A quality-improvement approach to urgent-care antibiotic stewardship for respiratory tract infections during the COVID-19 pandemic: Lessons learned.

OBJECTIVE: We investigated a decrease in antibiotic prescribing for respiratory illnesses in 2 academic urgent-care clinics during the coronavirus disease 2019 (COVID-19) pandemic using semistructured clinician interviews. METHODS: We conducted a quality-improvement project from November 2020 to May 2021. We investigated provider antibiotic decision making using a mixed-methods explanatory design including interviews. We analyzed transcripts using a thematic framework approach to identify emergent themes. Our performance measure was antibiotic prescribing rate (APR) for encounters with respiratory diagnosis billing codes. We extracted billing and prescribing data from the electronic medical record and assessed differences using run charts, p charts and generalized linear regression. RESULTS: We observed significant reductions in the APR early during the COVID-19 pandemic (relative risk [RR], 0.20; 95% confidence interval [CI], 0.17-0.25), which was maintained over the study period (P < .001). The average APRs were 14% before the COVID-19 pandemic, 4% during the QI project, and 7% after the project. All providers prescribed less antibiotics for respiratory encounters during COVID-19, but only 25% felt their practice had changed. Themes from provider interviews included changing patient expectations and provider approach to respiratory encounters during COVID-19, the impact of increased telemedicine encounters, and the changing epidemiology of non-COVID-19 respiratory infections. CONCLUSIONS: Our findings suggest that the decrease in APR was likely multifactorial. The average APR decreased significantly during the pandemic. Although the APR was slightly higher after the QI project, it did not reach prepandemic levels. Future studies should explore how these factors, including changing patient expectations, can be leveraged to improve urgent-care antibiotic stewardship.

A 360 degree mixed-methods evaluation of a specialized COVID-19 outpatient clinic and remote patient monitoring program.

BACKGROUND: Our goals are to quantify the impact on acute care utilization of a specialized COVID-19 clinic with an integrated remote patient monitoring program in an academic medical center and further examine these data with stakeholder perceptions of clinic effectiveness and acceptability. METHODS: A retrospective cohort was drawn from enrolled and unenrolled ambulatory patients who tested positive in May through September 2020 matched on age, presence of comorbidities and other factors. Qualitative semi-structured interviews with patients, frontline clinician, and administrators were analyzed in an inductive-deductive approach to identify key themes. RESULTS: Enrolled patients were more likely to be hospitalized than unenrolled patients (N = 11/137 in enrolled vs 2/126 unenrolled, p = .02), reflecting a higher admittance rate following emergency department (ED) events among the enrolled vs unenrolled, though this was not a significant difference (46% vs 25%, respectively, p = .32). Thirty-eight qualitative interviews conducted June to October 2020 revealed broad stakeholder belief in the clinic's support of appropriate care escalation. Contrary to beliefs the clinic reduced inappropriate care utilization, no difference was seen between enrolled and unenrolled patients who presented to the ED and were not admitted (N = 10/137 in enrolled vs 8/126 unenrolled, p = .76). Administrators and providers described the clinic's integral role in allowing health services to resume in other areas of the health system following an initial lockdown. CONCLUSIONS: Acute care utilization and multi-stakeholder interviews suggest heightened outpatient observation through a specialized COVID-19 clinic and remote patient monitoring program may have contributed to an increase in appropriate acute care utilization. The clinic's role securing safe reopening of health services systemwide was endorsed as a primary, if unmeasured, benefit.

Anti-nucleocapsid antibody levels and pulmonary comorbid conditions are linked to post-COVID-19 syndrome.

BACKGROUNDProlonged symptoms after SARS-CoV-2 infection are well documented. However, which factors influence development of long-term symptoms, how symptoms vary across ethnic groups, and whether long-term symptoms correlate with biomarkers are points that remain elusive.METHODSAdult SARS-CoV-2 reverse transcription PCR-positive (RT-PCR-positive) patients were recruited at Stanford from March 2020 to February 2021. Study participants were seen for in-person visits at diagnosis and every 1-3 months for up to 1 year after diagnosis; they completed symptom surveys and underwent blood draws and nasal swab collections at each visit.RESULTSOur cohort (n = 617) ranged from asymptomatic to critical COVID-19 infections. In total, 40% of participants reported at least 1 symptom associated with COVID-19 six months after diagnosis. Median time from diagnosis to first resolution of all symptoms was 44 days; median time from diagnosis to sustained symptom resolution with no recurring symptoms for 1 month or longer was 214 days. Anti-nucleocapsid IgG level in the first week after positive RT-PCR test and history of lung disease were associated with time to sustained symptom resolution. COVID-19 disease severity, ethnicity, age, sex, and remdesivir use did not affect time to sustained symptom resolution.CONCLUSIONWe found that all disease severities had a similar risk of developing post-COVID-19 syndrome in an ethnically diverse population. Comorbid lung disease and lower levels of initial IgG response to SARS-CoV-2 nucleocapsid antigen were associated with longer symptom duration.TRIAL REGISTRATIONClinicalTrials.gov, NCT04373148.FUNDINGNIH UL1TR003142 CTSA grant, NIH U54CA260517 grant, NIEHS R21 ES03304901, Sean N Parker Center for Allergy and Asthma Research at Stanford University, Chan Zuckerberg Biohub, Chan Zuckerberg Initiative, Sunshine Foundation, Crown Foundation, and Parker Foundation.

Integrated plasma proteomic and single-cell immune signaling network signatures demarcate mild, moderate, and severe COVID-19.

The biological determinants underlying the range of coronavirus 2019 (COVID-19) clinical manifestations are not fully understood. Here, over 1,400 plasma proteins and 2,600 single-cell immune features comprising cell phenotype, endogenous signaling activity, and signaling responses to inflammatory ligands are cross-sectionally assessed in peripheral blood from 97 patients with mild, moderate, and severe COVID-19 and 40 uninfected patients. Using an integrated computational approach to analyze the combined plasma and single-cell proteomic data, we identify and independently validate a multi-variate model classifying COVID-19 severity (multi-class area under the curve [AUC]training = 0.799, p = 4.2e-6; multi-class AUCvalidation = 0.773, p = 7.7e-6). Examination of informative model features reveals biological signatures of COVID-19 severity, including the dysregulation of JAK/STAT, MAPK/mTOR, and nuclear factor κB (NF-κB) immune signaling networks in addition to recapitulating known hallmarks of COVID-19. These results provide a set of early determinants of COVID-19 severity that may point to therapeutic targets for prevention and/or treatment of COVID-19 progression.

Sustained Reduction in Urgent Care Antibiotic Prescribing During the Coronavirus Disease 2019 Pandemic: An Academic Medical Center's Experience.

We compared antibiotic prescribing before and during the -coronavirus disease 2019 (COVID-19) pandemic at 2 academic urgent care clinics and found a sustained decrease in prescribing driven by respiratory encounters and despite transitioning to telemedicine. Antibiotics were rarely prescribed during encounters for COVID-19 or COVID-19 symptoms. COVID-19 revealed opportunities for outpatient stewardship programs.

Qualitative Assessment of Rapid System Transformation to Primary Care Video Visits at an Academic Medical Center.

BACKGROUND: The coronavirus disease 2019 pandemic spurred health systems across the world to quickly shift from in-person visits to safer video visits. OBJECTIVE: To seek stakeholder perspectives on video visits' acceptability and effect 3 weeks after near-total transition to video visits. DESIGN: Semistructured qualitative interviews. SETTING: 6 Stanford general primary care and express care clinics at 6 northern California sites, with 81 providers, 123 staff, and 97 614 patient visits in 2019. PARTICIPANTS: 53 program participants (overlapping roles as medical providers [n = 20], medical assistants [n = 16], nurses [n = 4], technologists [n = 4], and administrators [n = 13]) were interviewed about video visit transition and challenges. INTERVENTION: In 3 weeks, express care and primary care video visits increased from less than 10% to greater than 80% and from less than 10% to greater than 75%, respectively. New video visit providers received video visit training and care quality feedback. New system workflows were created to accommodate the new visit method. MEASUREMENTS: 9 faculty, trained in qualitative research methods, conducted 53 stakeholder interviews in 4 days using purposeful (administrators and technologists) and convenience (medical assistant, nurses, and providers) sampling. A rapid qualitative analytic approach for thematic analysis was used. RESULTS: The analysis revealed 12 themes, including Pandemic as Catalyst; Joy in Medicine; Safety in Medicine; Slipping Through the Cracks; My Role, Redefined; and The New Normal. Themes were analyzed using the RE-AIM (reach, effectiveness, adoption, implementation, and maintenance) framework to identify critical issues for continued program utilization. LIMITATIONS: Evaluation was done immediately after deployment. Although viewpoints may have evolved later, immediate evaluation allowed for prompt program changes and identified broader issues to address for program sustainability. CONCLUSION: After pandemic-related systems transformation at Stanford, critical issues to sustain video visit long-term viability were identified. Specifically, technology ease of use must improve and support multiparty videoconferencing. Providers should be able to care for their patients, regardless of geography. Providers need decision-making support with virtual examination training and home-based patient diagnostics. Finally, ongoing video visit reimbursement should be commensurate with value to the patients' health and well-being. PRIMARY FUNDING SOURCE: Stanford Department of Medicine and Stanford Health Care.

New-onset IgG autoantibodies in hospitalized patients with COVID-19.

COVID-19 is associated with a wide range of clinical manifestations, including autoimmune features and autoantibody production. Here we develop three protein arrays to measure IgG autoantibodies associated with connective tissue diseases, anti-cytokine antibodies, and anti-viral antibody responses in serum from 147 hospitalized COVID-19 patients. Autoantibodies are identified in approximately 50% of patients but in less than 15% of healthy controls. When present, autoantibodies largely target autoantigens associated with rare disorders such as myositis, systemic sclerosis and overlap syndromes. A subset of autoantibodies targeting traditional autoantigens or cytokines develop de novo following SARS-CoV-2 infection. Autoantibodies track with longitudinal development of IgG antibodies recognizing SARS-CoV-2 structural proteins and a subset of non-structural proteins, but not proteins from influenza, seasonal coronaviruses or other pathogenic viruses. We conclude that SARS-CoV-2 causes development of new-onset IgG autoantibodies in a significant proportion of hospitalized COVID-19 patients and are positively correlated with immune responses to SARS-CoV-2 proteins.

A Specialized Acute COVID-19 Outpatient Clinic at an Academic Medical Center.

Health systems are challenged to provide equitable access to coronavirus disease 2019 (COVID-19) outpatient care during the pandemic. Infected patients may have difficulties accessing regular care and rely on emergency rooms. With the goal to improve system efficiencies and access to care, Stanford launched a designated outpatient COVID-19 "Care and Respiratory Observation of Patients With Novel Coronavirus" clinic in April 2020 in which all adult Stanford patients with newly diagnosed severe acute respiratory syndrome coronavirus 2 were offered follow-up for 2-3 weeks through video, telephone, and in-person encounters. Patients were triaged into risk categories and received home pulse oximeters based on a standardized protocol. Between April 15, 2020, and March 26, 2021, the Care and Respiratory Observation of Patients With Novel Coronavirus clinic enrolled 1317 patients. The clinic provided evaluation of Patients under Investigation, management of acute COVID-19 symptoms, care for COVID-19 patients after hospital discharge, clinical advice, and opportunities for research. The authors share crucial implementation lessons related to team agility, care personalization, and resource optimization.

Asthma phenotypes, associated comorbidities, and long-term symptoms in COVID-19.

BACKGROUND: It is unclear whether asthma and its allergic phenotype are risk factors for hospitalization or severe disease from SARS-CoV-2. METHODS: All patients over 28 days old testing positive for SARS-CoV-2 between March 1 and September 30, 2020, were retrospectively identified and characterized through electronic analysis at Stanford. A sub-cohort was followed prospectively to evaluate long-term COVID-19 symptoms. RESULTS: 168,190 patients underwent SARS-CoV-2 testing, and 6,976 (4.15%) tested positive. In a multivariate analysis, asthma was not an independent risk factor for hospitalization (OR 1.12 [95% CI 0.86, 1.45], p = .40). Among SARS-CoV-2-positive asthmatics, allergic asthma lowered the risk of hospitalization and had a protective effect compared with non-allergic asthma (OR 0.52 [0.28, 0.91], p = .026); there was no association between baseline medication use as characterized by GINA and hospitalization risk. Patients with severe COVID-19 disease had lower eosinophil levels during hospitalization compared with patients with mild or asymptomatic disease, independent of asthma status (p = .0014). In a patient sub-cohort followed longitudinally, asthmatics and non-asthmatics had similar time to resolution of COVID-19 symptoms, particularly lower respiratory symptoms. CONCLUSIONS: Asthma is not a risk factor for more severe COVID-19 disease. Allergic asthmatics were half as likely to be hospitalized with COVID-19 compared with non-allergic asthmatics. Lower levels of eosinophil counts (allergic biomarkers) were associated with a more severe COVID-19 disease trajectory. Recovery was similar among asthmatics and non-asthmatics with over 50% of patients reporting ongoing lower respiratory symptoms 3 months post-infection.