9 research outputs found

    Implementing a Virtual Emergency Department: Qualitative Study Using the Normalization Process Theory

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    BACKGROUND: COVID-19 necessitated the rapid implementation and uptake of virtual health care; however, virtual care's potential role remains unclear in the urgent care setting. In December 2020, the first virtual emergency department (ED) in the Greater Toronto Area was piloted at Sunnybrook Health Sciences Centre by connecting patients to emergency physicians through an online portal. OBJECTIVE: This study aims to understand whether and how ED physicians were able to integrate a virtual ED alongside in-person operations. METHODS: We conducted semistructured interviews with ED physicians guided by the Normalization Process Theory (NPT). The NPT provides a framework to understand how individuals and teams navigate the process of embedding new models of care as part of normal practice. All physicians who had worked within the virtual ED model were invited to participate. Data were analyzed using a combination of inductive and deductive techniques informed by the NPT. RESULTS: A total of 14 physicians were interviewed. Participant experiences were categorized into 1 of 2 groups: 1 group moved to normalize the virtual ED in practice, while the other described barriers to routine adoption. These groups differed in their perception of the patient benefits as well as the perceived role in the virtual ED. The group that normalized the virtual ED model saw value for patients (coherence) and was motivated by patient satisfaction witnessed (reflexive monitoring) at the end of the virtual appointment. By contrast, the other group did not find virtual ED work reflective of the perceived role of urgent care (cognitive participation) and felt their skills as ED physicians were underutilized. The limited ability to examine patients and a sense that patient issues were not fully resolved at the end of the virtual appointment caused frustration among the second group. CONCLUSIONS: As further digital integration within the health care system occurs, it will be essential to support the evolution of staff skill sets to ensure physicians are satisfied with the care they are providing to their patients, while also ensuring the technology and process are efficient

    Building Compassionate Experience Through Compassionate Action: Qualitative Behavioral Analysis

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    BackgroundThe acceleration of technology-based primary care during the COVID-19 pandemic outpaced the ability to understand whether and how it impacts care delivery and outcomes. As technology-based care continues to evolve, focusing on the core construct of compassion in a primary care context will help ensure high-quality patient care and increased patient autonomy and satisfaction. The ability to successfully operationalize the use of technology in patient-clinician interactions hinges on understanding not only how compassionate care is experienced in this context but also how clinicians can create it. ObjectiveThe objectives of this study were to understand whether and how compassionate behaviors are experienced in technology-based primary care interactions and identify the individual and contextual drivers that influence whether and how these behaviors occur. MethodsWe conducted a series of qualitative one-on-one interviews with primary care physicians, nurses, and patients. Qualitative data were initially analyzed using an inductive thematic analysis approach to identify preliminary themes for each participant group independently. We then looked across participant groups to identify areas of alignment and distinction. Descriptions of key behaviors that participants identified as elements of a compassionate interaction and descriptions of key drivers of these behaviors were inductively coded and defined at this stage. ResultsA total of 74 interviews were conducted with 40 patients, 20 nurses, and 14 primary care physicians. Key behaviors that amplified the experience of compassion included asking the patient’s modality preference, using video to establish technology-based presence, sharing the screen, and practicing effective communication. Participants’ knowledge or skills as well as their beliefs and emotions influenced whether or not these behaviors occurred. Contextual elements beyond participants’ control influenced technology-based interactions, including resource access, funding structures, culture, regulatory standards, work structure, societal influence, and patient characteristics and needs. A high-yield, evidence-based approach to address the identified drivers of compassion-focused clinician behavior includes a combination of education, training, and enablement. ConclusionsMuch of the patient experience is influenced by clinician behavior; however, clinicians need a supportive system and adequate supports to evolve new ways of working to create the experience of compassionate care. The current state of technology-based care operationalization has led to widespread burnout, societal pressure, and shifting expectations of both clinicians and the health system more broadly, threatening the ability to deliver compassionate care. For clinicians to exhibit compassionate behaviors, they need more than just adequate supports; they also need to receive compassion from and experience the humanity of their patients

    sj-docx-1-jtt-10.1177_1357633X231167905 - Supplemental material for Understanding how virtual care has shifted primary care interactions and patient experience: A qualitative analysis

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    Supplemental material, sj-docx-1-jtt-10.1177_1357633X231167905 for Understanding how virtual care has shifted primary care interactions and patient experience: A qualitative analysis by Kelly Wu, Marlena Dang Nguyen, Geneviève Rouleau, Rhea Azavedo, Diya Srinivasan, and Laura Desveaux in Journal of Telemedicine and Telecare</p

    Comparison of test-negative and syndrome-negative controls in SARS-CoV-2 vaccine effectiveness evaluations for preventing COVID-19 hospitalizations in the United States

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    BackgroundTest-negative design (TND) studies have produced validated estimates of vaccine effectiveness (VE) for influenza vaccine studies. However, syndrome-negative controls have been proposed for differentiating bias and true estimates in VE evaluations for COVID-19. To understand the use of alternative control groups, we compared characteristics and VE estimates of syndrome-negative and test-negative VE controls.MethodsAdults hospitalized at 21 medical centers in 18 states March 11-August 31, 2021 were eligible for analysis. Case patients had symptomatic acute respiratory infection (ARI) and tested positive for SARS-CoV-2. Control groups were test-negative patients with ARI but negative SARS-CoV-2 testing, and syndrome-negative controls were without ARI and negative SARS-CoV-2 testing. Chi square and Wilcoxon rank sum tests were used to detect differences in baseline characteristics. VE against COVID-19 hospitalization was calculated using logistic regression comparing adjusted odds of prior mRNA vaccination between cases hospitalized with COVID-19 and each control group.Results5811 adults (2726 cases, 1696 test-negative controls, and 1389 syndrome-negative controls) were included. Control groups differed across characteristics including age, race/ethnicity, employment, previous hospitalizations, medical conditions, and immunosuppression. However, control-group-specific VE estimates were very similar. Among immunocompetent patients aged 18-64&nbsp;years, VE was 93&nbsp;% (95&nbsp;% CI: 90-94) using syndrome-negative controls and 91&nbsp;% (95&nbsp;% CI: 88-93) using test-negative controls.ConclusionsDespite demographic and clinical differences between control groups, the use of either control group produced similar VE estimates across age groups and immunosuppression status. These findings support the use of test-negative controls and increase confidence in COVID-19 VE estimates produced by test-negative design studies

    Effectiveness of mRNA Vaccination in Preventing COVID-19–Associated Invasive Mechanical Ventilation and Death — United States, March 2021–January 2022

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    COVID-19 mRNA vaccines (BNT162b2 [Pfizer-BioNTech] and mRNA-1273 [Moderna]) are effective at preventing COVID-19-associated hospitalization (1-3). However, how well mRNA vaccines protect against the most severe outcomes of these hospitalizations, including invasive mechanical ventilation (IMV) or death is uncertain. Using a case-control design, mRNA vaccine effectiveness (VE) against COVID-19-associated IMV and in-hospital death was evaluated among adults aged ≥18 years hospitalized at 21 U.S. medical centers during March 11, 2021-January 24, 2022. During this period, the most commonly circulating variants of SARS-CoV-2, the virus that causes COVID-19, were B.1.1.7 (Alpha), B.1.617.2 (Delta), and B.1.1.529 (Omicron). Previous vaccination (2 or 3 versus 0 vaccine doses before illness onset) in prospectively enrolled COVID-19 case-patients who received IMV or died within 28 days of hospitalization was compared with that among hospitalized control patients without COVID-19. Among 1,440 COVID-19 case-patients who received IMV or died, 307 (21%) had received 2 or 3 vaccine doses before illness onset. Among 6,104 control-patients, 4,020 (66%) had received 2 or 3 vaccine doses. Among the 1,440 case-patients who received IMV or died, those who were vaccinated were older (median age&nbsp;=&nbsp;69 years), more likely to be immunocompromised* (40%), and had more chronic medical conditions compared with unvaccinated case-patients (median age&nbsp;=&nbsp;55 years; immunocompromised&nbsp;=&nbsp;10%; p&lt;0.001 for both). VE against IMV or in-hospital death was 90% (95% CI&nbsp;=&nbsp;88%-91%) overall, including 88% (95% CI&nbsp;=&nbsp;86%-90%) for 2 doses and 94% (95% CI&nbsp;=&nbsp;91%-96%) for 3 doses, and 94% (95% CI&nbsp;=&nbsp;88%-97%) for 3 doses during the Omicron-predominant period. COVID-19 mRNA vaccines are highly effective in preventing COVID-19-associated death and respiratory failure treated with IMV. CDC recommends that all persons eligible for vaccination get vaccinated and stay up to date with COVID-19 vaccination (4)
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