SCCM Account Access
SCCM recently updated its digital infrastructure. If you have an existing SCCM account, and have not logged in since November 1, 2024, you will need to create an account with the email address associated with your previous SCCM account. Learn more about SCCM account access here. 

Some website functionality may be limited as improvements continue. Please ensure you are logged in for the best experience.

 
CURE ID

CURE ID

Aggregating and analyzing COVID-19 treatments from EHRs and registries globally

visual bubble
visual bubble
visual bubble
visual bubble

This program is a collaboration between the Society of Critical Care Medicine (SCCM) and the CURE Drug Repurposing Collaboratory (CDRC) to extend SCCM’s VIRUS Registry work beyond its current scope. The goal is to crowdsource the global medical community for their experience in using repurposed drugs to treat infectious diseases that have no adequate approved therapies, such as COVID-19. This information may help identify promising treatments that can be investigated further. It may also help identify ineffective treatments. A package of tools called the edge tool will be tested; its purpose is to help healthcare institutions participate in CURE-ID with minimal effort. The investigators plan to expand beyond COVID-19 to sepsis and meningitis. The project’s focus is to create the data infrastructure locally for future research studies and embedded clinical trials.

Reach out to the SCCM contact below if you are interested in participating or receiving more details.

CDRC Contact: 
Smith Heavner, RN, PhD
Scientific Director
Critical Path Institute

SCCM Contact:
Chase Hamilton
Program Manager
Send email

Frequently Asked Questions

What is drug repurposing?

Drugs are approved by the U.S. Food and Drug Administration (FDA) for a specific disease. Drug repurposing, also called off-label use, is when clinicians use FDA-approved drugs to treat diseases for which they were not approved or use those drugs to treat different aspects of the disease, different populations, in different doses, or in different combinations.

What is the edge data automation tool?

The edge tool is a package of resources developed to expedite the implementation of data model extraction, transformation, and loading (ETL) of the Observational Medical Outcomes Partnership (OMOP), which is a data quality dashboard and platform for building exportable cohort definitions. This process uses graphic user interfaces to aid in mapping concepts from a hospital’s proprietary data model to OMOP (see What is concept mapping? below). The edge tool can assist in extracting data from discrete fields or those with defined ontologies (e.g., drop-down menus, type-ahead fields, or fields restricted to integers). Examples of discrete data include flowsheet rows in Epic (e.g., vital signs, nursing assessments), measurements (e.g., laboratory results), and certain past medical history fields and assessment forms. The edge tool cannot extract data from unstructured fields such as notes or reports (e.g., imaging results, patient histories, physical examination findings). The edge tool was developed by Johns Hopkins University (JHU) to automate data extraction from different electronic health records and convert it into the OMOP format. JHU deployed the edge tool using a cohort of sites recruited through the SCCM VIRUS Registry, with the support of Emory University School of Medicine.

What is the Observational Medical Outcomes Partnership Common Data Model?

The Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM), developed by the Observational Health Data Sciences and Informatics (OHDSI) community, allows for the systematic analysis of disparate observational databases. The concept behind this approach is to transform data contained in these databases into a common format (data model) and common representation (e.g., terminology vocabularies, coding schemes), and then perform systematic analyses using a library of standard analytic routines written based on the common format. The OMOP CDM organizes electronic health record (EHR) data into a standard set of tables using standard vocabularies such as LOINC, RxNorm, SNOMED, and ICD-10. Once data from an EHR has undergone extraction, transformation, and loading (ETL) into the OMOP CDM, it can be consolidated and analyzed with data from other EHRs that have undergone ETL process into the OMOP CDM.

What is concept mapping?

A concept is a specific type of data captured in the EHR. In a common data model, concept IDs help standardize the process of how data is obtained, captured, and stored. It is a clear definition outlining acceptable methods or devices for capturing the measurements. For example, in the Observational Medical Outcomes Partnership (OMOP), different ways of measuring, capturing, and recording the patient’s respiratory rate are stored in concept IDs.

What is SCCM’s Viral Infection and Respiratory Illness Universal Study?

The Viral Infection and Respiratory Illness Universal Study (VIRUS) Registry from SCCM’s Discovery, the Critical Research Network, is a global COVID-19 registry that tracks ICU and hospital care patterns. SCCM encourages enrollment of VIRUS participating sites as well as national and international collaboration on ancillary studies. The de-identified, HIPAA-compliant database was developed to capture both core data collection fields containing clinical information collected for all patients and an enhanced data set of daily physiologic, laboratory, and treatment information. The case report forms were adapted from those of the International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) and the World Health Organization with a focus on ICU-specific context. Participating sites retain all rights to the data they contribute and have full access to their own data through the ancillary study submission process. Participating sites whose data are analyzed for article preparation are given collaborative coauthorships on the subsequent article publication. Also, participating institutions will have infrastructure for Observational Medical Outcomes Partnership (OMOP) and can use the data to support other research, such as quality assurance or participation in other registries.

What is the Clinical Data Interchange Standards Consortium’s Study Data Tabulation Model?

The Clinical Data Interchange Standards Consortium’s (CDISC) Study Data Tabulation Model (SDTM) is used for organizing data, standardizing structure for human clinical trial data tabulations, and tabulating nonclinical study data for submission as part of a product application to a regulatory authority such as the U.S. Food and Drug Administration (FDA). The FDA has developed a repository for all submitted trial data as well as a suite of standard review tools to access, manipulate, and view the tabulations. The SDTM includes domain classes such as interventions, events, and findings.

^