Computational Phenotyping Core

Our faculty and staff collaborate in research that requires the use of databases that range from electronic medical records with clinical notes to incidence of disease, hospital discharge, and various socio/economic factors. Some projects require the creation of de novo databases for unique purposes.

We can link vast datasets for projects that consider numerous and diverse sources. We also have capabilities around de-duplicating patient records, important when working across multiple health systems, or systems with multiple health centers, that may see the same patient in various locations.

Collaborative Research Based on Electronic Health Records

The Institute supports faculty/clinicians at area health systems in data management and integration, harmonization, study design, analysis, visualization, and relaying findings, which typically result in publication. Our health system colleagues maintain their own secure data environment and provide access to our vetted and verified team members.   

The Institute has been integral to several studies in collaboration with The Cleveland Louis Stokes Veterans Administration, notably the development of a clinical quality dashboard the was integral to the VA’s Emergency Department earning Level I accreditation in elderly care, the first among all VA’s nationwide.  Read more here.

Mapping and Standardizing Data Using a Common Data Model

The Institute works with the Observational Health Data Sciences and Informatics consortium (ODHSI), an international collaborative of researchers that have developed an open-source common data model that allows for the systematic analysis of disparate observational databases. The common data model adopted by the consortium is the Observational Medical Outcomes Partnership (OMOP). This links varying health systems’ coding systems to a standardized vocabulary, with minimal data loss.

Once a database has been converted to the OMOP common data model (CDM), research can be conducted using standardized open source as well as proprietary analytical tools. Collaborating with all ODHSI participating institutions facilitates inquiries at a regional, national, or international scale.

We are currently working with University Hospitals/Cleveland to validate mapping their clinical data to the OHDSI OMOP common data model. This supports UH’s system-specific research and will facilitate CICB/UH collaborating researchers’ access to the OHDSI consortium’s datasets. Read more here

Exploring Unstructured Data within EHRs using EMERSE (Electronic Medical Record Search Engine)

EMERSE is a search engine that facilitates the use of free-text documents in medical records (clinical, radiology, pharmacy, and pathology).

It supports clinical and translational research, including:

  • Cohort building
  • Internal quality improvement and quality assurance initiatives
  • Complex case review
  • Patient outcomes studies
  • Creation of clinical registries

EMERSE makes it possible to search information regarding the clinical phenotype of patients that is in free text vs information searchable through structured diagnostic/billing codes.

Currently in the pilot phase at University Hospitals/Cleveland, EMERSE will be launched system-wide at UH in the fall of 2021. Read more here

Creating and Linking Datasets for Population Health Research

Northeast Ohio Cancer Risk Assessment and Surveillance Engine (NEO-CASE)

The Institute played an integral role in the creation of NEO-CASE, which links various data sources, including the U.S. Census American Community Survey and the Ohio Cancer Incidence Surveillance System (OCISS). These linked data sets can provide snapshots of cancer burden, sociodemographic, and health services access for communities defined at the county, zip code, or municipality level.  NEO-CASE is an important tool to identify and form hypotheses about disparities in cancer-related health services and outcomes along dimensions of demographics, socioeconomic status, and geography. This facilitates cancer control research and practice, with input from the academic research, health system, public health, and community advocacy communities. Read more here.

Core Contact:

Mark Beno, MSM, Senior Director of Strategic Operations

CICB_info@case.edu