Stanford University medical researchers have published a paper this week in the journal of Biopharmaceutical statistics that looks at understanding some of the lessons learned from the Apple Heart Study and its implications for data management of future digital clinical trials. The paper also includes Sumbul Desai as one of the researchers. She is currently the VP of Health at Apple Inc.
The Apple Heart Study was launched through a research sponsorship by Apple, Inc., in November 2017 to determine whether the software on the Apple Watch could use data from the Watch’s heart-rate pulse sensor to identify atrial fibrillation, which is one of the most commonly diagnosed significant cardiac arrhythmias in the United States, affecting up to 6 million people.
Related Reading:
- LifeSpace, a new Stanford Research Health app begins its journey on the Apple App Store
- Mayo Clinic Researchers can now detect weak heart pumps from Apple Watch ECGs using AI
- How to use your MFI hearing aids with your iPhone and Apple Watch
- New Mayo Clinic study to validate Apple Watch ECG and symptoms data calls for million participants
- 3 Best Blood Pressure Monitors to use with Apple’s Health app
About the Apple Heart Study
By 2019, the study already had 400,000 participants making Apple Heart Study the largest virtual study to date.
Many contemporary clinical trials are designed with various levels of pragmatism including those that rely on digital-based interventions, giving rise to what is referred to as the digital clinical trial (DCT).
Digital clinical trials provide several advantages:
- First, digital tools may be used to recruit participants with little effort and may further relieve the burden on study participants (e.g., from having to come into the clinic) and on study staff (e.g., from coordinating visits and taking and recording measurements).
- Second, once a participant has consented to join the study, passive data collection can be advantageous over a traditional design with on-site data acquisition by collecting data in the participant’s normal environment and during activities of daily living.
- Third, many mobile devices enable a voluminous and rich stream of longitudinal data with measurements sampled much more frequently – opportunistically, or continuously – depending on the device.
The Apple health / Stanford University team faced several challenges in executing the digital clinical trial.
They identified three specific challenges that they faced in the Apple Heart Study (AHS):
- Participant adherence,
- Accounting for the unique number of participants enrolled in the trial; and
- Using timestamp data to establish longitudinal trajectories for participants.
According to Apple’s health team, these challenges needed solutions to ensure study integrity and high-quality data.
The team conducting the Apple health study found that the biggest lesson learned was the need to do a pilot study on the data flow, the data integration and the data integrity.
“Piloting on a number of participants may have provided us with insight into issues with integrating data across the diverse streams; information on participant duplication; the prevalence of missing data; the need for collecting data on reasons for missingness for certain measures; the need for timestamps; the noise involved in the time stamp variables; and perhaps even the need for a stronger engagement plan.”
If you are a digital health professional actively engaged in designing distributed clinical trials or planning to launch new digital health studies, this paper is worth reading.
The Apple Health and Stanford University team have done a wonderful job in laying out some of the lessons learned from one of the largest digital health study ever conducted.
