Secondary data are data that have been originally collected for purposes other than a specific research question. This includes data from sources like electronic medical records (EMRs), medical claims data, product or disease registries, and other digital health technologies. Secondary data are often used in pharmacoepidemiological research to evaluate the safety and effectiveness of medicines… Continue reading Secondary and Primary Data Integration in Clinical Research
Tag: Data
EMR to EDC Integration: Applications, Challenges and Operational Considerations
EMR to EDC Integration refers to the process of transferring data from Electronic Medical Records (EMR), which are used in healthcare settings to maintain patient health records, to Electronic Data Capture (EDC) systems, which are specialized databases used in clinical trials to collect and manage study data. This integration aims to automate data transfer, enhancing… Continue reading EMR to EDC Integration: Applications, Challenges and Operational Considerations
Converting Unstructured Data into Structured Data from EMR: Challenges and Solutions
Discover the challenges and solutions in converting unstructured data into structured data from Electronic Medical Records (EMRs). Learn how Natural Language Processing (NLP), standardized terminologies, and data integration tools can help overcome these obstacles, ensuring accurate and efficient data extraction for improved healthcare outcomes.
Chart Review and EMR Extractions in RWE Research
Two primary methods used to gather data for Real World Evidence (RWE) research are chart reviews and Electronic Medical Record (EMR) extractions. Chart Review involves manually extracting data from patient medical records, including both paper-based charts and digital documents. This method provides a rich source of detailed clinical information. EMR Extractions involve the… Continue reading Chart Review and EMR Extractions in RWE Research
Common Data Models in Clinical Research
In clinical research, data models are essential for organizing, storing, and analyzing complex healthcare data. Effective data modeling ensures accurate data integration, facilitates efficient data analysis, and enhances data sharing across different systems and studies. Let’s explore some of the most commonly used data models in clinical research and their applications. 1. CDISC… Continue reading Common Data Models in Clinical Research