Reduction in outpatient antibiotic utilization: An unintended benefit of the COVID-19 pandemic?

Background: The COVID-19 pandemic heavily affected healthcare delivery systems in the United States. However, little is known about its impact on overall antimicrobial consumption, especially in outpatient settings. We assessed the impact of the COVID-19 pandemic on antimicrobial consumption in both outpatient and inpatient (acute-care, long-term care, and mental health) settings in the Veterans' Health Administration (VHA) during the 2 years before and after the start of the pandemic. Methods: We conducted a retrospective study for all patients who received care within the VHA from January 2018 to December 2021. We used antibiotic days as the primary outcome measure (days of therapy for inpatient settings and dispensed days supply for outpatient settings), and we obtained data for antimicrobial consumption from the VHA Corporate Data Warehouse. Antibiotics were categorized into classes by the NHSN protocol and included only systemic agents (oral and parenteral). We defined 2018–2019 as the prepandemic period and 2020–2021 as the pandemic period. We compared the relative and absolute difference in antibiotic consumption between the 2 periods. Results: Across all periods, 8.3 million patients received care in the VHA, and an average of 28,709,680 antibiotic days were prescribed per year. Overall, 92.9% of all antibiotic days were outpatient and 7.1% were inpatient. Total antibiotic days during the pandemic period decreased by 12.4% compared to the prepandemic period (pandemic period: 53,613,840 and prepandemic period: 61,224,878). This reduction was primarily driven by reductions in outpatient settings (relative reduction: 12.7% and absolute reduction: 7,254,880 antibiotic days over 2 years), but antibiotic days in inpatient settings decreased more modestly (relative reduction: 8.4% and absolute reduction: 356,158 antibiotic days over 2 years) (Fig. 1). When frequently prescribed antimicrobials were categorized by classes, fluoroquinolones and lincosamides showed the largest decreases (fluoroquinolones: 29.2% reduction and lincosamides: 27.2% reduction). Tetracyclines and sulfamethoxazole–trimethoprim had the smallest reductions (5.2% and 11.2%, respectively). Conclusions: Compared to the prepandemic period, the pandemic was associated with a substantial reduction in overall antibiotic consumption, especially in outpatient settings, which accounted for 95% of the overall reduction despite being outside the domain of most traditional antibiotic stewardship programs. The impact of the pandemic was most modest in the use of tetracyclines and trimethoprim–sulfamethoxazole and was most prominent in the use of fluoroquinolones and lincosamides. Further studies are required to improve the causal inference between the COVID-19 pandemic and this reduction in antibiotic consumption, as well as its impact on patient outcomes.Funding: NoneDisclosures: None

Prediction models for severe manifestations and mortality due to COVID-19: A systematic review.

BACKGROUND: Throughout 2020, the coronavirus disease 2019 (COVID-19) has become a threat to public health on national and global level. There has been an immediate need for research to understand the clinical signs and symptoms of COVID-19 that can help predict deterioration including mechanical ventilation, organ support, and death. Studies thus far have addressed the epidemiology of the disease, common presentations, and susceptibility to acquisition and transmission of the virus; however, an accurate prognostic model for severe manifestations of COVID-19 is still needed because of the limited healthcare resources available. OBJECTIVE: This systematic review aims to evaluate published reports of prediction models for severe illnesses caused COVID-19. METHODS: Searches were developed by the primary author and a medical librarian using an iterative process of gathering and evaluating terms. Comprehensive strategies, including both index and keyword methods, were devised for PubMed and EMBASE. The data of confirmed COVID-19 patients from randomized control studies, cohort studies, and case-control studies published between January 2020 and May 2021 were retrieved. Studies were independently assessed for risk of bias and applicability using the Prediction Model Risk Of Bias Assessment Tool (PROBAST). We collected study type, setting, sample size, type of validation, and outcome including intubation, ventilation, any other type of organ support, or death. The combination of the prediction model, scoring system, performance of predictive models, and geographic locations were summarized. RESULTS: A primary review found 445 articles relevant based on title and abstract. After further review, 366 were excluded based on the defined inclusion and exclusion criteria. Seventy-nine articles were included in the qualitative analysis. Inter observer agreement on inclusion 0.84 (95%CI 0.78-0.89). When the PROBAST tool was applied, 70 of the 79 articles were identified to have high or unclear risk of bias, or high or unclear concern for applicability. Nine studies reported prediction models that were rated as low risk of bias and low concerns for applicability. CONCLUSION: Several prognostic models for COVID-19 were identified, with varying clinical score performance. Nine studies that had a low risk of bias and low concern for applicability, one from a general public population and hospital setting. The most promising and well-validated scores include Clift et al.,15 and Knight et al.,18 which seem to have accurate prediction models that clinicians can use in the public health and emergency department setting.

Successful multimodal measures preventing coronavirus disease 2019 (COVID-19) outbreaks without universal frequent testing within long-term care units in the Midwestern Veterans' Health Care Network.

Coronavirus disease 2019 (COVID-19) remains a serious threat for long-term care facilities, and frequent screening of employees and residents places a substantial burden on those facilities. We report our successful multimodal prevention measures without frequent testing, which resulted in no cases within 20 nursing home units over the first 6 months of the pandemic.