This report describes the results of a data query of the patients with sensory-related health conditions that had at least 1 face-to-face encounter and a recorded diagnosis code (e.g., ICD-10) at a health care setting across PCORnet between January 1 – December 31, 2024. The query used a 5-year “look-back” period to identify patients with diagnosis codes for specific sensory-related health conditions that were reflected in the electronic health record.

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 report describes the results of a data query of the patients with selected metabolic and endocrine conditions that had at least 1 face-to-face ambulatory encounter and a recorded diagnosis code (e.g., ICD-10) at a health care setting across PCORnet between January 1 – December 31, 2024. The query used a 5-year “look-back” period to identify patients with diagnosis codes for specific metabolic and endocrine conditions that were reflected in the electronic medical record.

This report describes the results of a data query of the patient population with at least 1 face-to-face encounter and a recorded diagnosis code (e.g., ICD-10) at a health care setting across PCORnet between January 1 – December 31, 2024. The query results will enhance public awareness of the population of patients across sites participating in PCORnet that potentially would be available for future health care research.

This report describes the results of a network data query of the patient population of women receiving health care services at clinical sites across PCORnet between January 1, 2019 – December 31, 2023. The query results will enhance public awareness of the population of patients that are women across sites participating in PCORnet that potentially would be available for future health care research.

This query of PCORnet data resources describes the patient population who have undergone gene therapy between January 1, 2016, and June 30, 2024, with distinct cohorts created for gene-therapy-eligible cancer patients and gene-therapy-eligible noncancer patients. The query results will enhance public awareness of the utilization of gene therapies by relevant health conditions across sites participating in PCORnet.

This document outlines the data quality validation processing for populating the CDM data model and defines measures that each domain follows during validation processing. Research sites can use this guide locally to help improve their data prior to populating the CDM.

This report characterizes the patients with recorded diagnosis codes for mental and behavioral health (MBH) conditions that received care at health care settings across institutions participating in PCORnet. The data report will inform how PCORnet can be used for patient-centered CER studies on interventions related to MBH conditions, and to inform opportunities to enhance PCORnet data resources for MBH research.

This query of PCORnet data resources describes the sociodemographic and clinical characteristics of the population of pediatric patients ages birth to 20 years old with at least one face-to-face health care encounter at a PCORnet partner site between January 1, 2023 – December 31, 2023. The query results enhance public awareness and provide investigators and the public with information on ways PCORnet can be used to conduct patient-centered CER to improve the health of children and youth.

This query of PCORnet® data resources describes the sociodemographic and clinical characteristics of a population of patients with a pregnancy-related event that had a healthcare encounter at a partner site between October 1, 2016 – January 1, 2022. The query results will inform how PCORnet can be used for patient-centered comparative clinical effectiveness research (CER) research on MMM and to inform opportunities to enhance PCORnet data resources for MMM research.

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.

This query of PCORnet® data resources explores the use of telehealth services among patients at partner sites. The query results aim to showcase how the PCORnet infrastructure can identify disparities in telehealth delivery, understand trends pre- and post-COVID-19, and illustrate how populations managed chronic conditions using telehealth services throughout the pandemic.

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.

This query of PCORnet data resources describes a population of patients with intellectual and developmental disabilities (IDD) with a healthcare encounter at a partner site. This query is the largest known, national-scale descriptive analysis of IDD populations using electronic health record (EHR) data. Query results inform how PCORnet can be used for patient-centered comparative effectiveness research (CER) research on IDD and to inform opportunities to enhance PCORnet IDD data resources.

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.

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.

The INSIGHT Data Dictionary provides a detailed look at the data elements in INSIGHT's Central Repository, including their format and content.

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.

GPC Reusable Observable Study Environment (GROUSE): GROUSE is a Greater Plains Collaborative (GPC) project (as well as name of the data enclave) to obtain health insurance claims from the Center for Medicare and Medicaid Services through the Research Data Assistance Center (ResDAC). GPC currently have 2011-2017 Medicare data and 2011-2012 Medicaid data from 9 states in the GPC.

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.

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.

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.

The PCORnet Common Data Model, developed by the PCORnet community, standardizes millions of data points from the Network’s 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.

The PaTH Clinical Research Network (CRN) developed this training to understand the importance of statistical tests in explaining study data, to become familiar with some statistical language, such as p values and null hypotheses and to be able to state some outcomes we are examining in the PaTH to Health Diabetes Study.

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.

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.

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.

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.

Muench and Le review the history of the rise in opioid addiction and overdose deaths, prior efforts to track pain medication prescriptions, and current efforts to organize the ADVANCE Clinical Research Network electronic health record data to more easily describe prescribing pattern changes that follow interventions at national, state, and clinic levels.

This is the PCORnet Common Data Model Glossary. Use this to learn how terms are used in the context of the PCORnet Common Data Model.

This presentation goes over the differences between intellectual property and data, Open Access, attributions, and Creative Commons licenses. Speaker: John Wilbanks