Data Management

Pertaining to administrative processes, including acquiring, validating, storing, protecting, and processing required data to ensure the accessibility, reliability, and timeliness of the data

Master Code Set

Posted on by Jodi Snare

The master code set provides a centralized, standardized reference of clinical codes across various disease areas along with their corresponding descriptions and classifications. It is designed to support consistent cohort definition, analysis, and reporting by ensuring uniform use of codes across studies and sites. By consolidating all relevant codes into a single, curated resource, the master code set reduces ambiguity, improves reproducibility, and streamlines multi-site research workflows. This comprehensive mapping enables researchers to efficiently identify, compare, and analyze patient populations across a wide range of conditions and data domains.

View the master code set. (Excel File)

Common Data Model (CDM) Data Quality Validation

Posted on by Jodi Snare

This document outlines the data quality validation processing for populating the CDM data model and defines measures that each domain follows during validation processing. Data quality validation covers several aspects including data content validation, data integrity and data profiling, with the goal of improving data content quality and integrity of the CDM data model. Research sites can use this guide locally to help improve their data prior to populating the CDM. Implementing this ahead of time causes fewer data check failures during the data curation process.

Access the CDM Data Quality Validation guide here.

INSIGHT Data Visualization Templates

Posted on by Jodi Snare

The INSIGHT Data Visualization Template provides templates of data visualizations that capture the demographic breakdown of a CRN’s patient cohort. A list of data elements available to request is also available. These slides can be reformatted to suit a CRN’s available data elements and highlight strengths of the patient cohort.

Access the Data Visualization Template here.

GPC Tumor Table Transformation and Linkage

Posted on by Jodi Snare

The PCORnet tumor table contains data from hospital tumor registries that are formatted according to standards developed by the North American Association of Certified Cancer Registrars (NAACCR). All hospitals that are accredited by the American College of Surgeons Commission on Cancer employ trained registrars to abstract medical record data according to these specifications. Researchers can use this resource transform their own tumor registries.

Access the GPC Tumor Table Transformation and Linkage

Structured fields for demographic, clinical, and treatment observations are included, and the data are considered to be high quality. GPC tumor table documentation includes specifications for data formats, quality checks, and relationships with other CDM tables. This standardization allows linkages between NAACCR data and the other CDM tables. It also allows queries of the NAACCR data to be quickly deployed across the network.

GPC sites have already transformed their hospital tumor registry data into the PCORnet TUMOR table format. Table specifications can be found here. A sample ETL code and workflow are attached for references.

To assess the quality and quantity of tumor registry data found in the TUMOR table at GPC sites, a quality control script was created to be run against the newly created TUMOR tables. QC reports are being used for quality evaluation.

Data Study Flow Resources – Basic

Posted on by Jodi Snare

This diagram shows a basic data flow in a study powered by PCORnet® and is intended for sites to include in their IRB application. Using this document, project teams can ensure consistency in IRB applications and speed IRB submission by providing a template for sites to quickly fill in the blanks based on data flow in their study.

Access the Basic Data Study Flow Diagram.

Data Study Flow Resources – Complex

Posted on by Jodi Snare

This diagram shows a complex data flow in a study powered by PCORnet® and is intended for sites to include in their IRB application. Using this document, project teams can ensure consistency in IRB applications and speed IRB submission by providing a template for sites to quickly fill in the blanks based on data flow in their study.

Access the Complex Data Study Flow Diagram.

Data Science Analyst Training

Posted on by Jodi Snare

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.

PaTH to Health Just-In-Time Data Analysis Training Part 1

Posted on by Jodi Snare

The PaTH Clinical Research Network (CRN) designed this training explaining the benefits and limitations of observational studies, common data issues and how to manage them via the PaTH to Health Diabetes Study.

Access the resource here.

Clinic Staff as a Unique Stakeholder Group in Patient-Centered Outcomes Research

Posted on by Jodi Snare

Research Action for Health Network (REACHnet) and LPHI discuss the role of clinic staff in patient-centered outcomes research. Through a project funded by the PCORI Eugene Washington Engagement Award, LPHI implemented pragmatic research studies that resulted in a training workbook to help clinic staff better understand the research process.

Speaker: Daniele Farrisi

Presented: March 19, 2019

Access the resource here.

Pilot Linkage Project Process and Results

Posted on by Jodi Snare

PCORnet CMS Linkage Pilot Team has released a white paper to help others learn more about how to use Medicare claims data to support studies. The pilot team developed a process for using Medicare claims data to supplement PCORnet data in pragmatic clinical trials such as the ADAPTABLE study, which compares the effectiveness of different daily aspirin dosing for heart attack and stroke prevention. The project team describes the processes and data flows used successfully in the pilot, as well as lessons learned and recommendations.

Access the resource here.