Acceptance of a computer vision facilitated protocol to measure adherence to face mask use: a single-site, observational cohort study among hospital staff.

OBJECTIVES: Mask adherence continues to be a critical public health measure to prevent transmission of aerosol pathogens, such as SARS-CoV-2. We aimed to develop and deploy a computer vision algorithm to provide real-time feedback of mask wearing among staff in a hospital. DESIGN: Single-site, observational cohort study. SETTING: An urban, academic hospital in Boston, Massachusetts, USA. PARTICIPANTS: We enrolled adult hospital staff entering the hospital at a key ingress point. INTERVENTIONS: Consenting participants entering the hospital were invited to experience the computer vision mask detection system. Key aspects of the detection algorithm and feedback were described to participants, who then completed a quantitative assessment to understand their perceptions and acceptance of interacting with the system to detect their mask adherence. OUTCOME MEASURES: Primary outcomes were willingness to interact with the mask system, and the degree of comfort participants felt in interacting with a public facing computer vision mask algorithm. RESULTS: One hundred and eleven participants with mean age 40 (SD15.5) were enrolled in the study. Males (47.7%) and females (52.3%) were equally represented, and the majority identified as white (N=54, 49%). Most participants (N=97, 87.3%) reported acceptance of the system and most participants (N=84, 75.7%) were accepting of deployment of the system to reinforce mask adherence in public places. One third of participants (N=36) felt that a public facing computer vision system would be an intrusion into personal privacy.Public-facing computer vision software to detect and provide feedback around mask adherence may be acceptable in the hospital setting. Similar systems may be considered for deployment in locations where mask adherence is important.

Coronavirus disease 2019 (COVID-19) screening system utilizing daily symptom attestation helps identify hospital employees who should be tested to protect patients and coworkers.

OBJECTIVE: To investigate the effectiveness of a daily attestation system used by employees of a multi-institutional academic medical center, which comprised of symptom-screening, self-referrals to the Occupational Health Services team, and/or a severe acute respiratory coronavirus virus 2 (SARS-CoV-2) test. DESIGN: We conducted a retrospective cohort study of all employee attestations and SARS-CoV-2 tests performed between March and June 2020. SETTING: A large multi-institutional academic medical center, including both inpatient and ambulatory settings. PARTICIPANTS: All employees who worked at the study site. METHODS: Data were combined from the attestation system (COVIDPass), the employee database, and the electronic health records and were analyzed using descriptive statistics including χ2, Wilcoxon, and Kruskal-Wallis tests. We investigated whether an association existed between symptomatic attestations by the employees and the employee testing positive for SARS-CoV-2. RESULTS: After data linkage and cleaning, there were 2,117,298 attestations submitted by 65,422 employees between March and June 2020. Most attestations were asymptomatic (99.9%). The most commonly reported symptoms were sore throat (n = 910), runny nose (n = 637), and cough (n = 570). Among the 2,026 employees who ever attested that they were symptomatic, 905 employees were tested within 14 days of a symptomatic attestation, and 114 (13%) of these tests were positive. The most common symptoms associated with a positive SARS-CoV-2 test were anosmia (23% vs 4%) and fever (46% vs 19%). CONCLUSIONS: Daily symptom attestations among healthcare workers identified a handful of employees with COVID-19. Although the number of positive tests was low, attestations may help keep unwell employees off campus to prevent transmissions.

Symptom monitoring after coronavirus disease 2019 (COVID-19) vaccination in a large integrated healthcare system: Separating symptoms from severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection.

OBJECTIVE: To describe the incidence of systemic overlap and typical coronavirus disease 2019 (COVID-19) symptoms in healthcare personnel (HCP) following COVID-19 vaccination and association of reported symptoms with diagnosis of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection in the context of public health recommendations regarding work exclusion. DESIGN: This prospective cohort study was conducted between December 16, 2020, and March 14, 2021, with HCP who had received at least 1 dose of either the Pfizer-BioNTech or Moderna COVID-19 vaccine. SETTING: Large healthcare system in New England. INTERVENTIONS: HCP were prompted to complete a symptom survey for 3 days after each vaccination. Reported symptoms generated automated guidance regarding symptom management, SARS-CoV-2 testing requirements, and work restrictions. Overlap symptoms (ie, fever, fatigue, myalgias, arthralgias, or headache) were categorized as either lower or higher severity. Typical COVID-19 symptoms included sore throat, cough, nasal congestion or rhinorrhea, shortness of breath, ageusia and anosmia. RESULTS: Among 64,187 HCP, a postvaccination electronic survey had response rates of 83% after dose 1 and 77% after dose 2. Report of ≥3 lower-severity overlap symptoms, ≥1 higher-severity overlap symptoms, or at least 1 typical COVID-19 symptom after dose 1 was associated with increased likelihood of testing positive. HCP with prior COVID-19 infection were significantly more likely to report severe overlap symptoms after dose 1. CONCLUSIONS: Reported overlap symptoms were common; however, only report of ≥3 low-severity overlap symptoms, at least 1 higher-severity overlap symptom, or any typical COVID-19 symptom were associated with infection. Work-related restrictions for overlap symptoms should be reconsidered.

Association of Self-reported High-Risk Allergy History With Allergy Symptoms After COVID-19 Vaccination.

Importance: Allergic history in individuals with confirmed anaphylaxis to a messenger RNA (mRNA) COVID-19 vaccine is common. However, the risk factors for allergy symptoms after receiving the vaccine are unknown. Objective: To assess the association between self-reported history of high-risk allergy and self-reported allergic reactions after mRNA COVID-19 vaccination of health care employees. Design, Setting, and Participants: This cohort study obtained demographic, medical, and vaccine administration data of employees of Mass General Brigham from the institutional electronic health record. Employees who received at least 1 dose of an mRNA COVID-19 vaccine between December 14, 2020, and February 1, 2021, and who completed at least 1 postvaccination symptom survey in the 3 days after vaccination were included. Exposures: Self-reported history of high-risk allergy, defined as a previous severe allergic reaction to a vaccine, an injectable medication, or other allergen. Main Outcomes and Measures: The primary outcome was 1 or more self-reported allergic reactions in the first 3 days after dose 1 or dose 2 of an mRNA COVID-19 vaccine. Multivariable log binomial regression was used to assess the association between allergic reactions and high-risk allergy status. Results: A total of 52 998 health care employees (mean [SD] age, 42 [14] years; 38 167 women [72.0%]) were included in the cohort, of whom 51 706 (97.6%) received 2 doses of an mRNA COVID-19 vaccine and 474 (0.9%) reported a history of high-risk allergy. Individuals with vs without a history of high-risk allergy reported more allergic reactions after receiving dose 1 or 2 of the vaccine (11.6% [n = 55] vs 4.7% [n = 2461]). In the adjusted model, a history of high-risk allergy was associated with an increased risk of allergic reactions (adjusted relative risk [aRR], 2.46; 95% CI, 1.92-3.16), with risk being highest for hives (aRR, 3.81; 95% CI, 2.33-6.22) and angioedema (aRR, 4.36; 95% CI, 2.52-7.54). Conclusions and Relevance: This cohort study found that self-reported history of high-risk allergy was associated with an increased risk of self-reported allergic reactions within 3 days of mRNA COVID-19 vaccination. However, reported allergy symptoms did not impede the completion of the 2-dose vaccine protocol among a cohort of eligible health care employees, supporting the overall safety of mRNA COVID-19 vaccine.

Virtual Team Rounding: A Cross-Specialty Inpatient Care Staffing Program to Manage COVID-19 Surges.

PROBLEM: The SARS-CoV-2 (COVID-19) pandemic presented numerous challenges to inpatient care, including overtaxed inpatient medicine services, surges in patient censuses, disrupted patient care and educational activities for trainees, underused providers in certain specialties, and personal protective equipment shortages and new requirements for physical distancing. In March 2020, as the COVID-19 surge began, an interdisciplinary group of administrators, providers, and trainees at Brigham and Women's Hospital created an inpatient virtual staffing model called the Virtual Team Rounding Program (VTRP). APPROACH: The conceptual framework guiding VTRP development was rapid-cycle innovation. The VTRP was designed iteratively using feedback from residents, physician assistants, attendings, and administrators from March to June 2020. The VTRP trained and deployed a diverse set of providers across specialties as "virtual rounders" to support inpatient teams by joining and participating in rounds via videoconference and completing documentation tasks during and after rounds. The program was rapidly scaled up from March to June 2020. OUTCOMES: In a survey of inpatient providers at the end of the pilot phase, 10/10 (100%) respondents reported they were getting either "a lot" or "a little" benefit from the VTRP and did not find the addition of the virtual rounder burdensome. During the scaling phase, the program grew to support 24 teams. In a survey at the end of the contraction phase, 117/187 (62.6%) inpatient providers who worked with a virtual rounder felt the rounder saved them time. VTRP leadership collaboratively and iteratively developed best practices for challenges encountered during implementation. NEXT STEPS: Virtual rounding provides a valuable extension of inpatient teams to manage COVID-19 surges. Future work will quantitatively and qualitatively assess the impact of the VTRP on inpatient provider satisfaction and well-being, virtual rounders' experiences, and patient care outcomes.

Digital triage: Novel strategies for population health management in response to the COVID-19 pandemic.

The COVID-19 pandemic has created unique challenges for the U.S. healthcare system due to the staggering mismatch between healthcare system capacity and patient demand. The healthcare industry has been a relatively slow adopter of digital innovation due to the conventional belief that humans need to be at the center of healthcare delivery tasks. However, in the setting of the COVID-19 pandemic, artificial intelligence (AI) may be used to carry out specific tasks such as pre-hospital triage and enable clinicians to deliver care at scale. Recognizing that the majority of COVID-19 cases are mild and do not require hospitalization, Partners HealthCare (now Mass General Brigham) implemented a digitally-automated pre-hospital triage solution to direct patients to the appropriate care setting before they showed up at the emergency department and clinics, which would otherwise consume resources, expose other patients and staff to potential viral transmission, and further exacerbate supply-and-demand mismatching. Although the use of AI has been well-established in other industries to optimize supply and demand matching, the introduction of AI to perform tasks remotely that were traditionally performed in-person by clinical staff represents a significant milestone in healthcare operations strategy.

Usage Patterns of a Web-Based Palliative Care Content Platform (PalliCOVID) During the COVID-19 Pandemic.

CONTEXT: The COVID-19 pandemic has highlighted the essential role of palliative care to support the delivery of compassionate, goal-concordant patient care. We created the Web-based application, PalliCOVID (https://pallicovid.app/), in April 2020 to provide all clinicians with convenient access to palliative care resources and support. PalliCOVID features evidence-based clinical guidelines, educational content, and institutional protocols related to palliative care for COVID-19 patients. It is a publicly available resource accessible from any mobile device or desktop computer that provides clinicians with access to palliative care guidance across a variety of care settings, including the emergency department, hospital ward, intensive care unit, and primary care practice. OBJECTIVE: The primary objective of this study was to evaluate usage patterns of PalliCOVID to understand user behavior in relation to this palliative care content platform during the period of the local peak of COVID-19 infection in Massachusetts. METHODS: We retrospectively analyzed deidentified usage data collected by Google Analytics from the first day of PalliCOVID's launch on April 7, 2020, until May 1, 2020, the time period that encompassed the local peak of the COVID-19 surge in Massachusetts. User access data were collected and summarized by using Google Analytics software that had been integrated into the PalliCOVID Web application. RESULTS: A total of 2042 users accessed PalliCOVID and viewed 4637 pages from April 7 to May 1, 2020. Users spent an average of 2 minutes and 6 seconds per session. Eighty-one percent of users were first-time visitors, while the remaining 19% were return visitors. Most users accessed PalliCOVID from the United States (87%), with a large proportion of users coming from Boston and the surrounding cities (32% of overall users). CONCLUSIONS: PalliCOVID is one example of a scalable digital health solution that can bring palliative care resources to frontline clinicians. Analysis of PalliCOVID usage patterns has the potential to inform the improvement of the platform to better meet the needs of its user base and guide future dissemination strategies. The quantitative data presented here, although informative about user behavior, should be supplemented with future qualitative research to further define the impact of this tool and extend our ability to deliver clinical care that is compassionate, rational, and well-aligned with patients' values and goals.