FDA Sentinel System's Coronavirus (COVID-19) Activities

In June 2020, preliminary results for the Randomised Evaluation of COVID-19 Therapy (RECOVERY) trial conducted in the UK indicated benefit from dexamethasone in severely ill hospitalized patients with COVID-19 but potential harm in those not requiring oxygen. In October 2020, the National Institutes of Health (NIH) issued COVID-19 treatment guidelines advising against systemic corticosteroid use in patients with mild to moderate COVID-19. Using two large US health care claims databases, we examined systemic corticosteroid use among non-hospitalized patients with COVID-19.

Health plan claims may provide complete longitudinal data for timely, real-world population-level COVID-19 assessment. However, these data often lack laboratory results, the standard for COVID-19 diagnosis.

We assessed the validity of International Classification of Disease, Tenth Revision, Clinical Modification (ICD-10-CM) diagnosis codes for identifying patients hospitalized with COVID-19 in U.S. claims databases, compared to linked laboratory results, among six FDA Sentinel System Data Partners (two large national insurers, four integrated delivery systems) from February 20 - October 17, 2020. We identified patients hospitalized with COVID-19 according to five ICD-10-CM diagnosis code-based algorithms, which included combinations of codes U07.1, B97.29, general coronavirus codes, and diagnosis codes for severe symptoms. We calculated the positive predictive value (PPV) and sensitivity of each algorithm relative to laboratory test results. We stratified results by data source type and across three time periods: February 20 - March 31 (Time A), April 1 - April 30 (Time B), May 1 - October 17 (Time C).

We seek to determine if race and ethnicity are associated with health outcomes among persons hospitalized with COVID-19, after adjusting for relevant risk factors. This study will also evaluate race and ethnicity trends and the impact of race and ethnicity on COVID-19 outcomes in patients less than 65 years old, a population that has not been well characterized.

Epidemiologic data indicate that communities of color continue to be disproportionally impacted by the ongoing COVID-19 pandemic, with members of Hispanic, American Indian, and non-Hispanic Black populations three times more likely to be hospitalized and die of COVID-19 than members of White and Asian populations (1,2). Data from the Centers for Disease Control (CDC) also show that although Black and Hispanic individuals account for 13.4% and 18.5% of the U.S. population respectively (3), they account for almost 17% and 28% of COVID-19 cases, and 21% and 16% of COVID-19 deaths(4). These findings have emerged despite race and ethnicity data not being consistently captured at the county, state, and national levels.

Our specific aims are as follows:

Evaluate the association between race and ethnicity and COVID-19 critical disease and in-hospital death among patients overall and under 65-year-old hospitalized for COVID-19.

• To evaluate the association between race and ethnicity with critical COVID-19 disease among patients hospitalized with COVID-19 after adjusting for demographic and clinical risk factors.
• To evaluate the association between race and ethnicity with in-hospital deaths among patients hospitalized with COVID-19 after adjusting for demographic and clinical risk factors.

Sources:

1. Laboratory Confirmed COVID-19-Associated Hospitalizations. https://gis.cdc.gov/grasp/COVIDNet/COVID19_3.html

2. The Color of Coronavirus: COVID-19 Deaths by Race and Ethnicity in the U.S. https://www.apmresearchlab.org/covid/deaths-by-race

3. United States Census Bureau. Quick Facts. https://www.census.gov/quickfacts/fact/table/US/PST045219

4. CDC COVID Data Tracker. https://covid.cdc.gov/covid-data-tracker/#demographics

This project is funded by U.S. Food and Drug Administration (FDA) Office of Minority Health and Health Equity (OMHHE).

This presentation shares experiences of the US FDA’s Sentinel System during the development and implementation of its COVID-19-related studies by covering the following topics: 1) Rationale and development of a Master Protocol to identify health plan members with COVID-19 in the US FDA Sentinel System, classify COVID-19 disease severity, and ascertain relevant data elements; 2) Methods to identify persons with COVID-19 and key data elements validly within inpatient electronic health records; 3) Challenges and solutions to examining complications of COVID-19 in claims data; and 4) Approaches to enhance collaborations with researchers, data providers, and regulatory agencies to enhance the validity and generalizability of results.

It was presented as a symposium at the 37th International Conference on Pharmacoepidemiology and Therapeutic Risk Management. 

SARS-CoV-2 infection is associated with thrombotic complications. However, the risk of thrombotic events (TEs) for outpatient COVID-19 cases is unknown. This presentation aims to describe hospitalized TEs following an outpatient COVID-19 diagnosis among patients aged 40-79 years without known pre-existing risk factors for thrombosis.

It was presented as a Lightning Forum at the 37th International Conference on Pharmacoepidemiology and Therapeutic Risk Management. 

Data from COVID-19 randomized controlled trials (RCTs) may be used to develop clinical guidelines. It is important to understand differences between trial-eligible and real-world (RW) patients’ characteristics and outcomes. This objective of this presentation is to compare hospitalized COVID-19 patients who may meet key eligibility requirements for the Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV-4a) trial (RCT-eligible cohort) to patients without these criteria (RW-COVID cohort) and report unadjusted occurrence of invasive mechanical ventilation (IMV).

It was presented as a Lightning Forum at the 37th International Conference on Pharmacoepidemiology and Therapeutic Risk Management. 

The US Food and Drug Administration's Sentinel System was established in 2009 to use routinely collected electronic health data for improving the national capability to assess post‐market medical product safety. Over more than a decade, Sentinel has become an integral part of FDA's surveillance capabilities and has been used to conduct analyses that have contributed to regulatory decisions. FDA's role in the COVID‐19 pandemic response has necessitated an expansion and enhancement of Sentinel. Here we describe how the Sentinel System has supported FDA's response to the COVID‐19 pandemic. We highlight new capabilities developed, key data generated to date, and lessons learned, particularly with respect to working with inpatient electronic health record data.

Administrative claims data, which comprise most of the data in the current Sentinel Distributed Database, are limited in their ability to study severely ill hospitalized patients, including those in the intensive care unit. For example, data on duration of mechanical ventilation, symptom severity, oxygen saturation, supplemental oxygenation requirements, ventilator settings, and lung imaging features are not readily available in claims data. 

Information-rich unstructured electronic health record (EHR) data may address these challenges and enhance medical product safety surveillance. COVID-19 is a compelling use case for using unstructured EHR data to improve medical product safety assessment in Sentinel since studying COVID-19 requires accurate information about its symptoms, severity, comorbidities, and treatment outcomes and because patients with COVID-19 disease often present in emergency department and receive care in inpatient settings. 

This project will yield algorithms and methods to better position Sentinel for addressing future pandemics and advance Sentinel’s long-term objective of enhancing medical product safety surveillance by incorporating EHR data into surveillance methods. Specifically, we will use natural language processing (NLP) and text mining methods to identify patients with COVID-19 disease and to extract clinical features from unstructured EHR data. These features will complement structured data already available in the Sentinel Common Data Model (SCDM). This project will also develop processes that would allow us to more rapidly prototype EHR-based information extraction algorithms for new health outcomes of interest (HOIs) in the case of future pandemics and other needs.
 

The Sentinel System can be used to address numerous questions of importance to FDA during the COVID‐19 pandemic. One population of significant interest for study is pregnant women. Evidence suggests that pregnant women are more likely to experience severe illness related to respiratory infections, including COVID‐19, than nonpregnant women (1,2). Little information is available to support understanding the natural history of COVID‐19 disease in pregnant women, or the impact of COVID‐19 treatment upon pregnant women or the developing fetus.

To address vulnerable populations, including pregnant women, Sentinel recently published a COVID‐19 Natural History Master Protocol, designed to identify multiple COVID‐19 cohorts to support a variety of on‐demand queries and subsequent descriptive and inferential studies. The protocol can be adapted to various data sources with clinically rich data and included pregnant women as a specific population of interest. The EMA (European Medicines Agency) has also funded a project, called CONSIGN (“COVID‐19 infectiOn aNd medicineS In pregnancy”) designed to understand the natural history of COVID‐19 disease in pregnant women, including disease severity and clinical outcomes of COVID-19, medications utilization, and impact of COVID-19 treatment on neonatal outcomes. The CONSIGN study will be implemented in varied data sources across eight European countries. 

This project will implement the following (two) aims of the CONSIGN protocol:

1. To estimate the prevalence of medicines used and compare this among pregnant women with COVID‐19, pregnant women without COVID‐19, and non‐pregnant women with COVID‐19.
2. To describe severity and clinical outcomes of COVID‐19 disease in pregnant women with COVID‐19, according to treatments  received during pregnancy, and compare these data with those of nonpregnant women of reproductive age with COVID‐19.

(1) Allotey J, Stallings E, Bonet M, et al. Clinical manifestations, risk factors, and maternal and perinatal outcomes of coronavirus disease 2019 in pregnancy: living systematic review and meta-analysis. BMJ. Published online September 1, 2020:m3320. doi:10.1136/bmj.m3320

(2) Ellington S. Characteristics of Women of Reproductive Age with Laboratory-Confirmed SARS-CoV-2 Infection by Pregnancy Status — United States, January 22–June 7, 2020. MMWR Morb Mortal Wkly Rep. 2020;69. doi:10.15585/mmwr.mm6925a1

Among hospitalized non-pregnant adults with COVID-19, we aimed to describe the number of patients with hospitalized thrombotic events or death through 28 days. We stratified each outcome by d-dimer level and record of early intensive care services. We used electronic health record (EHR) data from the TriNetX Live™ USA Network to identify adults with positive COVID-19 antigen or PCR laboratory test results or documented COVID-19 diagnoses within ±3 days of a hospitalization record. We queried 65 health care organizations’ data from February 20, 2020 through October 16, 2020.