This is my first entry in my new blog. Let me tell you a little about myself, and why I decided to start this blog.
My name is Randy Thompson. I am an Emergency Physician and I practice at the Billings Clinic in Billings Montana. I am also the Chief Medical Information Officer (CMIO) for the Billings Clinic. In my role as CMIO, I act as a bridge between the world of clinical medicine on one hand, and the Information Technology world on the other. As part of this effort I am branching out into the world of social media, and have established linked in and twitter accounts, and now have this blog. The information and views expressed in this blog will be mine, and do not reflect the views or policy of the Billings Clinic.
There are many things I would like to blog about, but the main reason for establishing this blog is to document the subjects that I feel very passionate about. These include my quest to become a data scientist, my interest in predictive monitoring (developing smarter bedside physiological monitors), and my interest in complexity science as it applies to human health and disease, as well as organizational dynamics and development.
One of my biggest goals in blogging is to chronicle my journey to become a data scientist. I have a huge interest in healthcare analytics in general and big data analytics in particular. We have had difficulties in funding, recruiting, and hiring data scientists, so I thought the best solution for me and my organization was for me to become one. Initially I tried to do this informally with books and online courses, but this Spring made the decision to do this formally. I will be starting an online Master’s program this Fall to accomplish this goal. I would like to document this journey from analytic novice to data scientist on this blog.
I also plan on documenting the field of predictive monitoring as time goes on. I will blog more about this in the future, but will briefly describe this effort. The bedside physiologic monitors used in healthcare have not fundamentally changed since the 1970’s. They provide information about what is happening to the patient now, and you can retrieve some information about what happened to them in the past. However, there are only a few monitoring systems that can predict what will happen to the patient in the future. Will they get better? Will they get worse? Will they develop sepsis(an overwhelming systemic infection)? Will they deteriorate and require a ventilator to help them breathe? These are the questions we would like the monitors to help us answer. In order to do this, we need to develop predictive algorithms that could be incorporated into these monitors, making them much smarter and more clinically relevant.
Hopefully, you will find this journey interesting and informative.