Components of an Individualized Medicine Approach

You may have noticed that the majority of the content on this site is focused around the analytics of individual-level data, and the need for a different application of statistics than what is typically used in healthcare research.   The reason is that analytics in many ways represents the convergence of information and application, and we believe is the cornerstone from which individual information can be applied to the individual, rather than at a population level (see prior post for more details).  However, sometimes it can be useful to take a step back and understand where analysis fits into the greater goal of providing an individualized approach to health and medicine, and the challenges that extend well beyond analytics that must be overcome in order to reach this goal.  In the next series of posts, we will address each of these challenges in detail, starting from a high level and delving into some of the details behind how these challenges are being addressed with the Individualized Data Analysis Organization, and outside our institution.

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We have identified 5 components of the individualized approach that must be integrated in order to create an adaptive, dynamic, and self-contained system for individualized medicine:

1. Data collection, including sensors and monitors
2. User interface/application
3. Clinical application
4. Analytics
5. Feedback and improvement

In the following series of posts, we will address each component with the goal of explaining how that component fits into the overall process, the technical knowledge and capabilities needed for implementation, and future directions of development.  Although none will be entirely encompassing, hopefully this series will provide guidance and food-for-thought for anyone interested in bringing individualized data analysis to modern healthcare.