Advances in sensor technology and data science have revolutionized the ability to remotely obtain and analyze clinically relevant information from individuals. Remote sensor data collected from Digital Health Technologies (DHTs) has the potential to overcome the challenges of suboptimal clinical outcomes in clinical investigation and offer patient-centric, objective clinical outcomes. Sensor-based DHTs, however, involve complex processing steps (algorithms) that can be confusing to clinical trialists who are used to working with patient reported outcomes (PRO) and clinician reported outcomes (ClinRO) collected during intermittent study visits. Through the last 20 years of supporting clinical research, we have learned that one of the key factors when using sensor-based DHTs for clinical investigation is the collection and retention of raw sensor data.
In this white paper, we clarify the myths about raw data and discuss why raw data is essential to maximize the clinical insights and the investment made into the clinical trials.