(Summarized by the Zoom AI Meeting Agent; may contain errors or inaccuracies)
TriNetX Clinical Trials Platform Overview
Daniel explained the TriNetX platform, a clinical informatics platform used for facilitating clinical trials across multiple sites. He described how the platform allows researchers to identify specific patient pools for trials by analyzing demographic, diagnostic, and treatment data from electronic health records across 71 healthcare organizations in the US and 12 other countries. Daniel highlighted the platform's limitations, such as the absence of HIPAA information and restricted access to neonatal data, but noted its advantages, including frequent data refreshes and the ability to conduct cohort-based research for natural experiments using real-world data.
TriNetX Platform Features and Limitations
Daniel discussed the use of propensity score matching as a method to adjust for confounding variables in cohort studies, highlighting its limitations but emphasizing its reliability. He explained the user-friendly features of the TriNetX platform, including its cohort builder and in-system data analysis tools, which require no coding knowledge.
TriNetX Research Capabilities Overview
Daniel discussed the limitations and capabilities of TriNetX, a healthcare data analytics platform, focusing on its use cases and potential for medical research. He highlighted that while TriNetX can provide valuable insights into patient outcomes and disparities, it has restrictions on certain types of data, such as neonatal information and sensitive incidents. Daniel emphasized the importance of a thorough literature review to define research questions and build solid cohorts. He also outlined a structured approach to conducting TriNetX projects, covering foundational skills in weeks one and two, and more advanced topics in subsequent weeks. Daniel concluded by introducing a worked example to illustrate the platform's capabilities and encourage attendees to think critically about their research approaches.
Statin Use and Alzheimer's Risk
Daniel presented a study examining the relationship between statin use and Alzheimer's disease risk. He explained that while some studies suggested statins might reduce dementia risk, his analysis found that non-statin users were 2.23 times more likely to develop Alzheimer's, though the study population was relatively healthy. The findings, which controlled for age through propensity score matching, could potentially result in significant cost savings if applied to the broader population, as statins are typically low-cost medications. Daniel is working with students to develop this research into a manuscript.
TriNetX Platform Study Setup Demo
Daniel demonstrated how to access and use the TriNetX platform for starting a study. He explained the login process using a UCR net ID and Duo sign-in, and showed how to create a new study by entering basic information like study name and research purpose. Daniel highlighted key features such as the query builder for searching patient data, the ability to create Boolean logic chains, and options for filtering by demographics like ethnicity, language, and marital status. He also advised adding team members to the study for collaboration and emphasized the importance of using meaningful race categories when filtering data.
TriNetX Platform Overview and Features
Daniel provided a detailed overview of the TriNetX platform, explaining how to search for and analyze medical data using various coding systems like ICD-10, CPT codes, and LOINC codes. He demonstrated how to create cohorts based on specific criteria, such as A1C levels, and showed the process of sorting patients by age or sex. Daniel also addressed technical issues, such as login problems, and clarified that only UCR email account holders with TriNetX accounts can access the platform.
Data Analysis Techniques
Daniel explained the limitations of tracking medication adherence in electronic health records and demonstrated how to use Boolean logic and the "Count Patients" button to refine cohorts. He clarified that Trinetx does not analyze patient notes for diagnosis codes due to data reliability issues, and discussed how hospitals use CDI programs to add missing codes. Daniel also covered how to conduct studies on medication adverse effects, and emphasized the importance of proper cohort selection by introducing the "Doctors Don't Pay Money Late" mnemonic for comprehensive data review.
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