Resources
Whitepapers
Data quality
Truveta Language Model
Advancements in AI have presented a unique opportunity to transform and clean massive streams of healthcare data to make it available for research, innovation, and patient care. This whitepaper explains the Truveta Language Model, a large-language model used to clean billions of EHR data points for health research.
Data analytics
Data security
Patient privacy
Powering device research
Medical device companies are challenged by a significant lack of real-world data on device use in clinical practice. In this whitepaper, learn how Truveta provides critical device specific information linked to deep clinical data to accelerate device research for over 150,000 unique medical devices.
Advancing cardiovascular research
Cardiovascular disease is a leading cause of death in the US, but researchers face many challenges when seeking to study the safety and effectiveness of drugs and devices used to treat it. This whitepaper highlights historical limitations of RWD and explains how Truveta addresses them to accelerate research on outcomes and care.
Truveta Mapper: A zero-shot ontology alignment framework
We share the technical details behind Truveta Mapper the underlying AI technology in the Truveta Language Model. Truveta Mapper leverages a multi-task sequence-to-sequence transformer model to perform alignment across multiple ontologies in a zero-shot, unified, and end-to-end manner. This paper was originally published at arXiv.
Ethics policy
We believe it is a moral imperative to harness the power of data to improve healthcare. We know we’ve taken on an enormous responsibility, and we pursue our work with a commitment to patient privacy, broadly enabling research and transparency about our data, all in close coordination with our member health systems.
Briefings & case studies
Prostate cancer data
Medical images
De-identified medical images are often hard to find and detached from clinical context, hindering research efforts. Truveta provides access to more than 85 million medical imaging studies integrated with complete EHR data. This briefing provides insight into the images available and how they’re advancing research.
Assessing device safety
Despite promising clinical data for novel pulmonary embolism therapies, there are no randomized prospective studies comparing them and guidelines have not been updated to reflect real-world safety data. This case study showcases findings from a peer-reviewed study using Truveta Data to compare the safety of devices from Boston Scientific and Inari Medical.
Why TLM outperforms other LLMs
Unlocking the full potential of healthcare data has long been hindered by issues of fragmentation and lack of structure. The Truveta Language Model (TLM) offers a premier solution for normalizing EHR data at scale, enabling novel research. This briefing highlights what sets TLM apart from general large language models.
Linked EHR-SDOH data
Clinical care affects only 10-20% of modifiable health factors, while 80-90% are influenced by behaviors, socioeconomic factors, and the environment. This briefing highlights how integrating social drivers of health (SDOH) data into real-world data analyses offers precise insights on unmet needs, healthcare disparities, and therapy performance.
Echo data
Echocardiograms contain crucial clinical observations relevant for cardiovascular research, but obtaining these measures at scale for real-world data analysis has been a longstanding challenge. This briefing highlights how Truveta is normalizing and extracting echo observations at scale for research, and outlines data availability for specific measures.
Timeliness
Timely data are critical for life sciences and healthcare organizations, enabling innovation and high-quality patient care. However, most RWD sources have lags of weeks to months. This briefing focuses on Truveta’s real-time data and showcases the clinical questions it enables researchers to answer.
GLP-1 prescribing
GLP-1s, originally created to treat diabetes, have been found to suppress appetites and induce substantial weight loss in many patients. Extensive media coverage and celebrity endorsements have created overwhelming demand for these drugs, but little is known about real-world use. This briefing highlights findings from an analysis of first-time GLP-1 prescribing trends.
PAD treatment
Peripheral Artery Disease (PAD) is a common disease that causes the narrowing of the arteries in the extremities. As part of PAD Awareness month, Truveta Research investigated disparities in the frequency of common procedures used to treat PAD, known as endovascular (or minimally invasive) revascularization, and the associated outcomes.
Webinars
Uncovering disparities in access to popular treatments: insights from linked EHR and SDOH data
Explore how linked EHR and SDOH data are accelerating the identification of health disparities for type 2 diabetes, Alzheimer’s disease, and heart disease treatments
Enabling timely comparative effectiveness research: head-to-head analysis of GLP-1s for weight loss
See the results of a real-world GLP-1 comparative effectiveness study and the impact of timely and representative RWD in assessing performance of new therapies.
Driving therapeutic innovation and de-risking clinical development: The power of RWD from EHRs
Speakers from Truveta, Reprieve Cardiovascular, The Permanente Medical Group, and Stanford Cardiovascular Medicine discuss how Truveta Data is being used to drive product innovation for acute heart failure.
Transforming clinical research: Scaling real-world data across diseases with expert-led AI
Hear from experts at UCB and Truveta as they demonstrate the power of Truveta’s AI-driven extraction of critical information from free text clinical notes to further research at UCB.
Advancing clinical research through unprecedented data and learning community for health
Partnering with Fierce Pharma, hear from an expert panel on the power of unprecedented data and what early patient insights have been unveiled.
Videos
Introducing Truveta Studio: Delivering the Health Data and Analytics the World Deserves Now
Truveta Announces Collaboration with Boston Scientific
Empowering Researchers with Truveta Studio
Health System leaders form Truveta to save lives with data
Helping Address Health Inequities with Data
The Importance of Data Quality for Medical Research
Truveta and LexisNexis Risk Solutions Partner to Improve Data Quality and Health Equity
Introducing the Truveta Platform and New COVID-19 Insights
Microsoft and Truveta Announce Strategic Partnership to Achieve Our Vision of Saving Lives with Data
Terry Myerson keynote at ViVE 2022
Featured research
A time-series analysis of anxiety diagnoses and prescriptions from January 2018 to January 2023
medRxiv
https://doi.org/10.1101/2023.12.21.23300415
Time-series analysis of first-time pediatric speech delays from 2018 to 2022
JAMA Pediatrics
doi:10.1001/jamapediatrics.2023.5226
Comparative effectiveness of semaglutide and tirzepatide for weight loss in adults with overweight and obesity in the US: A real-world evidence study
medRxiv
doi: https://doi.org/10.1101/2023.05.18.23290122