Using Digital Data to Predict CHD
Completed
Conditions studied: Cardiovascular Diseases
In brief
This project seeks to identify and characterize features derived from digital data (e.g. social media, online search, mobile media) which are associated with coronary heart disease (CHD) and related risk factors, and develop models that use digital data and conventional predictive models to predict CHD risk and health care utilization.
Key facts
- Study ID
- NCT04574882
- Run by
- University of Pennsylvania
- People needed
- 781
- Starts
- 2020-09-25
- Expected to finish
- 2025-06-01
- Last updated by the study team
- 2025-11-04
Who can join
Age: 30 and older, up to 74. Sex: any. Healthy volunteers: accepted.
You may qualify if…
- 30 - 74 years of age
- Willing to sign informed consent
- Primarily English speaking (for language analysis)
- Has an account on any of the following digital data platforms (Facebook, Instagram, Twitter Reddit, Google (gmail), or smartphone or wearable device such as Apple Health, Fitbit, Samsung Health, MapMyFitness or Garmin) and willing to share data
- If has social media account, Instagram or Facebook, willing to share historical and prospective data (60 days) If has Google (gmail) account, willing to download and share google takeout zip file
- If has smartphone or wearable device, willing to share step data
- Willing to share access to medical health records
- Willing to share healthcare insurance information
You may not qualify if…
- Patient does not meet age inclusion criteria above
- Does not use and post on digital data sources we are studying or unwilling to donate data
- Patient is in severe distress, e.g. respiratory, physical, or emotional distress
- Patient is intoxicated, unconscious, or unable to appropriately respond to questions
Where it is running
- University of Pennsylvania Health System — Philadelphia, Pennsylvania, United States
Full record on ClinicalTrials.gov
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