Applying Data and Systems Science to Clinical
Care
Starting in 2011, our small hernia team began to learn how to apply
systems science principles to real patient care. It was not an easy
process- we didn’t have a roadmap or textbook. We were trying to take
the principles of a scientific paradigm that had been used in other
industries- financial industry, baseball (known as Moneyball), etc. and
apply it to real patient care.
One issue was that unfortunately, the application of systems science in
other industries was used to improve the revenue and profit of the
organization and/or win against other competitors. It was not being used
to improve the value for the customers as we were attempting to do. So,
we had a lot of trial and error.
At first, we were measuring way too many data points. We spent too much
time and resources on trying to capture data, and not nearly enough time
and resources figuring out how to measure outcomes in terms of value or
put in Einstein’s words: Measure what Matters . We then had to
learn how to apply analytical tools and feedback loops to improve value.
Improved patient outcomes and lower costs began to happen quicker. The
hospital noticed because they were no longer losing money on our complex
hernia patients.6 They even began to make a modest
profit on each patient.
Turning Data into Knowledge – The Sense-Making
Process
Our most unexpected and important discovery came a few years after we
started, and it took another few years to mature our understanding of
the impact of our finding and learn what process improvement measures we
could implement to address the discovery.
One day, we were having one of our hernia team CQI meetings and we were
looking at the patients who had complications and less than ideal
outcomes. We looked at our operative techniques and the typical patient
factors like BMI and smoking, but nothing seemed to explain a pattern
for these patients who had bad outcomes. Then our patient care manager
spoke up and noted that the patients that had bad outcomes seemed to be
the same patients that were more challenging to deal with before
surgery.
She described patterns in these patients- some were angry, some had
unrealistic expectations (especially those expecting a “quick fix”),
some had high anxiety and/or controlling personalities. We did not yet
know how to measure this, but we thought that this might be a pattern.
We needed some sort of measurement tool. Lacking much expertise in this
area at the time, we settled on a subjective measure we called
“emotional complexity” and we put patients in categories of either
high, medium or low.
As the next 6-9 months went by, we recorded emotional complexity along
with a few dozen other data points. The next analysis of the data we ran
showed that the emotional complexity was the highest modifiable factor
predicting outcomes for our patients. The only factors with a higher
correlation to outcomes were the size of the hernia and the number of
prior hernia recurrences, neither of which could be modified.
Since we found that this was such an important factor, we invited a
small group of social science and social worker experts to our next CQI
meeting to develop a more robust measurement tool.7These findings came from principles of systems science using a variety
of analytical tools. As we learned about the impact of a patient’s
neuro-cognitive/emotional state on surgical outcomes from the analysis
of data in our own patients, we found that this is not that surprising
based on recent research in neuroscience and the neurophysiologic impact
that traumatic events can have on the brain. We indeed observed that
many of our patients suffered from traumatic events in our healthcare
system. This insight lead to pre-surgical evaluation of
neuro-cognitive/emotional issues and implementation of cognitive
behavioral therapy as part of a prehabilitation program for most
patients. The concepts of applying a CQI process to real patient care
are illustrated in Figure 3.