SUBSCRIBE TO OUR BLOG
Stay up to date with the latest from Datavant.
In the early days of the pandemic, Datavant recognized a pressing need for national insight about COVID-19. In collaboration with partners including Change Healthcare, the Health Care Cost Institute, Healthjump, Medidata, Mirador Analytics, Office Ally, PointClickCare, SAS, StataCorp, Snowflake, and Veradigm, we formed the COVID-19 Research Database (CRDB) with a clear goal: provide as much real-world data as possible to academic and medical researchers for free.
The CRDB provides a longitudinal, connected dataset that contains more than 300 million unique patients. Researcher access is managed by a Scientific Steering Committee which is chaired by Dr. Mark Cullen, formerly of Stanford University. In just under two years since the CRDB’s inception, more than 600 researchers have used the database to study the pandemic’s impact and the effectiveness of our response. They have produced more than 50 publications, which have helped inform pandemic health policy.
Last summer, The CRDB was recognized by the Bill & Melinda Gates Foundation, through a grant of one million dollars to support researchers studying the role of gender in the pandemic. In December 2021, the CRDB was recognized by the Reagan-Udall Foundation for the FDA, who named the Database a recipient of a 2021 Innovations in Regulatory Science Award, recognizing the Database’s novel framework as a blueprint for collaboration to accelerate breakthrough research. In this post, we are spotlighting five publications that affected key aspects of health policy that focus on answering the following questions:
- How are policies related to school, workplace, or business closures, impacting patients, families, teachers, and employers?
- How is COVID-19 impacting care-seeking behaviors such as mental health or preventative care visits?
- What barriers to patient care stand in the way of effective public health guidance?
- How can we support patients with comorbid conditions who are at increased risk of mortality?
- Where are we seeing disparate outcomes due to COVID-19? How do we evolve our healthcare system to better address those inequities?
School policy has been fraught with controversy as we formed our COVID response strategy. Remote learning has been a hallmark of the pandemic. Though research has shown that school closures have led to significant slowdowns in educational progress, many believed this was a necessary price to pay to avoid infection spread and high rates of hospitalization. The trouble was, officials lacked data to effectively evaluate the increases in infection and hospitalization rates associated with in-person schooling.
In January 2021, researchers from Tulane University sought to measure COVID-19 hospitalizations associated with school reopenings. Using claims data available in the CRDB, the team combined COVID-19 hospitalization events with nearly all U.S. school districts’ reopening plans. They found no evidence that reopening schools in-person or in a hybrid form in fall 2020 had increased COVID-19 hospitalizations across counties. The team’s conclusions dominated the national conversation, cited by sources including The World Bank, NPR, and U.S. News. In the midst of an uncertain winter case surge, the study provided an evidence base for school policy and enabled school administrators to make the right decisions for their district.
In January 2021, Massachusetts was among the first to adopt an evidence-based approach to answering questions related to the burden of COVID-19 on the broader healthcare system. The legislature charged the Massachusetts Health Policy Commission with studying the effects of COVID-19 on the Massachusetts healthcare system, to help guide reinvestment and reconstruction of the system. Among the work of the interim report (released April 2021), the team used claims data in the CRDB to evaluate telehealth adoption and behavioral health deferrals. They demonstrated that due to the pandemic, telehealth accounted for 80% of healthcare visits in May 2020. They also showed that the pandemic led to a significant reduction in behavioral health care visits (25% of pediatric patients discontinued psychotherapy after the pandemic began). Massachusetts lawmakers are intent on rebuilding a more resilient system to support patients whose access to care suffered indirectly and solve health challenges created by the pandemic (such as the national emergency in pediatric mental health). The Health Policy Commission report is the foundation of real-world data that can shape their conversations and decision-making.
Effective public health policy that leaves no patient behind starts with understanding the care and services that are accessible to patients. A recommendation to test for COVID-19 is unlikely to be followed by an uninsured patient without access to affordable testing. Building a more equitable system that can support vulnerable populations starts with understanding their needs and barriers to care.
In September 2020, researchers from Johns Hopkins University used claims data available in the CRDB to understand the variance in the amount billed for a COVID-19 test. By analyzing claims for diagnostic and antibody tests across states, they identified the most common places tests were handled and found a wide variation in the rate billed to insurers (or patients themselves, when uninsured). In a subset of states, they also found that the rate billed far exceeded the Medicare reimbursement rate, creating a financial barrier to access – particularly for the uninsured. The results, picked up by the Houston Chronicle, put a spotlight on access to testing as a barrier to an effective and equitable COVID-19 response. The study fueled a conversation about how future pandemic policies can close gaps in patient access, and where investments to improve access should be made.
Working with the Economist in March 2021, health analytics company A3.AI set out to build the tools to better understand differences in COVID-19 outcomes. Drawing upon a combination of clinical records, social determinants data, mortality, and insurance claims data in the CRDB, the team built an interactive COVID-19 risk estimator that evaluated demographics and health conditions. The model showed an increase in the risk of hospitalization and death for multiple comorbidities, including serious heart conditions (a 45% and 30% increase, respectively), Type II Diabetes (40% and 20%), and Chronic Obstructive Pulmonary Disease (or COPD, at 40% and 25%). The Economist disseminated the model which provided a public, evidence-based framework to quantify the risk of hospitalization and death from COVID-19. The study helped identify vulnerable populations for healthcare professionals and policymakers to consider in their approach to COVID-19 prevention and treatment.
The team at the Economist and A3.AI also aimed to shape the conversation about the disproportionate effects of COVID-19 on different ethnicities. Leveraging social determinants data and claims records available in the CRDB, they segmented COVID-19 diagnoses across socioeconomic characteristics. They found that while non-white Americans were 2.3x more likely to catch COVID-19 than white Americans, Hispanic Americans were especially at risk (3x as likely). Their risk exceeded black Americans’ (1.3x) as well as Asian Americans’ (2x), and Native Americans and Pacific Islanders’ (2.1x). The increased risk for contracting COVID-19 persisted for each minority, even after controlling for socioeconomic factors like education, income, and age – fueling an ongoing conversation about what factors could be driving the inequities and how to address them.
This is the tip of the insight iceberg
We are grateful to support a mission-critical collaboration to better understand COVID-19. This humble initiative has produced critical evidence that can help us respond to COVID-19 and prepare for future pandemics. There remain hundreds of open questions about the impact of the COVID-19 pandemic. Unlocking real-world data for research can help further elucidate the biology, influence behavior, and ultimately inform evidence-based public health policy.