Aggregating multiple real-world data sources using a patient-centered health-data-sharing platform.
Sanket S DhruvaJoseph R RossJoseph G AkarBrittany CaldwellKarla ChildersWing ChowLaura CiaccioPaul M CoplanJun DongHayley J DykhoffStephen JohnstonTodd KelloggCynthia LongPeter A NoseworthyKurt RobertsAnindita SahaAndrew YooNilay D ShahPublished in: NPJ digital medicine (2020)
Real-world data sources, including electronic health records (EHRs) and personal digital device data, are increasingly available, but are often siloed and cannot be easily integrated for clinical, research, or regulatory purposes. We conducted a prospective cohort study of 60 patients undergoing bariatric surgery or catheter-based atrial fibrillation ablation at two U.S. tertiary care hospitals, testing the feasibility of using a patient-centered health-data-sharing platform to obtain and aggregate health data from multiple sources. We successfully obtained EHR data for all patients at both hospitals, as well as from ten additional health systems, which were successfully aggregated with pharmacy data obtained for patients using CVS or Walgreens pharmacies; personal digital device data from activity monitors, digital weight scales, and single-lead ECGs, and patient-reported outcome measure data obtained through surveys to assess post-procedure recovery and disease-specific symptoms. A patient-centered health-data-sharing platform successfully aggregated data from multiple sources.
Keyphrases
- electronic health record
- healthcare
- bariatric surgery
- public health
- atrial fibrillation
- patients undergoing
- mental health
- heart failure
- machine learning
- drinking water
- social media
- data analysis
- coronary artery disease
- weight loss
- depressive symptoms
- ejection fraction
- risk assessment
- human health
- catheter ablation
- obese patients
- health promotion
- acute coronary syndrome
- patient reported