Medical device connectivity is becoming a standard IT program in most healthcare systems.  The clear advantages to improving data integrity and clinical workflow efficiency supported implementation initiatives.  Costs for such solutions are coming down as more vendors enter the market, and there are more IT and Healthcare Technology Management (i.e. CE or Biomed) professionals with experience to support these programs in house.

At the same time, the introduction of smart phone-based personal health records (i.e. Apple Health and Google Fit) has fueled the growth of the consumer wellness market, including a wide range of connected health devices.  Many hospitals have opened their EHR-supported patient portals to import this data as part of patient engagement initiatives.
For many, the next step is to feed this data into algorithms to either guide clinical care or calculate the probability that the patient requires a new level of medical attention.  Several of these tools are ad hoc solutions, customized to address the patient while in a certain level of care (rightfully so).

Healthcare leaders are beginning to look at all the possible solutions in order to develop a cohesive strategic roadmap that provides the appropriate level of predictive analytics that can follow the patient throughout the enterprise, including the home, while on a remote monitoring program.

The objective of this talk is to review the existing trends in predictive analytics, highlight certain innovative approaches, and discuss potential strategies to align these solutions with executive strategy.
Jennifer Jackson, Director, Connectivity, Masimo