Patient Experience With an In-Home COVID Virtual Observation Unit: An Analysis.

We performed a retrospective cohort study of patients admitted to a novel, home-based COVID Virtual Observation Unit (CVOU) from an urban, university-affiliated emergency department with ∼112,000 annual visits. Telephone-based survey questions were administered by nursing staff working with the program. Of 402 patients enrolled in the CVOU, 221 (55%) were able to be contacted during the study period; 180 (45%) agreed to participate in the telephone interview. Overall, 95% (169 out of 177) of the surveyed patients reported 8 to 10 on the likelihood to recommend CVOU and 82% (100 out of 122) rated the quality of care as 10 out of 10. Over 90% of respondents reported that all role groups (nurses, paramedics, and physicians) treated them with courtesy and respect, explained things in an understandable way, and listened to them carefully. Over 80% of respondents reported that the program kept them at home. In summary, patient experiences with this novel home-based care program were highly positive. These data help underscore the importance of patient-centeredness in home-based care, and further support the concept of these innovative care models.

Implementing a COVID-19 Virtual Observation Unit in Emergency Medicine: Frontline Clinician and Staff Experiences.

The COVID-19 pandemic pushed hospitals to deliver care outside of their four walls. To successfully scale virtual care delivery, it is important to understand how its implementation affects frontline workers, including their teamwork and patient-provider interactions. We conducted in-depth interviews of 17 clinicians and staff involved with the COVID-19 Virtual Observation Unit (CVOU) in the emergency department (ED) of an academic hospital. The program leveraged remote patient monitoring and mobile integrated health care. In the CVOU (vs. the ED), participants observed increases in interactions among clinicians and staff, patient participation in care delivery, attention to nonmedical factors, and involvement of coordinators and paramedics in patient care. These changes were associated with unintended, positive consequences for staff, namely, feeling heard, experience of meaningfulness, and positive attitudes toward virtual care. This study advances research on reconfiguration of roles following implementation of new practices using digital tools, virtual work interactions, and at-home care delivery.

Evaluation of a COVID-19 emergency department observation protocol.

OBJECTIVES: Caring for patients with COVID-19 has resulted in a considerable strain on hospital capacity. One strategy to mitigate crowding is the use of ED-based observation units to care for patients who may have otherwise required hospitalization. We sought to create a COVID-19 Observation Protocol for our ED Observation Unit (EDOU) for patients with mild to moderate COVID-19 to allow emergency physicians (EP) to gather more data for or against admission and intervene in a timely manner to prevent clinical deterioration. METHODS: This was a retrospective cohort study which included all patients who were positive for SARS-CoV-2 at the time of EDOU placement for the primary purpose of monitoring COVID-19 disease. Our institution updated the ED Observation protocol partway into the study period. Descriptive statistics were used to characterize demographics. We assessed for differences in demographics, clinical characteristics, and outcomes between admitted and discharged patients. Multivariate logistic regression models were used to assess whether meeting criteria for the ED observation protocols predicted disposition. RESULTS: During the time period studied, 120 patients positive for SARS-CoV-2 were placed in the EDOU for the primary purpose of monitoring COVID-19 disease. The admission rate for patients in the EDOU during the study period was 35%. When limited to patients who met criteria for version 1 or version 2 of the protocol, this dropped to 21% and 25% respectively. Adherence to the observation protocol was 62% and 60% during the time of version 1 and version 2 implementation, respectively. Using a multivariate logistic regression, meeting criteria for either version 1 (OR = 3.17, 95% CI 1.34-7.53, p < 0.01) or version 2 (OR = 3.18, 95% CI 1.39-7.30, p < 0.01) of the protocol resulted in a higher likelihood of discharge. There was no difference in EDOU LOS between admitted and discharged patients. CONCLUSION: An ED observation protocol can be successfully created and implemented for COVID-19 which allows the EP to determine which patients warrant hospitalization. Meeting protocol criteria results in an acceptable admission rate.

Neighborhood Disadvantage Measures and COVID-19 Cases in Boston, 2020.

OBJECTIVE: Understanding the pattern of population risk for coronavirus disease 2019 (COVID-19) is critically important for health systems and policy makers. The objective of this study was to describe the association between neighborhood factors and number of COVID-19 cases. We hypothesized an association between disadvantaged neighborhoods and clusters of COVID-19 cases. METHODS: We analyzed data on patients presenting to a large health care system in Boston during February 5-May 4, 2020. We used a bivariate local join-count procedure to determine colocation between census tracts with high rates of neighborhood demographic characteristics (eg, Hispanic race/ethnicity) and measures of disadvantage (eg, health insurance status) and COVID-19 cases. We used negative binomial models to assess independent associations between neighborhood factors and the incidence of COVID-19. RESULTS: A total of 9898 COVID-19 patients were in the cohort. The overall crude incidence in the study area was 32 cases per 10 000 population, and the adjusted incidence per census tract ranged from 2 to 405 per 10 000 population. We found significant colocation of several neighborhood factors and the top quintile of cases: percentage of population that was Hispanic, non-Hispanic Black, without health insurance, receiving Supplemental Nutrition Assistance Program benefits, and living in poverty. Factors associated with increased incidence of COVID-19 included percentage of population that is Hispanic (incidence rate ratio [IRR] = 1.25; 95% CI, 1.23-1.28) and percentage of households living in poverty (IRR = 1.25; 95% CI, 1.19-1.32). CONCLUSIONS: We found a significant association between neighborhoods with high rates of disadvantage and COVID-19. Policy makers need to consider these health inequities when responding to the pandemic and planning for subsequent health needs.