What is the difference between Identified and De-Identified requests?
De-Identified information has had all Patient Health Information (PHI) removed from the record that could be used to identify the subject. This includes date elements except year, and medical record numbers. Questions related to what constitutes PHI may be referred to the Privacy Office at Privacy@Nebraskamed.com.
What are ICD10 Codes/Procedure Codes/Medication IDs and where can I find them?
ICD codes or International Classification of Diseases are the categories used to describe categories of diseases and health problems widely used in the medical record. ICD10 codes were implemented in 2015 and replace the older ICD9 codes. Links to compendiums of ICD codes, as well as dictionaries of lab tests, medication IDs, and Surgery or Procedure codes, can be found below.
The Electronic Health Record (EHR) includes a whole range of data in comprehensive and summary form. It's a digital version of a patient's paper chart. EHR Systems combined as a single, large database, become a powerful tool to conduct comparative effectiveness research. The many modules available in the EHR make refining your research question critical to producing reliable and accurate results.
○ UNMC Clinical Codes Lookup *
*Resource only available while connected to UNMC internal network
What things should I consider when crafting my EHR query?
- Inclusion Criteria – What conditions are you looking for?
- Use of ICD10 (International Classification of Diseases) are widely used in the medical record and can be easily queried. A link to a compendium of these codes can be found above.
- Is gender a consideration?
- Does it matter where in the medical record a condition is located? i.e. Problem list, discharge diagnosis or both?
- Is the location of a visit important? Do you include rural practices or limit to only certain clinics/care centers.
- Exclusion Criteria – What don't you want included?
- Healthy other than the condition of interest?
- Are certain medication regimes acceptable? i.e. Statins, NSAIDs, etc.
- Cancer at any point in the history?
- Discrete Data – Is the data you are interested in located as a discrete field in the record?
- Calculated fields like pulmonary function tests and ejection fraction are not discrete fields
- Text files like pathology or radiology results are also not discrete fields.
- Some discrete fields like encounter and procedural data are only available since the implementation of EPIC in 2012.
- Are you asking for Protected Health Information?
What is the Clinical Research Analytics Environment (CRANE) at UNMC?
UNMC’s Clinical Research Analytics Environment (CRANE) is a flexible, inclusive clinical data warehouse combined with the tools, processes, and people needed to support knowledge discovery. It contains de-identified, structured data for UNMC research and quality improvement efforts. CRANE can be used as a search discovery tool allowing qualified researchers to search de-identified patient data from sources that would otherwise require IRB-approval or asynchronous consideration. CRANE is considered an environment because it is more than just the software and available data. CRANE is an entire ecosystem consisting of an IRB-approved, de-identified clinical data warehouse (CDW) that provides researchers with access to well organized, characterized, and standardized patient-level data in compliance with HIPAA, the common rule, and best practices. This CDW consolidates data from a variety of clinical sources to present a singular, multi-faceted view of the available data.
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 – which is a clinical condition, characteristic, or set of clinical features determined exclusively from the data available in EHRs and ancillary data sources without chart review or interpretive analysis by a clinician – for clinical research. Within CRANE are a number of data marts organized to meet the needs of collaborating Research Networks.
The National Patient-Centered Clinical Research Network (PCORnet) publishes a detailed Common Data Model (CDM) that is linked to a secure mechanism for querying. The latest version of the CDM is v6.1, which was released in April 2023. 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 the query compiler BABEL. These queries require local customization, so each site then customizes the query to work locally.
In order to further improve query sharing, the GPC is collaborating with Harvard’s clinical informatics team to deploy a large-scale flexible data mart within i2b2 termed Scalable Collaborative Infrastructure for a Learning Healthcare System (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.
CRANE Connections – PCORnet and PopMedNet
UNMC in partnership with Great Plains Collaborative (GPC) Network (11 other Midwestern academic medical institutes) received funding from the 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 CRANE is operational from the de-identified version of ICRD in support of PCORnet sponsored Comparative Effectiveness Research Trials.
PopMedNet is software developed by Harvard Medical School. UNMC’s Research IT Office 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 the de-identified version of ICRD and can be used by UNMC & Nebraska Medicine researchers. PopMedNet also connects to the de-identified version of ICRD but serves GPC network partners