BODEE-Weight Study
\ Download\ \ print page print page](/content/resources/a-new-model-for-real-world-data-in-weight-and-metabolic-health#/index.html) \ Print\ \ print page](/content/resources/a-new-model-for-real-world-data-in-weight-and-metabolic-health#/index.html) \ Share](/content/resources/a-new-model-for-real-world-data-in-weight-and-metabolic-health#/index.html)
Articles
A New Model for Real-World Data in Weight and Metabolic Health
Evidation’s BODEE-Weight Study recruited nearly 500 adults with BMI ≥25 in three weeks, pairing self-report, wearables, and EHR data to deliver a new interactive model for real-world evidence.
Introduction
GLP-1 receptor agonists are transforming the treatment landscape, not only for obesity, but for a range of interconnected conditions including type 2 diabetes, cardiovascular disease, and other disorders. As use expands across indications, so does the need for real-world evidence that reflects the full context of how individuals engage with these therapies: their motivations, behaviors, co-occurring conditions, and outcomes over time.
Claims and Electronic Health Record (EHR) data tell us what happened during a health system interaction, but they don’t explain why. They miss the behaviors, motivations, and perceptions that influence treatment choices and long-term outcomes. That gap is especially critical in rapidly evolving areas like weight loss, metabolic health, and GLP-1 use. They also miss what happens outside the clinic, where much of health activity actually unfolds. In an era of digital health solutions, telehealth platforms, and direct-to-consumer care, understanding real-world experiences means capturing activity outside the reach of traditional healthcare infrastructure.
Evidation is addressing these needs.
At the beginning of May 2025, we launched the Building an Observational Dataset of Emerging Evidence (BODEE)-Weight Study to rapidly assemble a richly contextualized real-world cohort of adults with BMI ≥25. In just three weeks, nearly 500 individuals completed the study—completing a survey, consenting to retrospective wearable data collection, and connecting their EHRs to create one integrated dataset.
Unlike static registries or retrospective datasets, this model is interactive by design. It’s built on a direct connection with participants that enables future engagement, recontact, and continuous learning.
The result: a real-world cohort with the depth, diversity, and dynamic connectivity to support research, development, and commercialization across a wide range of conditions.
A Multi-Dimensional View of Weight Management
The BODEE-Weight Study captures a layered, longitudinal view of weight management behaviors, experiences, and outcomes, rooted in the real lives of a demographically diverse group of adults across the U.S.
Participants contributed three key types of data:
- Self-reported weight history, medication use, mental health, and treatment motivations
- Up to two years of retrospective activity, sleep, and heart rate data from wearables
- Linked EHR data (mediated through an integration with 1upHealth), including labs, diagnoses, and medication history
This combination enables a level of context rarely available in real-world evidence. Instead of isolated data points, we can now see how self-reported goals, daily behaviors, and clinical events align, or diverge, within the same individuals over time.
For researchers and drug developers, this offers a powerful foundation to study treatment journeys, segment populations, validate outcomes, and explore the factors driving real-world response.
Targeted for Today’s Treatment Landscape
The cohort was purpose-built to reflect the evolving realities of weight management and metabolic health. We designed the cohort to capture real-world experiences that align with emerging therapeutic use and unmet evidence needs.
Key design characteristics of the cohort include:
- ~50% of participants currently using a GLP-1 medication
50% with a recent lab result (within 90 days)
- Balanced demographics across participant sex and race/ ethnicity
Participants were recruited from Evidation’s 5 million-member community based on real-time eligibility signals: prior self- or device-reported BMI ≥25, active use of a connected wearable, and willingness to link their EHRs.
Importantly, none of the participants are currently enrolled in weight management clinical trials. This ensures the dataset reflects naturalistic decision-making and treatment patterns, not protocol-driven behaviors, making it more applicable for real-world research and development.
Designed for Speed and Scale
The BODEE-Weight Study was made possible by Evidation’s existing infrastructure—an end-to-end platform that combines technology, direct relationships with individuals, and real-world data collection at scale. By tapping into pre-existing connections with engaged individuals, we dramatically reduced both participant burden and time to insight.
Before day one of the study:
- Demographic, lifestyle, and medical history data were pre-collected through the Evidation member experience
- Up to two years of behavioral data had already been logged through daily check-ins and passive tracking (e.g., steps, sleep, heart rate)
- Eligibility signals like BMI, device connectivity, and survey activity enabled rapid identification and activation
Leveraging the 1upHealth platform, study participants could instantly share clinical data from their provider’s EHR. 1upHealth enabled seamless data integrations into the study flow, ensuring a high completion rate with minimal friction for participants.
The study closed after just three weeks. At the time of close:
- 493 participants completed all study activities, including EHR connection, wearable data sharing, and survey completion
- 255 participants (52%) reported taking a GLP-1
- 174 participants (35%) identified as non-white
- 276 participants (55%) identified as female
- Participants reported 100+ unique health conditions
- Participants represented 49 out of 50 US states
This model demonstrates how deep, permissioned datasets can be assembled in a fraction of the time traditional studies require, without sacrificing depth, diversity, or longitudinal potential.
Early Insights from Linked EHRs
Initial analysis of permissioned EHR data underscores the richness and relevance of the BODEE-Weight cohort:
- 43,700+ clinical measurements - including weight, blood pressure, cholesterol, and HbA1c
- 8,800+ medication records
- 5,700+ diagnosis entries
Among participants with HbA1c values, the average number of lab results per person is 2.3, indicating meaningful longitudinal coverage within the clinical record. When combined with behavioral data and self-reported experiences, these records create opportunities for:
- Outcome modeling grounded in both clinical and lifestyle data
- Segmentation of populations by therapy type, comorbidity, or behavioral profile
- Validation of self-reported data against clinical markers, strengthening credibility for future studies
Unlocking Future Research Potential
This dataset is more than a snapshot, it’s a foundation for continuous learning.
As a next step, Evidation is launching an expanded research cohort focused on obesity and GLP-1 usage. The goal: to generate rich, multi-modal longitudinal data while introducing a fit-for-purpose participant experience built to promote long-term engagement and retention within the cohort.
This new cohort will include symptom tracking and prospectively collect lab results and genomic data, alongside surveys, wearable data, and EHRs. Together, these data streams will enable a high-resolution view of the patient journey, supporting strategic initiatives across research, development, and commercialization.
Unlike traditional Real-World Evidence (RWE) models that rely on static datasets, Evidation is introducing a paradigm that is interactive by design. Participants can be re-engaged as their health evolves, new therapies enter the market, or new research questions arise. This creates a flexible, living cohort capable of supporting prospective studies, embedded sub-studies, and adaptive evidence generation over time.
What We’ve Shown
The BODEE-Weight study demonstrated what’s possible when real-world data is collected from direct, ongoing relationships with individuals. It showed that self-reported experiences, wearable data, and EHRs can be rapidly integrated to create a richly contextualized dataset—assembled in weeks, and built to reflect how people engage with therapies in everyday life.
For teams across research, development, medical, and commercial functions, this model represents more than just speed. It’s a shift toward real-world evidence that’s richer, more adaptive, and more reflective of how health actually unfolds in people’s daily lives.
Want a deeper look at the data or explore custom cohort development? Contact us to access more information on the BODEE-Weight cohort, or to discuss how Evidation can power your RWE needs: https://evidation.com/for-customers/contact-us
Have questions?
Subscribe to our business newsletter
Articles
A New Model for Real-World Data in Weight and Metabolic Health
Introduction
Evidation is addressing these needs.
A Multi-Dimensional View of Weight Management
Participants contributed three key types of data:
Targeted for Today’s Treatment Landscape
Key design characteristics of the cohort include:
Designed for Speed and Scale
Before day one of the study:
The study closed after just three weeks. At the time of close:
Early Insights from Linked EHRs
Initial analysis of permissioned EHR data underscores the richness and relevance of the BODEE-Weight cohort:
- 43,700+ clinical measurements - including weight, blood pressure, cholesterol, and HbA1c
- 8,800+ medication records
- 5,700+ diagnosis entries
Unlocking Future Research Potential
This dataset is more than a snapshot, it’s a foundation for continuous learning.
What We’ve Shown
Related work
News News\ \ January 8, 2026\ \ Evidation Launches Temporal Proteomics Platform to Power Autoimmune Research\ \ ReAd
News News\ \ December 16, 2025\ \ Evidation Shares Insights on Real-World GLP-1 Dosing Behaviors from Over 60,000 Individuals\ \ ReAd
News News\ \ December 2, 2025\ \ Evidation Appoints Dr. Ghazanfar Khan as Chief Medical Officer\ \ ReAd
Have questions?
Subscribe to our business newsletter
Articles
A New Model for Real-World Data in Weight and Metabolic Health
Introduction
Evidation is addressing these needs.
A Multi-Dimensional View of Weight Management
Participants contributed three key types of data:
Targeted for Today’s Treatment Landscape
Key design characteristics of the cohort include:
Designed for Speed and Scale
Before day one of the study:
The study closed after just three weeks. At the time of close:
Early Insights from Linked EHRs
Initial analysis of permissioned EHR data underscores the richness and relevance of the BODEE-Weight cohort:
- 43,700+ clinical measurements - including weight, blood pressure, cholesterol, and HbA1c
- 8,800+ medication records
- 5,700+ diagnosis entries
Unlocking Future Research Potential
This dataset is more than a snapshot, it’s a foundation for continuous learning.
What We’ve Shown
Related work
Have questions?
Subscribe to our business newsletter
\ Download\ \ print page](/content/resources/a-new-model-for-real-world-data-in-weight-and-metabolic-health#/index.html) \ Print\ \ print page](/content/resources/a-new-model-for-real-world-data-in-weight-and-metabolic-health#/index.html) \ Share](/content/resources/a-new-model-for-real-world-data-in-weight-and-metabolic-health#/index.html)
Articles
A New Model for Real-World Data in Weight and Metabolic Health
Evidation and the Duke Big Ideas Lab have announced a partnership that aims to find ways to both increase representation of underserved populations and improve adherence among all participants in digital health studies.
The organizations are working together to build an analytic structure that will be available to other digital health researchers, helping to better predict study participation, adherence, and retention. Click below to read more about the project, led by Iredia M. Olaye, PhD, MSc, MHA, of Covered By Group and Evidation, in HealthLeaders.
Good reads
Patient Data Access News
Digital Divide Goes Beyond Broadband, Rests with Digital Health Literacy
Stat
Paying Research Participants — A Lot — May Be a Key to Increasing Diversity in Studies
Outsourcing Pharma
Bioethics International Reveals Index to Score Pharma on Trial Diversity
PatientEngagementHIT
$35 Cap on Insulin Could Boost Medication Adherence, Satisfaction
Healthcare Dive
How Technology Will Shape Healthcare in 2023
What we’ve been up to
Patient Data Access News
Using Real RWD to Better Understand and Engage Neuro Patients
Evidation
Predictors of Seeking Care for Influenza-Like Illness in a Novel Digital Study
Builin
Evidation is a 2023 Best Place to Work!
Upcoming events
Thanks to everyone who took the time to meet with us in San Francisco at this year’s J.P. Morgan Annual Conference and its surrounding events. Our team looks forward to staying in touch and helping you produce better health outcomes in 2023!
Get to know your Evidation team
Bertina Yen, Evidation's Senior Vice President of People & Community
Bertina Yen is Evidation's Senior Vice President of People & Community, where she is responsible for the end-to-end employee experience and building a community that supports everyone's ability to show up as their authentic selves and perform their best work. Prior to joining Evidation, Bertina served as EVP overseeing clinical teams, product management, marketing, and product development at Zynx Health, driving development of evidence-based clinical decision support solutions that improve health and financial outcomes.
Bertina received her BAS from Stanford, then completed her MD and residency in internal medicine at UC San Diego. She also holds an MPH in health services administration from UCLA.
Bertina is the resident DJ at Evidation and sources the music that is played during the All-Employee Meetings. Outside of work, she enjoys hiking, traveling, and watching anything with a live audience (sporting events, plays, movies). She also starts every morning by completing at least one crossword puzzle!
Connect with Bertina here
Subscribe to our business newsletter
Articles
A New Model for Real-World Data in Weight and Metabolic Health
Introduction
Evidation is addressing these needs.
A Multi-Dimensional View of Weight Management
Participants contributed three key types of data:
Targeted for Today’s Treatment Landscape
Key design characteristics of the cohort include:
Designed for Speed and Scale
Before day one of the study:
The study closed after just three weeks. At the time of close:
Early Insights from Linked EHRs
Initial analysis of permissioned EHR data underscores the richness and relevance of the BODEE-Weight cohort:
- 43,700+ clinical measurements - including weight, blood pressure, cholesterol, and HbA1c
- 8,800+ medication records
- 5,700+ diagnosis entries
Unlocking Future Research Potential
This dataset is more than a snapshot, it’s a foundation for continuous learning.
What We’ve Shown
Related work
Have questions?
Subscribe to our business newsletter
Articles
A New Model for Real-World Data in Weight and Metabolic Health
Introduction
Evidation is addressing these needs.
A Multi-Dimensional View of Weight Management
Participants contributed three key types of data:
Targeted for Today’s Treatment Landscape
Key design characteristics of the cohort include:
Designed for Speed and Scale
Before day one of the study:
The study closed after just three weeks. At the time of close:
Early Insights from Linked EHRs
Initial analysis of permissioned EHR data underscores the richness and relevance of the BODEE-Weight cohort:
- 43,700+ clinical measurements - including weight, blood pressure, cholesterol, and HbA1c
- 8,800+ medication records
- 5,700+ diagnosis entries
Unlocking Future Research Potential
This dataset is more than a snapshot, it’s a foundation for continuous learning.
What We’ve Shown
Related work
Have questions?
Subscribe to our business newsletter
Articles
A New Model for Real-World Data in Weight and Metabolic Health
Introduction
Evidation is addressing these needs.
A Multi-Dimensional View of Weight Management
Participants contributed three key types of data:
Targeted for Today’s Treatment Landscape
Key design characteristics of the cohort include:
Designed for Speed and Scale
Before day one of the study:
The study closed after just three weeks. At the time of close:
Early Insights from Linked EHRs
Initial analysis of permissioned EHR data underscores the richness and relevance of the BODEE-Weight cohort:
- 43,700+ clinical measurements - including weight, blood pressure, cholesterol, and HbA1c
- 8,800+ medication records
- 5,700+ diagnosis entries
Unlocking Future Research Potential
This dataset is more than a snapshot, it’s a foundation for continuous learning.
What We’ve Shown
Related work
Have questions?
Subscribe to our business newsletter
A New Model for Real-World Data in Weight and Metabolic Health
June 5, 2025
Articles
A New Model for Real-World Data in Weight and Metabolic Health
June 5, 2025
Articles
A New Model for Real-World Data in Weight and Metabolic Health
June 5, 2025
Articles
A New Model for Real-World Data in Weight and Metabolic Health
June 5, 2025
Articles
Introduction
Evidation is addressing these needs.
A Multi-Dimensional View of Weight Management
Participants contributed three key types of data:
Targeted for Today’s Treatment Landscape
Key design characteristics of the cohort include:
Designed for Speed and Scale
Before day one of the study:
The study closed after just three weeks. At the time of close:
Early Insights from Linked EHRs
Initial analysis of permissioned EHR data underscores the richness and relevance of the BODEE-Weight cohort:
- 43,700+ clinical measurements - including weight, blood pressure, cholesterol, and HbA1c
- 8,800+ medication records
- 5,700+ diagnosis entries
Unlocking Future Research Potential
This dataset is more than a snapshot, it’s a foundation for continuous learning.
What We’ve Shown
Related Therapeutic Areas:
[Subscribe to our monthly business newsletter