AOM identified in a nationwide claims database. The primary exposure was the antibiotic agent, and the primary outcomes were treatment failure and recurrence.

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Objectives: To describe acute respiratory illnesses (ARI) visits and antibiotic prescriptions in 2011 and 2018 across outpatient settings to evaluate progress in reducing unnecessary antibiotic prescribing for ARIs.

Design: Cross-sectional study.

Setting And Patients: Outpatient medical and pharmacy claims captured in the IBM MarketScan commercial database, a national convenience sample of privately insured individuals aged <65 years.

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Background: Widespread inappropriate antibiotic prescribing is a major driver of resistance. Little is known about antifungal prescribing practices in the United States, which is concerning given emerging resistance in fungi, particularly to azole antifungals.

Objective: We analyzed outpatient U.

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This study of Medicare claims data examines the prescribing of antibiotics to older US patients who had outpatient visits for COVID-19 in an effort to address unnecessary antibiotic use for viral infections.

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Antibiotic prescribing can lead to adverse drug events and antibiotic resistance, which pose ongoing urgent public health threats (1). Adults aged ≥65 years (older adults) are recipients of the highest rates of outpatient antibiotic prescribing and are at increased risk for antibiotic-related adverse events, including Clostridioides difficile and antibiotic-resistant infections and related deaths (1). Variation in antibiotic prescribing quality is primarily driven by prescribing patterns of individual health care providers, independent of patients' underlying comorbidities and diagnoses (2).

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Using a machine-learning model, we examined drivers of antibiotic prescribing for antibiotic-inappropriate acute respiratory illnesses in a large US claims data set. Antibiotics were prescribed in 11% of the 42 million visits in our sample. The model identified outpatient setting type, patient age mix, and state as top drivers of prescribing.

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Time constraints have been suggested as a potential driver of antibiotic overuse for acute respiratory tract infections. In this cross-sectional analysis of national data from visits to offices and emergency departments, we identified no statistically significant association between antibiotic prescribing and the duration of visits for acute respiratory tract infections.

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Background: The objective of our study was to describe trends in US outpatient antibiotic prescriptions from January through May 2020 and compare with trends in previous years (2017-2019).

Methods: We used data from the IQVIA Total Patient Tracker to estimate the monthly number of patients dispensed antibiotic prescriptions from retail pharmacies from January 2017 through May 2020. We averaged estimates from 2017 through 2019 and defined expected seasonal change as the average percent change from January to May 2017-2019.

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Background: Candidemia is a common healthcare-associated bloodstream infection with high morbidity and mortality. There are no current estimates of candidemia burden in the United States (US).

Methods: In 2017, the Centers for Disease Control and Prevention conducted active population-based surveillance for candidemia through the Emerging Infections Program in 45 counties in 9 states encompassing approximately 17 million persons (5% of the national population).

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Article Synopsis
  • On September 6, 2019, the CDC reported 215 potential cases of severe lung disease linked to e-cigarette use from 25 state health departments, as of August 27, 2019.
  • E-cigarettes create aerosols by heating a liquid that contains harmful materials, such as heavy metals and cancer-causing substances, which users inhale into their lungs.
  • The report provides interim case definitions and guidance for identifying and reporting instances of severe pulmonary illness associated with e-cigarette use, with plans for updates as new information emerges.
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Candidemia, a bloodstream infection caused by Candida species, is typically considered a health care-associated infection, with known risk factors including the presence of a central venous catheter, receipt of total parenteral nutrition or broad-spectrum antibiotics, recent abdominal surgery, admission to an intensive care unit, and prolonged hospitalization (1,2). Injection drug use (IDU) is not a common risk factor for candidemia; however, in the context of the ongoing opioid epidemic and corresponding IDU increases, IDU has been reported as an increasingly common condition associated with candidemia (3) and methicillin-resistant Staphylococcus aureus bacteremia (4). Little is known about the epidemiology of candidemia among persons who inject drugs.

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Background: Although trends in antibiotic use have been characterized, less is known about antifungal use. Data on antifungal use are important for understanding practice patterns, assessing emergence of antifungal resistance and developing antifungal stewardship programmes. We estimated national trends in inpatient antifungal use in the USA.

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Background: Transmission of multidrug-resistant Candida auris infection has been reported in the USA. To better understand its emergence and transmission dynamics and to guide clinical and public health responses, we did a molecular epidemiological investigation of C auris cases in the USA.

Methods: In this molecular epidemiological survey, we used whole-genome sequencing to assess the genetic similarity between isolates collected from patients in ten US states (California, Connecticut, Florida, Illinois, Indiana, Maryland, Massachusetts, New Jersey, New York, and Oklahoma) and those identified in several other countries (Colombia, India, Japan, Pakistan, South Africa, South Korea, and Venezuela).

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Candida auris is an emerging yeast that causes healthcare-associated infections. It can be misidentified by laboratories and often is resistant to antifungal medications. We describe an outbreak of C.

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Candidemia and Clostridium difficile infection (CDI) are important healthcare-associated infections that share certain risk factors. We sought to describe candidemia-CDI coinfection using population-based surveillance data. We found that nearly 1 in 10 patients with candidemia had CDI coinfection.

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Candida auris is an emerging, multidrug-resistant yeast that can spread in healthcare settings. It can cause invasive infections with high mortality and is difficult to identify using traditional yeast identification methods. Candida auris has been reported in more than a dozen countries, and as of August 2017, 112 clinical cases have been reported in the United States.

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