Reporting and Availability of COVID-19 Demographic Data by US Health Departments (April to October 2020): Observational Study

Medical School Curriculum Relating to Clinical Ethical Decision Making During a Pandemic: A Scoping Review

Background

The COVID-19 pandemic has demonstrated the need for medical students to be prepared to make adequate decisions during unique challenges presented during pandemics.

Objective

This review aims to provide a comprehensive look into the current global literature that discusses medical curricula on clinical ethical issues during a pandemic.

Methods

The scoping review methodology was divided into three stages. Phase 1, planning, involved identifying key terms, selecting databases, creating a search criterion, and deciding on inclusion and exclusion criteria. Phase 2, study selection and data extraction, included screening the title and abstract, reviewing the complete text, and extracting data. Phase 3, analysis and write-up, comprised analyzing the extracted information and composing the review.

Results

10 studies were included and underwent data extraction as part of the review. The studies varied by country, study design, institution, education setting, and course titles. Ethical issues identified while reviewing the curriculums were resource allocation, healthcare worker obligations, personal protective equipment, disease control, communication, management protocols, and patient care.

Conclusion

This review revealed a lack of literature regarding the curriculum for medical students on ethical issues during a pandemic. This indicates a need for reform in medical education to cover pandemic preparedness and ethical concerns during a pandemic. If medical schools do not address this gap, future physicians may encounter the same issues healthcare workers faced during the COVID-19 pandemic.

Evaluating Demographic Representation in Clinical Trials: Use of the Adaptive Coronavirus Disease 2019 Treatment Trial (ACTT) as a Test Case

Background

Clinical trials initiated during emerging infectious disease outbreaks must quickly enroll participants to identify treatments to reduce morbidity and mortality. This may be at odds with enrolling a representative study population, especially when the population affected is undefined.

Methods

We evaluated the utility of the Centers for Disease Control and Prevention's COVID-19-Associated Hospitalization Surveillance Network (COVID-NET), the COVID-19 Case Surveillance System (CCSS), and 2020 United States (US) Census data to determine demographic representation in the 4 stages of the Adaptive COVID-19 Treatment Trial (ACTT). We compared the cumulative proportion of participants by sex, race, ethnicity, and age enrolled at US ACTT sites, with respective 95% confidence intervals, to the reference data in forest plots.

Results

US ACTT sites enrolled 3509 adults hospitalized with COVID-19. When compared with COVID-NET, ACTT enrolled a similar or higher proportion of Hispanic/Latino and White participants depending on the stage, and a similar proportion of African American participants in all stages. In contrast, ACTT enrolled a higher proportion of these groups when compared with US Census and CCSS. The proportion of participants aged ≥65 years was either similar or lower than COVID-NET and higher than CCSS and the US Census. The proportion of females enrolled in ACTT was lower than the proportion of females in the reference datasets.

Conclusions

Although surveillance data of hospitalized cases may not be available early in an outbreak, they are a better comparator than US Census data and surveillance of all cases, which may not reflect the population affected and at higher risk of severe disease.

Data Collection during Public Health Emergencies: Design Tenets and Usability of an Electronic Data Capture Tool (Preprint)

Background

The Discovery Critical Care Research Network Program for Resilience and Emergency Preparedness (Discovery PREP) partnered with a third-party technology vendor to design and implement an electronic data capture tool that addressed multisite data collection challenges during public health emergencies (PHE) in the United States. The basis of the work was to design an electronic data capture tool and to prospectively gather data on usability from bedside clinicians during national health system stress queries and influenza observational studies.

Objective

The aim of this paper is to describe the lessons learned in the design and implementation of a novel electronic data capture tool with the goal of significantly increasing the nation’s capability to manage real-time data collection and analysis during PHE.

Methods

A multiyear and multiphase design approach was taken to create an electronic data capture tool, which was used to pilot rapid data capture during a simulated PHE. Following the pilot, the study team retrospectively assessed the feasibility of automating the data captured by the electronic data capture tool directly from the electronic health record. In addition to user feedback during semistructured interviews, the System Usability Scale (SUS) questionnaire was used as a basis to evaluate the usability and performance of the electronic data capture tool.

Results

Participants included Discovery PREP physicians, their local administrators, and data collectors from tertiary-level academic medical centers at 5 different institutions. User feedback indicated that the designed system had an intuitive user interface and could be used to automate study communication tasks making for more efficient management of multisite studies. SUS questionnaire results classified the system as highly usable (SUS score 82.5/100). Automation of 17 (61%) of the 28 variables in the influenza observational study was deemed feasible during the exploration of automated versus manual data abstraction. The creation and use of the Project Meridian electronic data capture tool identified 6 key design requirements for multisite data collection, including the need for the following: (1) scalability irrespective of the type of participant; (2) a common data set across sites; (3) automated back end administrative capability (eg, reminders and a self-service status board); (4) multimedia communication pathways (eg, email and SMS text messaging); (5) interoperability and integration with local site information technology infrastructure; and (6) natural language processing to extract nondiscrete data elements.

Conclusions

The use of the electronic data capture tool in multiple multisite Discovery PREP clinical studies proved the feasibility of using the novel, cloud-based platform in practice. The lessons learned from this effort can be used to inform the improvement of ongoing global multisite data collection efforts during the COVID-19 pandemic and transform current manual data abstraction approaches into reliable, real time, and automated information exchange. Future research is needed to expand the ability to perform automated multisite data extraction during a PHE and beyond.