Clinical Research Analysis Environment (CRANE)
What is the Clinical Research Analysis Environment at UNMC?
UNMC’s CRANE provides researchers with access to well organized, characterized, and standardized patient-level data in compliance with HIPAA, the common rule, and best practices.
The primary data derives from the Nebraska Medicine EHR through a series of extracts and transformations to render the data in a well characterized common data model. The EHR data is supplemented with other patient level data sources including, but not limited to, state cancer registry data, encounter data from the Nebraska Health Information Initiative, and the Social Security death index.
Additional data sources to expand the patient level data include formally encoded anatomic pathology data, biomarker data, and pointers to biobank specimens.
The data is rendered in Office of the National Coordinator (ONC) for Health Information Technology approved standard codes and supported by both integrated R and SAS statistical software.
In an effort to support clinical researchers without exposing them to the technical details we are proposing an integrated approach providing as close to a “self-serve” data mechanism for qualified researchers.
What is a qualified researcher?
Access to the system is limited to UNMC faculty or their designees who have completed CITI training and are in compliance with UNMC competency training including HIPAA training and Information Security Awareness training. These researchers may apply for access to the de-identified data system for feasibility queries. Access to identified patient data requires IRB approval. Data release is through an honest broker for qualified faculty.
What does CRANE represent?
The research data marts exposed for use represent a detailed distillation of the raw EHR data normalized, standardized and processed with supporting metadata to assist researchers in calculating computable phenotypes for clinical research. Within CRANE are a number of data marts organized to meet the needs of collaborating Research Networks.
The National PCORnet publishes a detailed data model (CDM) that is linked to a secure mechanism for querying. PCORnet writes SAS code to query the CDM for supported trials. Because these are national trials with 50-80 data nodes, there is rigorous data quality checking and data characterization.
The Greater Plains Collaborative (GPC) is the prime mover behind our local development of CRANE. The 12 GPC member academic medical centers maintain architecturally similar systems allowing collaborative development of the technology. The GPC supports a query mechanism where local queries are shared through a BABEL. These queries require local customization so each site then messages the query to work locally.
In order to further improve query sharing, the GPC is collaborating with the Harvard team to deploy a large scale flexible data mart within i2b2 termed SCILHS. This allows shared queries through the Harvard SHRINE networked query tool. The SHRINE system operates through secure channels to individual data marts.
CRANE also provides a powerful clinical informatics education and research platform for extending data standardization and linking. A Big-Data-to-Knowledge U01 grant supports the process of linking anatomic pathology findings, biomarkers, and biobank data with the EHR data in CRANE. The resultant architecture is under development internationally, led by UNMC informatics researchers.
- I2B2 provides a web based portal interface developed by Harvard School of Medicine as part of their CTSA program.
- UNMC in partnership with Great Plains Collaborative (GPC) Network (11 other Midwestern academic medical institutes) received funding from Patient Centered Outcome Research Institute (PCORI) to implement I2B2 & PopMedNet.
- The I2B2 backend connects to the Integrated Clinical Research Data warehouse (ICRD) of UNMC.
- Currently the I2B2 is operational from de-identified version of ICRD in support of PCORnet sponsored Comparative Effectiveness Research Trials.
- PopMedNet is software developed by Harvard Medical School. RITO has built the production environment for PopMedNet.
- The PopMedNet software application enables simple creation, operation, and governance of distributed health data networks. It facilitates distributed analyses of electronic health data to support medical product safety, comparative effectiveness, quality, medical resource use, cost-effectiveness, and related studies.
- The PopMedNet enables UNMC to securely receive and send query data held by GPC partners. The software also allows GPC partners to maintain physical and operational control over their data.
In summary, the I2B2 software framework connects to de-identified version of ICRD and can be used by UNMC & Nebraska Medicine researchers. PopMedNet also connects to de-identified version of ICRD but serves GPC network partners.