Cancer Informatics

Clinical Informatics

The primary aim of the Clinical Informatics Shared Services (CISS) is to provide state-of-the-art centralized clinical informatics services for the support of Masonic Cancer Center operations, research, and quality of care improvement effort. These services include access to rich clinical and genomics database, data extraction and preparations, secure and robust informatics infrastructure, advanced analytics, application development as well as collaborative science opportunities with highly qualified informatics consultants and faculty.

Submit Requests:

Consultation   

Services

Access to Data:
Clinical, Genomics, OnCore

Feasibility Analysis:
Research, Quality of Care Improvement, Operations, Patient Recruitment

Dataset Preparation & Extraction:
Formatting, Summarization, Codeset Mapping (ICD9/ICD10, NDC, RxNorm, etc.)
Data repositories & registries

Natural Language Processing:
Extracting coded data and information from notes

Application Development:
Interface Design, Mobile Apps

Data de-identification:
Fully de-identified & Limited Datasets

Informatics Infrastructure:
Secure, Compliant and robust Data Infrastructure

Informatics Resources:
Informatics Consultants Data Analysts Database Engineers Developers

 Data Environment

Academic Health Center Information Exchange (AHC-IE):

  • Clinical EMR data for ~ 2.5M Fairview and University of Minnesota Physicians (UMP) patients.
  • Genomics data

OptumLabs Data Warehouse (OLDW):

  • De-identified claims and electronic health records data for >150M lives (20% with EMR).
  • OnCore® enterprise CTMS:

Extraction of Clinical Trial Data that are managed by OnCore® enterprise CTMS

Dental Records

  • AaxiUm records through School of Dentistry (in progress)
  • Master Death Index:
    • Death Certificates through Minnesota Department of Health

Spatial Data:

  • Census data at the block group level from the 2010 Census.
  • The Clinical EMR data is geocoded and enhanced latitude/longitude/block data elements

UMLS Data:

  • Standard Terminology and code sets including ICD-9/10, LOINC, NDF-RT, RxNorm, CPT, HCPCS

Masonic Cancer Center Data Registries and Repositories

  • Bone Marrow Transplant database (BMT): Blood and Marrow Transplant database used by the Cancer Center to capture post-transplant outcome data on subjects.
  • Laboratory information management system (LIMS):  Subjects’ samples processed data based on study objective. For Example: number of aliquots, analyte, pre and post Ficoll.
  • FreezerWorks: Research samples freezer inventory data. Such as: Freezer name, shelf, rows, box etc.

Rates and Publications

CISS provides consultation free of charge to all MCC members to help prepare the informatics resource sections for grant applications and to provide initial cost estimates for other informatics projects.

Extended collaboration with the Informatics team should be directly supported by the appropriate funding sources. Costs for services are recovered through percent effort of personnel or through the ISO model.

Publications resulting from informatics work should merit co-authorship: the order of authorship is up to the principal investigator/primary author.

Qlikview Basics - CISS
Connecting to Qlikview - CISS

Cancer Bioinformatics

With a focus on data associated with a large-scale molecular studies, our services are developed on an ad hoc basis depending on the needs of the given researcher. These needs may be as straightforward as working with researchers to access tools available within the University (such as those provided by the Minnesota Supercomputing Institute) or outside the University.
 

More often, our staff members may serve as collaborative partners in the development of custom databases and analysis pipelines involving large data sets generated in high throughput projects.

Complete a: request form for informatic services

Services We Offer

Requests for assistance will be placed in order of priority as listed below:
  • Projects that provide funding for Cancer Informatics experts in the core
  • Grant preparation
  • Data analysis for cancer-related projects

Planning

  • Design experiments involving large-scale molecular studies
  • Referrals to MSI software and staff for other molecular studies
  • Referrals to external software sources (e.g., EnsEMBL, FANTOM)
  • Write bioinformatic components of grant proposals
  • Identify leading-edge technologies to be incorporated in research plans

Analysis

  • Conduct analysis of high throughput molecular data (e.g., mRNA, miRNA, insertional mutagenesis studies, ChIP-seq)
  • Assist with the interpretation of results
  • Recommend presentation and visualization methods
  • Author bioinformatics component of manuscripts