Can we predict — and prevent — suicidal ideation from how individuals use their smartphones? What about hypertension, or post-surgical complications? What does a truly digital clinic look like? As the baseline of clinical care moves towards asynchronous telemedicine and precision medicine, digital phenotyping is poised to become invaluable in the physician’s toolkit. This temporal “digital fingerprint” of an individual or illness population could hold the key to unlocking a multimodal dynamic view of illness progression that spans individual to populations. The COVID-19 pandemic highlighted the value of patient-generated health data (PGHD) in clinical care to leverage deeper clinical insights that improve decision-making and patient outcomes. However, the lack of standards and easy-to-use tools continue to pose barriers in the use of high-frequency data generated from patient-owned smartphones and off-the-shelf wearable devices, such as Apple Watch and Google FitBit. In this talk, Aditya Vaidyam, the lead architect of the mindLAMP Platform, discusses current research and solutions to address these challenges. From pre/post-operative surveys to personalized just-in-time adaptive interventions, effective integration of PGHD, and digital phenotyping transforms into actionable clinical insight.
