Tidepool Big Data Donation Project

Data Partners

Our Data Partners

How your data will be put to use

With your help, our goal is to provide our data partners with the best opportunity for ground-breaking research. Real-world datasets will help diabetes researchers, device makers and other innovators innovate faster, create better products, and expand the boundaries of their knowledge about diabetes.

We will always be completely transparent with you about what we do with the data you donate – and we’re excited to share how our data partners are using the data, and what they have learned through their research.

Data Partner Research

Here, we will keep you up-to-date on all data partners. We’ll share how each data partner intends on utilizing anonymized, de-identified donated data, and what their results are after publication where possible. We’ve just scratched the surface of what’s possible.

Tidepool and Dexcom are working together to develop technologies that better serve the needs of the diabetes community. To facilitate this collaboration, Tidepool is providing Dexcom continuous glucose monitoring (CGM) datasets with concurrent insulin and meal data. The data will be used by Dexcom engineers to develop insights that will help patients on multiple daily injections and pump therapy achieve better outcomes with less effort.

Eli Lilly & Co. is discovering and developing new, innovative drug delivery systems and treatment technologies to realize our vision of improving global health into the 21st Century. Both at our Cambridge Innovation Center and at our corporate research facilities, we will leverage these anonymized datasets as we develop new delivery devices, algorithms and mobile medical applications, which will provide one with actionable insight for simpler, more effective diabetes management.

DreaMed Diabetes is collaborating with Tidepool to improve its groundbreaking, cloud-based Advisor analytics technology for insulin treatment plan optimization. The datasets provided by Tidepool are being used to improve and further develop the sophisticated learning algorithms for the Advisor patient-specific dosing decision-support solution.

Tidepool and Stanford are developing clinical processes and advanced analytics to improve the quality and convenience of diabetes care. Tidepool will provide Stanford with continuous glucose monitoring data, other related data (e.g., insulin and meal data), and access to Tidepool APIs. A team of faculty and students from Stanford Medicine and Stanford Engineering will use these data to gain a better understanding of patient progress, opportunities to improve long-term outcomes, and to set the groundwork for improving access to convenient telemedicine care options.

Rice University is collaborating with Tidepool to develop data-driven solutions and digital tools for improved self-management of diabetes. This research includes investigating algorithms to understand the effects of individual management patterns and developing novel visualization tools to quickly extract actionable insights from longitudinal data. The overarching goal is to further improve personalized decision support for people living with diabetes.

Students from the Master’s of Science in Health Informatics program at the University of San Francisco are working with Tidepool to clean, validate, and improve the quality of donated CGM and pump data. The current projects include, but are not limited to, assessing the accuracy of local time estimates, deduplicating data, and data inference via machine learning.

Tidepool and Oregon Health & Science University (OHSU) are collaborating to develop new automated insulin delivery systems and decision support systems for use in helping people with type 1 diabetes better control their glucose levels. A group of faculty and students in the Artificial Intelligence for Medical Systems (AIMS) lab within the Biomedical Engineering Department at OHSU is using the Tidepool data sets to design, develop, and evaluate new machine learning and signal processing algorithms that may ultimately be integrated into the OHSU artificial pancreas and the OHSU smart-phone based decision support tools currently under development.

The Diabetes Technology Research Team at Stanford University will be using insulin, mealtime, and continuous glucose monitoring data provided by Tidepool. The research team will analyze adherence to various technologies, identify patterns, and evaluate the effects of insulin bolusing behavior on glycemic control.

Last Updated: September 21, 2018
Interested in becoming a data partner?

Get in touch

If you are a research organization or device maker and are interested in the Tidepool Big Data Donation Project, email us at bigdata@tidepool.org.