The Promise of Small Data for Telemedicine in Chronic Condition Management: A Real-World Case Series

*Corresponding author: Steven M. Schwartz*, Brigid Byrd, Helen Dempster and Tim Payne

Abstract

Connected care is defined as the “real-time, electronic communication between a patient and a provider, including telehealth, remote patient monitoring, and secure email communication between clinicians and their patients” (Alliance of Connected Care). Connected care can create a high-value interaction strategy with patients when it makes thoughtful use of commercially available digital health technologies with demonstrated both clinical and economic effectiveness. Karantis360™, is a home sensor technology that enables real-time tracking, data analytics and predictive care for personal (at home) care powered by IBM Watson Health. IndividuALLyticsTM is a telemedicine platform driven by a patent-pending an N-of-1 analytical engine and related digital dashboards that provides individual, patient level evaluation of treatment response. The underlying technology combines disparate digital health technology data with the best evidence-base guidelines with N-of-1 methodology. The output allows for creation of personalized treatments empirically tested at the patient level over time (aka over the course of care). When aggregated both within and across persons,
the time-ordered data can build predictive pathways of behavior and ensure the relevant care and medical treatments are in place to support effective medical and self-management of chronic illness. This case-series report describes the implementation of a joint home sensor technology (big data) and an N-of-1 analytic engine (small data) with three elderly consented volunteer customers-patients of Karantis360™. Each person underwent successive, 2-week behavioral change treatment phases to determine usability, utility regarding medical and self-management and any proximal effects on health risks.
Keywords
Telemedicine; Small data; n-of-1; Internet of things; Chronic conditions; Self-management; Predictive analytics.