John R. Zaleski, PhD, CPHIMS

Yesterday I attended an NSF grant status review at the University of Pennsylvania. I had a chance to visit with some old friends of mine and to reacquaint with some new friends. It is striking to me the energy in the area of systems engineering in the medical field that has taken place since I was a student there some 16-20 years ago. When I was a student at PENN, the notion of applying systems engineering to medicine was not even a field: it was the study of one lone student in the department. I am happy to see such growth.

While I cannot get into the specifics of the discussions of the various projects, I will lend my overall impressions vis a vis the types of concepts that are being focused on, and that are a major focus in healthcare and medicine today.

Useful use (as opposed to Meaningful Use) of data within the enterprise is a huge objective in the treatment of patients:

1) using past information and history to assist in reducing the likelihood of readmissions;

2) better management of those patients, particularly in critical care who are likely to suffer from sepsis, ventilator acquired pneumonia, etc.;

3) reduction in the number of medical device alarms that bombard the clinicians;

4) better use of integrated information through application of interoperability standards.

All of these areas are of high value. As I noted in my “outbrief” at the end of the meeting, my views, while highly motivated by pure research, are more governed by the pragmatic from the perspective that I live with customers and their problems, and this motivates me to write on areas that are both pragmatic but motivated by research interests of my own.

The term “Big Data” has often been used, and by itself is nothing more than marketing tripe. To my mind, systems engineering and the various concepts related to it, from situational awareness to systems of systems engineering, has been around a long, long time, primarily as related to the aerospace/defense industry (a former industry of my own). What is becoming more and more clear is that the effective use of data–not just mining it for whatever trend falls out of the net–is the real value. Combining specific information associated with diagnoses and then determining from that which patients are likely to be readmitted; which patients are likely to respond favorably from a certain course of treatment, etc. are outcomes assessments that carry with them great value but also great responsibility.

Pragmatically, most hospital systems that I have been involved with professionally are still at the stage of connecting the dots: getting information from point A to point B. As is typically the case, large academic research institutions are out in front looking at the why and wherefore of what to do with the information–the futuristic. Once something becomes generally accepted in clinical practice, that is when the futuristic becomes commonplace.

Yet, something else is happening now: I see even smaller community hospitals beginning to look at the futuristic from the perspective of how it can assist in the commonplace practice of medicine. It is not just the matter of connecting the dots of how data gets from one point to another; or how certain functions (e.g.: CPOE, eMAR) need to be rolled out into the institution, but what happens with the information after that. Interestingly, a motivation for this is the care and management of patients with chronic ailments and/or co-morbidities. Managing the patient once he or she leaves the hospital is of much more interest, regardless of the size of the institution.

Assisting in this management is the effective study of past history and increasing situational awareness surrounding patients in their home environments as well as in the hospital and how they compare with respect to peers. This is the focus and benefit of big data–where it is going. And we are at the beginning.