Data Sharing Agreement

The Data Sharing Agreement (DSA) is an approved PCORnet template for use by research institutions to speed prep-to-research queries. The DSA defines the standard terms to which the Coordinating Center for PCORnet® will adhere when data are sent from the Network Partners to the Coordinating Center. The DSA also contains a template showing the flow of data through the queries.

Access the Data Sharing Agreement here.

Data Science Analyst Training

The PEDSnet Data Science Analyst course provides training on the structure and use of the PEDSnet CDM for research and approaches to study-specific data quality assessment.

Access the Data Science Analyst course.

HERO Data Dictionary

Use this resource to review information, content, format, and structure of the HERO (Healthcare Worker Exposure Response & Outcomes) Research database and the relationship between its elements.

Access the resource here.

Daquery

The PaTH Clinical Research Network (CRN) Department of Bio-Medical Informatics team developed Daquery a tool used to deploy code, as well as to automate and archive network-wide Quality Assurance queries. The code is publicly available and may be useful to support other CRNs data processes.

Access the Daquery resource here.

PCORnet Common Data Model

The PCORnet Common Data Model, developed by the PCORnet community, standardizes millions of data points from the Network’s diverse clinical information systems into a common format. As a result, users of PCORnet can ask the same question simultaneously to hundreds of disparate systems and receive a clear, reliable answer.

Access the PCORnet CDM.

PaTH: How EHR Data is Collected and Protected via a Chocolate-Making Analogy

The PaTH Clinical Research Network (CRN) developed this guide to explain how electronic health record (EHR) data is captured, protected, and utilized for research purposes via a chocolate-making analogy.

Access the resource here.

PaTH to Health: Diabetes, Chocolate Making & Data Extraction Video

This video on electronic health data utilizes the metaphor of making chocolate to clearly lay out how electronic health records can be used to anonymize data. It is a useful tool for clearly explaining EHRs and the privacy inherent in building a research network.

Access the resource here.