Bayesian Modeling Framework for Causal Inference and Assessing Sensitivity to Unmeasured Confounding with Multiple Treatments [Methods Study], United States, 2020-2022 (ICPSR 39721)
The research team based their new method on an existing method called Bayesian Additive Regression Trees, or BART. To test the new method, the team used data created by a computer program to look like real patient data. Then they compared the new method with current methods under different scenarios. Each scenario included three treatments. The team changed the total number of patients, the number of patients who took each treatment, and how alike or different the patients were who took each treatment. Across all scenarios, the team predicted the average treatment effect for all patients and for only patients who received a treatment.
Next, the research team used the new method with real data from patients with lung cancer who were receiving care in New York City hospitals. The team compared three types of surgery: open chest, robotic assisted, and video assisted. The team looked at the effects of each type of surgery on four health outcomes: breathing problems; length of hospital stay after surgery; stay in an intensive care unit, or ICU; and the need to return to the hospital.
Patients, doctors, and researchers helped design the study.
Best Practices to Reduce COVID-19 in Group Homes for Individuals with Serious Mental Illness and Intellectual and Developmental Disabilities, Massachusetts, 2021-2022 (ICPSR 39404)
The overall goal for this project was to reduce the incidence of COVID-19, hospitalization, and mortality among adults with serious mental illness (SMI) and intellectual disabilities/developmental disabilities (IDD) in congregate living settings (i.e., group homes) in Massachusetts, as well as to reduce COVID-19 incidence among staff who work in these settings. The research team was guided by two comparative effectiveness questions:
- With the goal of prioritizing and making actionable best practices available as resources, what is the comparative effectiveness of various types and intensities of preventative interventions (e.g., screening, isolation, contact tracing, hand hygiene, physical distancing, use of face masks) in reducing rates of COVID-19, related hospitalizations, and related mortality in this population?
- With the goal of effectively implementing best practices, what is the most effective implementation strategy to reduce rates of COVID-19 in this population: using tailored best practices (TBP) with SMI/IDD residents and staff of group homes in mind, or general best practices (GBP) from state and federal standard guidelines for all congregate care settings?
The specific aims of this study were as follows:
Aim 1a. Synthesize existing baseline data collected by 6 state behavioral health agencies on COVID-19 rates, hospitalization, mortality, and use of infection prevention practices.
Aim 1b. Collect stakeholder input via surveys and virtual focus groups on staff and resident experiences and on barriers/facilitators to implementing recommended preventative practices.
Aims 2a and 2b. Determine the comparative effectiveness of various COVID-19 preventative practices by (Aim 2a) using a validated simulation model to estimate COVID-19 spread in group homes and (Aim 2b) obtaining stakeholder input on prioritizing and defining tailored best practices for implementation.
Aim 3. Compare the effectiveness of TBPs with GBPs by using a hybrid effectiveness-implementation cluster randomized controlled trial.
Data collected to answer Aims 1 and 2 served as the foundation for designing the Aim 3 trial. Data for the trial were collected in 3-month intervals beginning January 2021 (baseline) until October 2022 (15-month follow-up). Residents and staff were sampled from approximately 400 group homes. Primary implementation outcome measures were COVID-19 vaccination rates and fidelity scores. The primary effectiveness outcome measure was COVID-19 infection.
Notes: This collection contains only data from Aim 1a and Aim 3. Throughout the data and documentation, "intellectual and/or developmental disabilities" is abbreviated as both IDD and ID/DD.
Comparative Effectiveness of Single-Site and Scattered-Site Permanent Supportive Housing on Patient-Centered and COVID-19-Related Outcomes for People Experiencing Homelessness, California, 2021-2023 (ICPSR 39155)
People experiencing homelessness (PEH) were among the most likely to contract the novel coronavirus disease 2019 (COVID-19). Many PEH utilized high-density public places to satisfy their basic needs (e.g., soup kitchens for sustenance, public libraries for restrooms). This made it difficult for them to limit close contact with others and put them at increased risk of contracting and transmitting COVID-19. Furthermore, it was difficult to follow recommended protective measures--such as handwashing and social distancing--when living in shelters or on the streets.
PEH were at higher risk of COVID-19 related hospitalization and death than the rest of the population. The poor living conditions of PEH accelerated aging, leading them to experience geriatric conditions and medical complications more typical of individuals 10-20 years older. They were also at increased risk of cardiovascular and respiratory disease, HIV/AIDS, and diabetes, all conditions that increase vulnerability to serious COVID-19-related complications and death. These risks were compounded by the fact that PEH also faced significant barriers to accessing quality health care. In the absence of protective action, it was estimated that more than 21,000 PEH would require hospitalization due to COVID-19, more than 7,000 would require critical care, and nearly 3,500 would die.
Consequently, the COVID-19 pandemic made housing and health care for PEH one of the top priorities for the U.S. health care and public health systems. State and local governments across the country used federal relief funds to allocate private hotel rooms as protective shelter for vulnerable PEH. In Los Angeles County (LAC), which contains the largest unsheltered homeless population in the nation, 2,400 PEH were placed in hotels. COVID-19 response plans included accommodating up to 15,000 PEH in hotels who would then be moved to permanent housing in 90 days. This rapid push into housing amid a pandemic necessitated a delicate balance between social distancing and maintaining patients' basic needs, continuity of existing care, and personal and social well-being.
Permanent supportive housing (PSH)--programs that provide immediate access to independent living situations coupled with support services--is the most effective approach for serving PEH. Numerous studies have demonstrated PSH's effectiveness in improving housing retention, quality of life, and HIV outcomes. Though evidence concerning its impact on other health outcomes, health behaviors, and health care utilization is limited, the National Academies of Sciences, Engineering, and Medicine has nonetheless recognized PSH as extremely beneficial for PEH's health. COVID-19 was what this organization termed a "housing-sensitive condition"--one whose transmissibility, course, and medical management are particularly influenced by homelessness. Consequently, the National Alliance to End Homelessness recommended the use of PSH as part of its framework to address COVID-19 and homelessness.
However, significant questions remain about what types of PSH programs can best address COVID-19-related risk and promote patient-centered outcomes at a time of social and community disruption. There are two distinct approaches to implementing PSH: place-based (PB) PSH, or single-site housing placement in a congregate residence with on-site services, and scattered-site (SS) PSH, which uses apartments rented from a private landlord to house clients while providing mobile case management services. The strengths and weaknesses of these two approaches remain largely unknown but may have direct implications for adherence to COVID-19 prevention protocols and other health-related outcomes.
Comparing Patient-reported Impact of COVID-19 Shelter-in-place Policies and Access to Containment and Mitigation Strategies Overall and in Vulnerable Populations, United States, 2020-2022 (ICPSR 39218)
The COVID-19 Citizen Science (CCS) Study was launched early in the pandemic to collect patient-reported information about exposures, risk behaviors and outcomes relevant to the pandemic. The Patient-Centered Outcomes Research Institute (PCORI) funded the research team to expand recruitment into CCS using PCORnet, the National Patient-Centered Clinical Research Network, and to use the resulting data to compare the patient-reported impact of pandemic associated policies. The research team systematically collected pandemic-associated policies enacted by counties across the United States (focusing in areas where there were many CCS participants), and to do so on a weekly basis from the beginning of the pandemic using publicly available sources.
Researchers combined data from various sources to answer two primary research questions (RQ):
- What is the comparative impact of different shelter-in-place/reopening policies, overall and in vulnerable populations, on patient-reported financial insecurity, mental health, and other subjective outcomes important to patients?
- What is the comparative effectiveness of county-level containment and mitigation strategies at achieving timely access to COVID-19 vaccination, testing, healthcare, information and contact tracing?
The research team collected patient-reported data from the CCS study and policy data from the U.S COVID-19 County Policy (UCCP) database. Electronic health record (EHR) data were also available from some participants recruited from health systems located across 7 U.S. states who consented and authorized use of these data for the study. Data for these participants were extracted from the PCORnet Common Data Model (CDM). Additional county-level contextual variables were included in analysis.
This collection contains CCS survey data on patient-reported anxiety with county-level policies data (DS1), respondent demographics (DS2), baseline survey results (DS3), daily (DS4) and weekly (DS5) COVID-19 symptoms reports, COVID-19 vaccination surveys repeated monthly (DS6) as well as a one-time vaccination survey (DS7), and pandemic impacts check-in surveys (DS8). CDM datasets include logistic regression model outcomes to predict study enrollment among all invited participants (DS9), codes for immunizations (DS10), laboratory tests (DS11), and procedures (DS12). County-level variables are also available for years 2021 (DS13) and 2023 (DS14).
Comparing Ways to Monitor Patients with COVID-19 at Home (COVID Watch), New Jersey, Pennsylvania, Delaware, 2020-2021 (ICPSR 38951)
The University of Pennsylvania Health System (Penn Medicine) developed COVID Watch, an automated text message-based, remote monitoring program with 24/7 clinical support. Remote outpatient monitoring of patients with COVID-19 became needed because patients with SARS-CoV-2 infection can decline rapidly and unpredictably, and because of their own limited capacity to manage acute symptoms and concerns about staff safety, office-based outpatient practices often redirect patients with confirmed or suspected COVID-19 to hospitals. As a result, emergency departments (EDs) and hospitals became overwhelmed during surge periods of high community incidence rates and prevalence. Remote monitoring has the potential to facilitate ED- and hospital-level care for patients who require it while supporting access to care for patients who can safely remain at home.
This study compared outcomes for patients enrolled in COVID Watch with those of patients who were eligible to enroll but received usual care, with the hypothesis that enrollment in COVID Watch was associated with reduced mortality. The present research examined whether patients with COVID-19 who were enrolled in COVID Watch experienced better health outcomes compared with usual care (Aim 1) and whether augmenting COVID Watch with at-home monitoring of SpO2 (blood-oxygen saturation) improves patient outcomes (Aim 2).
COVID-19 Project ECHO for Nursing Homes: A Patient-centered, Randomized-controlled Trial to Implement Infection Control, United States, 2021 (ICPSR 38769)
Healthcare Worker Exposure Response and Outcomes of Hydroxychloroquine Trial (HERO-HCQ Trial), United States, 2020-2021 (ICPSR 38819)
Severe acute respiratory syndrome coronavirus 2 associated disease (COVID-19) is caused by a novel betacoronavirus, SARS-CoV-2, that was first isolated in January 2020 and has since caused a global pandemic unseen in decades in cases and mortality. At the time of initial protocol submission in April 2020, human vaccine clinical trials had just begun and experts predicted that a vaccine would not be available until April 2021 at the earliest. Therefore, new measures remained needed to prevent the spread of disease. In vitro studies suggested a potential moderate antiviral effect of hydroxychloroquine (HCQ).
This study aimed to evaluate the efficacy of HCQ to prevent COVID-19 clinical infection and to prevent viral shedding of SARS-CoV-2 among healthcare workers (HCWs), as well as to evaluate the safety and tolerability of HCQ. Participants prescreened through the Healthcare Exposure Response and Outcomes (HERO) Registry across 34 U.S. clinical centers were randomly assigned to take a placebo (n=676) or HCQ (n=683) for 30 days, with in-person clinic visits at baseline and 30 days, and an end-of-study virtual visit at 60 days. This collection contains analysis (DS1 through DS6) and tabulation (DS7 through DS44) data and accompanying documentation.
HERO Registry: Creating and Using a Community Registry to Understand the Experiences of Healthcare Workers and Their Communities during COVID-19, United States, 2020-2022 (ICPSR 39153)
To study the impact of COVID-19 pandemic on frontline healthcare workers in the United States over time, the Healthcare Worker Exposure Response and Outcomes (HERO) Registry was created in 2020 to form a virtual research community of healthcare workers (and later, their family members and community members). The registry was intended for healthcare workers interested in completing research studies related to the COVID-19 pandemic and its impacts on their lives. Observational data were collected at various timepoints between April 2020 and September 2022 via web-based questionnaires available on the HERO Registry online portal.
This collection contains 39 sets of data from over 50,000 HERO Registry members. Datasets represent separate surveys with distinct survey designs and sampling criteria. Surveys focused on health history, workplace experiences, COVID-19 exposure, social support, mental health, and the respondents' willingness to remain in or leave the healthcare field. Datasets 24 through 39 represent "hot topics" such as vaccines, vaccine willingness and uptake, childcare and school arrangements, and staffing shortages. Datasets for registry administration, respondent demographics, and survey eligibility criteria are also included.