Insights from a Rapidly Implemented COVID-19 Biobank Using Electronic Consent and Informatics Tools.

Biobanking during the COVID-19 pandemic presented unique challenges regarding patient enrollment, sample collection, and experimental analysis. This report details the ways in which we rapidly overcame those challenges to create a robust database of clinical information and patient samples while maintaining clinician and researcher safety. We developed a pipeline using REDCap (Research Electronic Data Capture) to coordinate electronic informed consent, sample collection, immunological assay execution, and data analysis for biobanking samples from patients with COVID-19. We then integrated immunological assay data with clinical data extracted from the electronic health record to link study parameters with clinical readouts. Of the 193 inpatients who participated in this study, 138 consented electronically and 56 provided paper consent. We collected and banked blood samples to measure circulating cytokines and chemokines, peripheral immune cell composition and activation status, anti-COVID-19 antibodies, and germline gene polymorphisms. In addition, we collected DNA and RNA from nasopharyngeal swabs to assess viral titer and microbiome composition by 16S sequencing. The rapid spread and contagious nature of COVID-19 required special considerations and innovative solutions to biobank samples quickly while protecting researchers and clinicians. Overall, this workflow and computational pipeline allowed for comprehensive immune profiling of 193 inpatients infected with COVID-19, as well as 89 outpatients, 157 patients receiving curbside COVID-19 testing, and 86 healthy controls. We describe a novel electronic framework for biobanking and analyzing patient samples during COVID-19, and present insights and strategies that can be applied more broadly to other biobank studies.

Analysis of COVID-19 Pandemic on Supplement Usage and Its Combination with Self-Medication within the State of Arkansas.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel coronavirus responsible for the COVID-19 pandemic that can lead to severe respiratory distress requiring hospitalization and can be fatal. Media have reported that various dietary supplements (DS) or their combination with different medications can prevent infection or decrease disease severity. Here, we analyzed data collected from 15,830 patient follow-up telephone interviews from the University of Arkansas for Medical Sciences COVID-19 testing sites from March 15 to August 1, 2020. Within the REDCap database, we recorded patient demographics and DS and medication use. In total, data on DS and medication use was available for 8,150 study participants, of whom 21.9% and 4.1% reported using DS or medications, respectively, to either prevent or treat COVID-19. The majority of respondents were female (64%) and non-Hispanic whites (44.5%). Most individuals (64.5%) who took DS were younger than 50 years of age. Products such as vitamin C (1,013, 33.2%), multivitamins (722, 23.6%), and vitamin D (294, 9.6%) were the most commonly used DS among the responders. Analysis of the DS use and symptom scores association did not provide a strong evidence of beneficial health effects of DS. The results of this study demonstrate that a significantly higher proportion of study participants considered usage of DS to mitigate or prevent COVID-19-related symptoms compared to those who preferred medications. However, lack of observable health benefits associated with ingestion of DS suggests that more rigorous research is needed to substantiate the label claims.

Developing and testing a Corona VaccinE tRiAL pLatform (COVERALL) to study Covid-19 vaccine response in immunocompromised patients.

BACKGROUND: The rapid course of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic calls for fast implementation of clinical trials to assess the effects of new treatment and prophylactic interventions. Building trial platforms embedded in existing data infrastructures is an ideal way to address such questions within well-defined subpopulations. METHODS: We developed a trial platform building on the infrastructure of two established national cohort studies: the Swiss human immunodeficiency virus (HIV) Cohort Study (SHCS) and Swiss Transplant Cohort Study (STCS). In a pilot trial, termed Corona VaccinE tRiAL pLatform (COVERALL), we assessed the vaccine efficacy of the first two licensed SARS-CoV-2 vaccines in Switzerland and the functionality of the trial platform. RESULTS: Using Research Electronic Data Capture (REDCap), we developed a trial platform integrating the infrastructure of the SHCS and STCS. An algorithm identifying eligible patients, as well as baseline data transfer ensured a fast inclusion procedure for eligible patients. We implemented convenient re-directions between the different data entry systems to ensure intuitive data entry for the participating study personnel. The trial platform, including a randomization algorithm ensuring balance among different subgroups, was continuously adapted to changing guidelines concerning vaccination policies. We were able to randomize and vaccinate the first trial participant the same day we received ethics approval. Time to enroll and randomize our target sample size of 380 patients was 22 days. CONCLUSION: Taking the best of each system, we were able to flag eligible patients, transfer patient information automatically, randomize and enroll the patients in an easy workflow, decreasing the administrative burden usually associated with a trial of this size.

Post-9/11 veterans perceptions of the pandemic: Areas of greatest impact on health and well-being.

Objective: Assess potential impacts of the COVID-19 pandemic on a subset of Post-9/11 U.S. Veterans included in a study of post-traumatic epilepsy (PTE). Methods: Two measures were added to a structured health interview for Veterans during temporary pandemic research shutdown: a validated health questionnaire [1] previously completed by survey, and a semi-structured instrument developed to assess whether pandemic conditions affected responses to the health questionnaire and identify unique impacts. Interviews were conducted between August 2020 - February 2021. Scaled items were calculated and t-tests used to compare results. Open-ended items were coded using thematic analyses. Results: Veterans identified eight major areas of impact with negative and positive impacts: mental health, family, social, work/employment, access to resources, physical health, finances, and education. Innovation: The temporary shut-down of a large health study for Post-9/11 Veterans provided an opportunity to devise an instrument to assess COVID-19's impact on health and well-being. The instrument was accepted as of the first Veteran instrument in a pandemic SDOH research repository [2], and is being used in other studies. Conclusion: This study highlights the need to assess and understand interrelated relationships of factors impacting health and well-being, especially as COVID-19 moves from pandemic to endemic with reverberating effects across multiple social determinants of health (SDOH).

Latent class analysis: an innovative approach for identification of clinical and laboratory markers of disease severity among COVID-19 patients admitted to the intensive care unit.

Objective: The aim of this study was to identify clinical and laboratory phenotype distribution patterns and their usefulness as prognostic markers in COVID-19 patients admitted to the intensive care unit (ICU) at Tygerberg Hospital, Cape Town. Methods and results: A latent class analysis (LCA) model was applied in a prospective, observational cohort study. Data from 343 COVID-19 patients were analysed. Two distinct phenotypes (1 and 2) were identified, comprising 68.46% and 31.54% of patients, respectively. The phenotype 2 patients were characterized by increased coagulopathy markers (D-dimer, median value 1.73 ng/L vs 0.94 ng/L; p < 0.001), end-organ dysfunction (creatinine, median value 79 µmol/L vs 69.5 µmol/L; p < 0.003), under-perfusion markers (lactate, median value 1.60 mmol/L vs 1.20 mmol/L; p < 0.001), abnormal cardiac function markers (median N-terminal pro-brain natriuretic peptide (NT-proBNP) 314 pg/ml vs 63.5 pg/ml; p < 0.001 and median high-sensitivity cardiac troponin (Hs-TropT) 39 ng/L vs 12 ng/L; p < 0.001), and acute inflammatory syndrome (median neutrophil-to-lymphocyte ratio 15.08 vs 8.68; p < 0.001 and median monocyte value 0.68 × 109/L vs 0.45 × 109/L; p < 0.001). Conclusion: The identification of COVID-19 phenotypes and sub-phenotypes in ICU patients could help as a prognostic marker in the day-to-day management of COVID-19 patients admitted to the ICU.

In-hospital mortality and severe outcomes after hospital discharge due to COVID-19: A prospective multicenter study from Brazil.

Background: We evaluated in-hospital mortality and outcomes incidence after hospital discharge due to COVID-19 in a Brazilian multicenter cohort. Methods: This prospective multicenter study (RECOVER-SUS, NCT04807699) included COVID-19 patients hospitalized in public tertiary hospitals in Brazil from June 2020 to March 2021. Clinical assessment and blood samples were performed at hospital admission, with post-hospital discharge remote visits. Hospitalized participants were followed-up until March 31, 2021. The outcomes were in-hospital mortality and incidence of rehospitalization or death after hospital discharge. Kaplan-Meier curves and Cox proportional-hazard models were performed. Findings: 1589 participants [54.5% male, age=62 (IQR 50-70) years; BMI=28.4 (IQR,24.9-32.9) Kg/m² and 51.9% with diabetes] were included. A total of 429 individuals [27.0% (95%CI,24.8-29.2)] died during hospitalization (median time 14 (IQR,9-24) days). Older age [vs<40 years; age=60-69 years-aHR=1.89 (95%CI,1.08-3.32); age=70-79 years-aHR=2.52 (95%CI,1.42-4.45); age≥80-aHR=2.90 (95%CI 1.54-5.47)]; noninvasive or mechanical ventilation at admission [vs facial-mask or none; aHR=1.69 (95%CI 1.30-2.19)]; SAPS-III score≥57 [vs<57; aHR=1.47 (95%CI 1.13-1.92)] and SOFA score≥10 [vs <10; aHR=1.51 (95%CI 1.08-2.10)] were independently associated with in-hospital mortality. A total of 65 individuals [6.7% (95%CI 5.3-8.4)] had a rehospitalization or death [rate=323 (95%CI 250-417) per 1000 person-years] in a median time of 52 (range 1-280) days post-hospital discharge. Age ≥ 60 years [vs <60, aHR=2.13 (95%CI 1.15-3.94)] and SAPS-III ≥57 at admission [vs <57, aHR=2.37 (95%CI 1.22-4.59)] were independently associated with rehospitalization or death after hospital discharge. Interpretation: High in-hospital mortality rates due to COVID-19 were observed and elderly people remained at high risk of rehospitalization and death after hospital discharge. Funding: Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and Programa INOVA-FIOCRUZ.

REDCap Delivery of a Web-Based Intervention for Patients With Voice Disorders: Usability Study.

BACKGROUND: Web-based health interventions are increasingly common and are promising for patients with voice disorders because web-based participation does not require voice use. To address needs such as Health Insurance Portability and Accountability Act compliance, unique user access, the ability to send automated reminders, and a limited development budget, we used the Research Electronic Data Capture (REDCap) data management platform to deliver a patient-facing psychological intervention designed for patients with voice disorders. This was a novel use of REDCap. OBJECTIVE: We aimed to evaluate the usability of the intervention, with this intervention serving as a use case for REDCap-based patient-facing interventions. METHODS: We used REDCap survey instruments to develop the web-based voice intervention modules, then conducted usability evaluations using (1) heuristic evaluations by 2 evaluators, and (2) formal usability testing with 7 participants, consisting of predetermined tasks, a think-aloud protocol, ease-of-use measurements, a product reaction card, and a debriefing interview. RESULTS: Heuristic evaluations found strengths in visibility of system status and real-world match, and weaknesses in user control and help documentation. Based on this feedback, changes to the intervention were made before usability testing. Overall, usability testing participants found the intervention useful and easy to use, although testing revealed some concerns with design, content, and terminology. Some concerns were readily addressed, and others required adaptations within REDCap. CONCLUSIONS: The REDCap version of a complex web-based patient-facing intervention performed well in heuristic evaluation and formal usability testing. REDCap can effectively be used for patient-facing intervention delivery, particularly if the limitations of the platform are anticipated and mitigated.

Efficacy of Digital Health Tools for a Pediatric Patient Registry: Semistructured Interviews and Interface Usability Testing With Parents and Clinicians.

BACKGROUND: Acute respiratory infection (ARI) in childhood is common, but more knowledge on the burden and natural history of ARI in the community is required. A better understanding of ARI risk factors, treatment, and outcomes will help support parents to manage their sick child at home. Digital health tools are becoming more widely adopted in clinical care and research and may assist in understanding and managing common pediatric diseases, including ARI, in hospitals and in the community. We integrated 2 digital tools-a web-based discharge communication system and the REDCap (Research Electronic Data Capture) platform-into the Pragmatic Adaptive Trial for Acute Respiratory Infection in Children to enhance parent and physician engagement around ARI discharge communication and our patient registry. OBJECTIVE: The objective of this study is to determine the efficacy and usability of digital tools integrated into a pediatric patient registry for ARI. METHODS: Semistructured interviews and software interface usability testing were conducted with 11 parents and 8 emergency department physicians working at a tertiary pediatric hospital and research center in Perth, Western Australia, in 2019. Questions focused on experiences of discharge communication and clinical trial engagement. Responses were analyzed using the qualitative Framework Method. Participants were directly observed using digital interfaces as they attempted predetermined tasks that were then classified as success, failure, software failure, or not observed. Participants rated the interfaces using the System Usability Scale (SUS). RESULTS: Most parents (9/11, 82%) indicated that they usually received verbal discharge advice, with some (5/11, 45%) recalling receiving preprinted resources from their physician. Most (8/11, 73%) would also like to receive discharge advice electronically. Most of the physicians (7/8, 88%) described their usual practice as verbal discharge instructions, with some (3/8, 38%) reporting time pressures associated with providing discharge instructions. The digital technology option was preferred for engaging in research by most parents (8/11, 73%). For the discharge communication digital tool, parents gave a mean SUS score of 94/100 (SD 4.3; A grade) for the mobile interface and physicians gave a mean usability score of 93/100 (SD 4.7; A grade) for the desktop interface. For the research data management tool (REDCap), parents gave a mean usability score of 78/100 (SD 11.0; C grade) for the mobile interface. CONCLUSIONS: Semistructured interviews allowed us to better understand parent and physician experiences of discharge communication and clinical research engagement. Software interface usability testing methods and use of the SUS helped us gauge the efficacy of our digital tools with both parent and physician users. This study demonstrates the feasibility of combining qualitative research methods with software industry interface usability testing methods to help determine the efficacy of digital tools in a pediatric clinical research setting.

Use of research electronic data capture (REDCap) in a COVID-19 randomized controlled trial: a practical example.

BACKGROUND: Randomized controlled trials (RCT) are considered the ideal design for evaluating the efficacy of interventions. However, conducting a successful RCT has technological and logistical challenges. Defects in randomization processes (e.g., allocation sequence concealment) and flawed masking could bias an RCT's findings. Moreover, investigators need to address other logistics common to all study designs, such as study invitations, eligibility screening, consenting procedure, and data confidentiality protocols. Research Electronic Data Capture (REDCap) is a secure, browser-based web application widely used by researchers for survey data collection. REDCap offers unique features that can be used to conduct rigorous RCTs. METHODS: In September and November 2020, we conducted a parallel group RCT among Indiana University Bloomington (IUB) undergraduate students to understand if receiving the results of a SARS-CoV-2 antibody test changed the students' self-reported protective behavior against coronavirus disease 2019 (COVID-19). In the current report, we discuss how we used REDCap to conduct the different components of this RCT. We further share our REDCap project XML file and instructional videos that investigators can use when designing and conducting their RCTs. RESULTS: We reported on the different features that REDCap offers to complete various parts of a large RCT, including sending study invitations and recruitment, eligibility screening, consenting procedures, lab visit appointment and reminders, data collection and confidentiality, randomization, blinding of treatment arm assignment, returning test results, and follow-up surveys. CONCLUSIONS: REDCap offers powerful tools for longitudinal data collection and conduct of rigorous and successful RCTs. Investigators can make use of this electronic data capturing system to successfully complete their RCTs. TRIAL REGISTRATION: The RCT was prospectively (before completing data collection) registered at ClinicalTrials.gov; registration number: NCT04620798 , date of registration: November 9, 2020.

A REDCap-based model for online interventional research: Parent sleep education in autism.

INTRODUCTION: The use of online platforms for pediatric healthcare research is timely, given the current pandemic. These platforms facilitate trial efficiency integration including electronic consent, randomization, collection of patient/family survey data, delivery of an intervention, and basic data analysis. METHODS: We created an online digital platform for a multicenter study that delivered an intervention for sleep disorders to parents of children with autism spectrum disorder (ASD). An advisory parent group provided input. Participants were randomized to receive either a sleep education pamphlet only or the sleep education pamphlet plus three quick-tips sheets and two videos that reinforced the material in the pamphlet (multimedia materials). Three measures - Family Inventory of Sleep Habits (FISH), Children's Sleep Habits Questionnaire modified for ASD (CSHQ-ASD), and Parenting Sense of Competence (PSOC) - were completed before and after 12 weeks of sleep education. RESULTS: Enrollment exceeded recruitment goals. Trial efficiency was improved, especially in data entry and automatic notification of participants related to survey completion. Most families commented favorably on the study. While study measures did not improve with treatment in either group (pamphlet or multimedia materials), parents reporting an improvement of ≥3 points in the FISH score showed a significantly improved change in the total CSHQ (P = 0.038). CONCLUSION: Our study demonstrates the feasibility of using online research delivery platforms to support studies in ASD, and more broadly, pediatric clinical and translational research. Online platforms may increase participant inclusion in enrollment and increase convenience and safety for participants and study personnel.

Imaging Quality Control, Methodology Harmonization and Clinical Data Management in Stress Echo 2030.

Stress echo (SE) 2030 study is an international, prospective, multicenter cohort study that will include >10,000 patients from ≥20 centers from ≥10 countries. It represents the logical and chronological continuation of the SE 2020 study, which developed, validated, and disseminated the "ABCDE protocol" of SE, more suitable than conventional SE to describe the complex vulnerabilities of the contemporary patient within and beyond coronary artery disease. SE2030 was started with a recruitment plan from 2021 to 2025 (and follow-up to 2030) with 12 subprojects (ranging from coronary artery disease to valvular and post-COVID-19 patients). With these features, the study poses particular challenges on quality control assurance, methodological harmonization, and data management. One of the significant upgrades of SE2030 compared to SE2020 was developing and implementing a Research Electronic Data Capture (REDCap)-based infrastructure for interactive and entirely web-based data management to integrate and optimize reproducible clinical research data. The purposes of our paper were: first, to describe the methodology used for quality control of imaging data, and second, to present the informatic infrastructure developed on RedCap platform for data entry, storage, and management in a large-scale multicenter study.

Use of EHRs in a Tertiary Hospital During COVID-19 Pandemic: A Multi-Purpose Approach Based on Standards.

This work aims to describe how EHRs have been used to meet the needs of healthcare providers and researchers in a 1,300-beds tertiary Hospital during COVID-19 pandemic. For this purpose, essential clinical concepts were identified and standardized with LOINC and SNOMED CT. After that, these concepts were implemented in EHR systems and based on them, data tools, such as clinical alerts, dynamic patient lists and a clinical follow-up dashboard, were developed for healthcare support. In addition, these data were incorporated into standardized repositories and COVID-19 databases to improve clinical research on this new disease. In conclusion, standardized EHRs allowed implementation of useful multi- purpose data resources in a major Hospital in the course of the pandemic.

Dermatology residency research policies: A 2021 national survey.

BACKGROUND: In this follow-up study to previous work, the authors survey the availability of key measures and resources pertaining to residency research in U.S. Accreditation Council for Graduate Medical Education-accredited dermatology residency programs, including potential policy changes following the COVID-19 pandemic. OBJECTIVE: The chief objective of this survey was to evaluate and compare dermatology programs' resident research requirements and guidelines. METHODS: This cross-sectional study employed a 13-item survey administered online in early 2021 to assess the degree to which dermatology residency programs require and support their new physician graduates in scholarly research endeavors. RESULTS: A total of 32 program directors representing 30 dermatology residency programs (30 of 138 accredited programs contacted [22%]) responded to the survey. Almost all programs described quality improvement project requirements for residents and were able to provide funding for resident conference participation. Most programs also reported resident publication requirements and the availability of research electives. However, the vast majority did not have required research rotations or a formal mentorship program. The COVID-19 pandemic did not have a substantial impact on residency research requirements. CONCLUSION: Our survey provides objective data about the current dermatology resident research requirements across the United States. These findings may prove valuable to prospective applicants, residency programs, and accrediting agencies in improving, advancing, and structuring dermatology residency guidelines and resources with the aim of encouraging new physician trainees to pursue research.

Creating and implementing a COVID-19 recruitment Data Mart.

The COVID-19 pandemic has resulted in an unprecedented strain on every aspect of the healthcare system, and clinical research is no exception. Researchers are working against the clock to ramp up research studies addressing every angle of COVID-19 - gaining a better understanding of person-to-person transmission, improving methods for diagnosis, and developing therapies to treat infection and vaccines to prevent it. The impact of the virus on research efforts is not limited to investigators and their teams. Potential participants also face unparalleled opportunities and requests to participate in research, which can result in a significant amount of participant fatigue. The Vanderbilt Institute for Clinical and Translational Research recognized early in the pandemic that a solution to assist researchers in the rapid identification of potential participants was critical, and thus developed the COVID-19 Recruitment Data Mart. This solution does not rest solely on technology; the addition of experienced project managers to support researchers and facilitate collaboration was essential. Since the platform and study support tools were launched on July 20, 2020, four studies have been onboarded and a total of 1693 potential participant matches have been shared. Each of these patients had agreed in advance to direct contact for COVID-19 research and had been matched to study-specific inclusion/exclusion criteria. Our innovative Data Mart system is scalable and looks promising as a generalizable solution for simultaneously recommending individuals from a pool of patients against a pool of time-sensitive trial opportunities.

Improvements in Patient Monitoring in the Intensive Care Unit: Survey Study.

BACKGROUND: Due to demographic change and, more recently, coronavirus disease (COVID-19), the importance of modern intensive care units (ICU) is becoming apparent. One of the key components of an ICU is the continuous monitoring of patients' vital parameters. However, existing advances in informatics, signal processing, or engineering that could alleviate the burden on ICUs have not yet been applied. This could be due to the lack of user involvement in research and development. OBJECTIVE: This study focused on the satisfaction of ICU staff with current patient monitoring and their suggestions for future improvements. We aimed to identify aspects of monitoring that interrupt patient care, display devices for remote monitoring, use cases for artificial intelligence (AI), and whether ICU staff members are willing to improve their digital literacy or contribute to the improvement of patient monitoring. We further aimed to identify differences in the responses of different professional groups. METHODS: This survey study was performed with ICU staff from 4 ICUs of a German university hospital between November 2019 and January 2020. We developed a web-based 36-item survey questionnaire, by analyzing a preceding qualitative interview study with ICU staff, about the clinical requirements of future patient monitoring. Statistical analyses of questionnaire results included median values with their bootstrapped 95% confidence intervals, and chi-square tests to compare the distributions of item responses of the professional groups. RESULTS: In total, 86 of the 270 ICU physicians and nurses completed the survey questionnaire. The majority stated they felt confident using the patient monitoring equipment, but that high rates of false-positive alarms and the many sensor cables interrupted patient care. Regarding future improvements, respondents asked for wireless sensors, a reduction in the number of false-positive alarms, and hospital standard operating procedures for alarm management. Responses to the display devices proposed for remote patient monitoring were divided. Most respondents indicated it would be useful for earlier alerting or when they were responsible for multiple wards. AI for ICUs would be useful for early detection of complications and an increased risk of mortality; in addition, the AI could propose guidelines for therapy and diagnostics. Transparency, interoperability, usability, and staff training were essential to promote the use of AI. The majority wanted to learn more about new technologies for the ICU and required more time for learning. Physicians had fewer reservations than nurses about AI-based intelligent alarm management and using mobile phones for remote monitoring. CONCLUSIONS: This survey study of ICU staff revealed key improvements for patient monitoring in intensive care medicine. Hospital providers and medical device manufacturers should focus on reducing false alarms, implementing hospital alarm standard operating procedures, introducing wireless sensors, preparing for the use of AI, and enhancing the digital literacy of ICU staff. Our results may contribute to the user-centered transfer of digital technologies into practice to alleviate challenges in intensive care medicine. TRIAL REGISTRATION: ClinicalTrials.gov NCT03514173; https://clinicaltrials.gov/ct2/show/NCT03514173.