The recent Apple introduction of ResearchKit is a clear indicator that direct patient engagement by the life science industry is beginning to be realized. In conjunction with Apple's previous introduction of HealthKit, that enables consumers to begin to use iPhone apps to directly measure (in conjunction with devices like the FitBit) and track their own health status in real time, ResearchKit extends individual health monitoring to population health monitoring, allowing for much more data to be captured in conjunction with disease research, clinical trials, and other studies seeking to better understand disease metrics at the population level.
In increasing real time detailed patient medical data availability, ResearchKit opens up a whole new source of patient insights that should enable life science and healthcare researchers to accelerate disease research, improve patient care, and accelerate clinical trials. Recent FDA guidance on informed consent is also expected to contribute to accelerated adoption of solutions like ResearchKit by streamlining the patient informed consent process and more rapidly enrolling new patients into the process. Both internal iPhone sensors (i.e., GPS, accelerometer, camera, and microphone) and external technologies (e.g. FitBit, Bluetooth enabled blood pressure and glucose monitors) will enable ResearchKit to seamlessly capture patient data like never before, with real time streaming offering the potential to capture discrete events (e.g. a patient fall) or changes associated with daily routines (e.g. changes in heart rate during exercise or meals).
The addition of ResearchKit to the Apple App ecosystem is a powerful move forward, building on the consumer centric app ecosystem that people are comfortable with, can easily access, and regularly use. The key to successful implementation (as already demonstrated in a number of pilot efforts) will be demonstrating value to both ResearchKit end users (e.g. contributing to meaningful disease research or gaining personal insights on their own health conditions) and industry users (e.g. creating a new way to enroll clinical trial patients or gathering new data to support ongoing disease research).
The potential for failure seems remote so far and the opportunity is great. As always, comments and alternative opinions are welcome.